A one-dimensional interactive soil-atmosphere model for testing formulations of surface hydrology

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Eagleson, Peter S.

1990-01-01

A model representing a soil-atmosphere column in a GCM is developed for off-line testing of GCM soil hydrology parameterizations. Repeating three representative GCM sensitivity experiments with this one-dimensional model demonstrates that, to first order, the model reproduces a GCM's sensitivity to imposed changes in parameterization and therefore captures the essential physics of the GCM. The experiments also show that by allowing feedback between the soil and atmosphere, the model improves on off-line tests that rely on prescribed precipitation, radiation, and other surface forcing.

Soil mapping and process modeling for sustainable land use management: a brief historical review

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Pereira, Paulo; Muñoz-Rojas, Miriam; Miller, Bradley A.; Cerdà, Artemi; Parras-Alcántara, Luis; Lozano-García, Beatriz

2017-04-01

Basic soil management goes back to the earliest days of agricultural practices, approximately 9,000 BCE. Through time humans developed soil management techniques of ever increasing complexity, including plows, contour tillage, terracing, and irrigation. Spatial soil patterns were being recognized as early as 3,000 BCE, but the first soil maps didn't appear until the 1700s and the first soil models finally arrived in the 1880s (Brevik et al., in press). The beginning of the 20th century saw an increase in standardization in many soil science methods and wide-spread soil mapping in many parts of the world, particularly in developed countries. However, the classification systems used, mapping scale, and national coverage varied considerably from country to country. Major advances were made in pedologic modeling starting in the 1940s, and in erosion modeling starting in the 1950s. In the 1970s and 1980s advances in computing power, remote and proximal sensing, geographic information systems (GIS), global positioning systems (GPS), and statistics and spatial statistics among other numerical techniques significantly enhanced our ability to map and model soils (Brevik et al., 2016). These types of advances positioned soil science to make meaningful contributions to sustainable land use management as we moved into the 21st century. References Brevik, E., Pereira, P., Muñoz-Rojas, M., Miller, B., Cerda, A., Parras-Alcantara, L., Lozano-Garcia, B. Historical perspectives on soil mapping and process modelling for sustainable land use management. In: Pereira, P., Brevik, E., Muñoz-Rojas, M., Miller, B. (eds) Soil mapping and process modelling for sustainable land use management (In press). Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. 2016. Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274.

An integrated Modelling framework to monitor and predict trends of agricultural management (iMSoil)

NASA Astrophysics Data System (ADS)

Keller, Armin; Della Peruta, Raneiro; Schaepman, Michael; Gomez, Marta; Mann, Stefan; Schulin, Rainer

2014-05-01

Agricultural systems lay at the interface between natural ecosystems and the anthroposphere. Various drivers induce pressures on the agricultural systems, leading to changes in farming practice. The limitation of available land and the socio-economic drivers are likely to result in further intensification of agricultural land management, with implications on fertilization practices, soil and pest management, as well as crop and livestock production. In order to steer the development into desired directions, tools are required by which the effects of these pressures on agricultural management and resulting impacts on soil functioning can be detected as early as possible, future scenarios predicted and suitable management options and policies defined. In this context, the use of integrated models can play a major role in providing long-term predictions of soil quality and assessing the sustainability of agricultural soil management. Significant progress has been made in this field over the last decades. Some of these integrated modelling frameworks include biophysical parameters, but often the inherent characteristics and detailed processes of the soil system have been very simplified. The development of such tools has been hampered in the past by a lack of spatially explicit soil and land management information at regional scale. The iMSoil project, funded by the Swiss National Science Foundation in the national research programme NRP68 "soil as a resource" (www.nrp68.ch) aims at developing and implementing an integrated modeling framework (IMF) which can overcome the limitations mentioned above, by combining socio-economic, agricultural land management, and biophysical models, in order to predict the long-term impacts of different socio-economic scenarios on the soil quality. In our presentation we briefly outline the approach that is based on an interdisciplinary modular framework that builds on already existing monitoring tools and model components that are currently in development: (i) the socio-economic agent-based model SWISSland; (ii) a land management downscaling approach that provides crop rotation, fertilisers and pesticides application rates for each land management unit, and (iii) the agro-ecosystem model EPIC, which is currently being calibrated with long-term soil measurements and agricultural management data provided by the Swiss Soil Monitoring Network. Moreover, the IMF will make use of land cover information derived from remote sensing to continuously update predictions. The IMF will be tested on two case study regions to develop indicators of sustainable soil management that can be implemented into Swiss policies.

Terrestrial ecosystem process model Biome-BGCMuSo v4.0: summary of improvements and new modeling possibilities

NASA Astrophysics Data System (ADS)

Hidy, Dóra; Barcza, Zoltán; Marjanović, Hrvoje; Zorana Ostrogović Sever, Maša; Dobor, Laura; Gelybó, Györgyi; Fodor, Nándor; Pintér, Krisztina; Churkina, Galina; Running, Steven; Thornton, Peter; Bellocchi, Gianni; Haszpra, László; Horváth, Ferenc; Suyker, Andrew; Nagy, Zoltán

2016-12-01

The process-based biogeochemical model Biome-BGC was enhanced to improve its ability to simulate carbon, nitrogen, and water cycles of various terrestrial ecosystems under contrasting management activities. Biome-BGC version 4.1.1 was used as a base model. Improvements included addition of new modules such as the multilayer soil module, implementation of processes related to soil moisture and nitrogen balance, soil-moisture-related plant senescence, and phenological development. Vegetation management modules with annually varying options were also implemented to simulate management practices of grasslands (mowing, grazing), croplands (ploughing, fertilizer application, planting, harvesting), and forests (thinning). New carbon and nitrogen pools have been defined to simulate yield and soft stem development of herbaceous ecosystems. The model version containing all developments is referred to as Biome-BGCMuSo (Biome-BGC with multilayer soil module; in this paper, Biome-BGCMuSo v4.0 is documented). Case studies on a managed forest, cropland, and grassland are presented to demonstrate the effect of model developments on the simulation of plant growth as well as on carbon and water balance.

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.

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.

On the Need to Establish an International Soil Modeling Consortium

NASA Astrophysics Data System (ADS)

Vereecken, H.; Vanderborght, J.; Schnepf, A.

2014-12-01

Soil is one of the most critical life-supporting compartments of the Biosphere. Soil provides numerous ecosystem services such as a habitat for biodiversity, water and nutrients, as well as producing food, feed, fiber and energy. To feed the rapidly growing world population in 2050, agricultural food production must be doubled using the same land resources footprint. At the same time, soil resources are threatened due to improper management and climate change. Despite the many important functions of soil, many fundamental knowledge gaps remain, regarding the role of soil biota and biodiversity on ecosystem services, the structure and dynamics of soil communities, the interplay between hydrologic and biotic processes, the quantification of soil biogeochemical processes and soil structural processes, the resilience and recovery of soils from stress, as well as the prediction of soil development and the evolution of soils in the landscape, to name a few. Soil models have long played an important role in quantifying and predicting soil processes and related ecosystem services. However, a new generation of soil models based on a whole systems approach comprising all physical, mechanical, chemical and biological processes is now required to address these critical knowledge gaps and thus contribute to the preservation of ecosystem services, improve our understanding of climate-change-feedback processes, bridge basic soil science research and management, and facilitate the communication between science and society. To meet these challenges an international community effort is required, similar to initiatives in systems biology, hydrology, and climate and crop research. Our consortium will bring together modelers and experimental soil scientists at the forefront of new technologies and approaches to characterize soils. By addressing these aims, the consortium will contribute to improve the role of soil modeling as a knowledge dissemination instrument in addressing key global issues and stimulate the development of translational research activities. This presentation will provide a compelling case for this much-needed effort, with a focus on tangible benefits to the scientific and food security communities.

Soil and climate modelling to explain soil differences in MIS5e and MIS13 on the Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Finke, P. A.; Yu, Y.; Yin, Q.; Bernardini, N. J.

2016-12-01

Objective Proxy records indicate that MIS5 (about 120 ka ago) was warmer than MIS13 (about 500 ka ago). Nevertheless, MIS13-soils in the Chinese loess plateau (105 -115°E and 30-40°N) are stronger developed than MIS5-soils. This has been attributed to a stronger East Asian summer monsoon. Other differences are interglacial lengths and loess deposition rates. We aimed to find explanations for soil development differences by using a soil formation model (SoilGen) with climatic inputs obtained from an earth system model (LOVECLIM). Material and Methods The LOVECLIM model is driven by time-varying insolation and greenhouse gas concentrations and was run to give monthly values for temperature, precipitation and evaporation as well the dominant vegetation type. Model results for were corrected for systematic differences between present-day observation data and simulation. Reconstructions were made for both interglacials of the amount of inblown loess, and the mineralogy and grain size distribution of the initial loess as well as the dust. These data were fed into the SoilGen model, which was used to calculate various soil parameters with depth and over time. Results Simulations show a stronger developed MIS13 soil, in terms of weathering (loss of anorthite), and redistribution of calcite, gypsum and clay. This corresponds to observed paleosoils. MIS13-soils are more leached. As simulated temperatures and annual precipitation between MIS5 and MIS13 did not vary strongly, the greater length of MIS13 seemed the main explanation for the stronger leaching and weathering. Closer analysis however showed a larger number of months in MIS13 with a precipitation surplus, even when only considering the first 22 ka. Only in such months significant leaching can occur. Conclusion Using simulation models it was demonstrated that the stronger soil expression in MIS13 than in MIS5 is likely caused by more months with a precipitation surplus, in combination with a longer duration of MIS13.

Reactive transport modeling

USDA-ARS?s Scientific Manuscript database

This special section in the Vadose Zone Journal focusing on reactive transport modeling was developed from a special symposium jointly sponsored by the Soil Physics and Soil Chemistry Divisions of the Soil Science Society of America at the 2010 annual meetings held in Long Beach, CA. It contains eig...

Cracking up (and down): Linking multi-domain hydraulic properties with multi-scale hydrological processes in shrink-swell soils

NASA Astrophysics Data System (ADS)

Stewart, R. D.; Rupp, D. E.; Abou Najm, M. R.; Selker, J. S.

2017-12-01

Shrink-swell soils, often classified as Vertisols or vertic intergrades, are found on every continent except Antarctica and within many agricultural and urban regions. These soils are characterized by cyclical shrinking and swelling, in which bulk density and porosity distributions vary as functions of time and soil moisture. Crack networks that form in these soils act as dominant environmental controls on the movement of water, contaminants, and gases, making it important to develop fundamental understanding and tractable models of their hydrologic characteristics and behaviors. In this study, which took place primarily in the Secano Interior region of South-Central Chile, we quantified soil-water interactions across scales using a diverse and innovative dataset. These measurements were then utilized to develop a set of parsimonious multi-domain models for describing hydraulic properties and hydrological processes in shrink-swell soils. In a series of examples, we show how this model can predict porosity distributions, crack widths, saturated hydraulic conductivities, and surface runoff (i.e., overland flow) thresholds, by capturing the dominant mechanisms by which water moves through and interacts with clayey soils. Altogether, these models successfully link small-scale shrinkage/swelling behaviors with large-scale thresholds, and can be applied to describe important processes such as infiltration, overland flow development, and the preferential flow and transport of fluids and gases.

Geotechnical centrifuge use at University of Cambridge Geotechnical Centre, August-September 1991

NASA Astrophysics Data System (ADS)

Gilbert, Paul A.

1992-01-01

A geotechnical centrifuge applies elevated acceleration to small-scale soil models to simulate body forces and stress levels characteristic of full-size soil structures. Since the constitutive behavior of soil is stress level development, the centrifuge offers considerable advantage in studying soil structures using models. Several experiments were observed and described in relative detail, including experiments in soil dynamics and liquefaction study, an experiment investigation leaning towers on soft foundations, and an experiment investigating migration of hot pollutants through soils.

Linkage of a Physically Based Distributed Watershed Model and a Dynamic Plant Growth Model

DTIC Science & Technology

2006-12-01

i.e., Universal Soil Loss Equation ( USLE ) factors, K, C, and P). The K, C, and P factors are empiri- cal coefficients with the same conceptual...with general ecosystem models designed to make long-term projections of ecosystem dynamics. This development effort investigated the linkage of soil ...20 EDYS soil module

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Soil moisture dynamics modeling considering multi-layer root zone.

PubMed

Kumar, R; Shankar, V; Jat, M K

2013-01-01

The moisture uptake by plant from soil is a key process for plant growth and movement of water in the soil-plant system. A non-linear root water uptake (RWU) model was developed for a multi-layer crop root zone. The model comprised two parts: (1) model formulation and (2) moisture flow prediction. The developed model was tested for its efficiency in predicting moisture depletion in a non-uniform root zone. A field experiment on wheat (Triticum aestivum) was conducted in the sub-temperate sub-humid agro-climate of Solan, Himachal Pradesh, India. Model-predicted soil moisture parameters, i.e., moisture status at various depths, moisture depletion and soil moisture profile in the root zone, are in good agreement with experiment results. The results of simulation emphasize the utility of the RWU model across different agro-climatic regions. The model can be used for sound irrigation management especially in water-scarce humid, temperate, arid and semi-arid regions and can also be integrated with a water transport equation to predict the solute uptake by plant biomass.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Decomposition by ectomycorrhizal fungi alters soil carbon storage in a simulation model

DOE PAGES

Moore, J. A. M.; Jiang, J.; Post, W. M.; ...

2015-03-06

Carbon cycle models often lack explicit belowground organism activity, yet belowground organisms regulate carbon storage and release in soil. Ectomycorrhizal fungi are important players in the carbon cycle because they are a conduit into soil for carbon assimilated by the plant. It is hypothesized that ectomycorrhizal fungi can also be active decomposers when plant carbon allocation to fungi is low. Here, we reviewed the literature on ectomycorrhizal decomposition and we developed a simulation model of the plant-mycorrhizae interaction where a reduction in plant productivity stimulates ectomycorrhizal fungi to decompose soil organic matter. Our review highlights evidence demonstrating the potential formore » ectomycorrhizal fungi to decompose soil organic matter. Our model output suggests that ectomycorrhizal activity accounts for a portion of carbon decomposed in soil, but this portion varied with plant productivity and the mycorrhizal carbon uptake strategy simulated. Lower organic matter inputs to soil were largely responsible for reduced soil carbon storage. Using mathematical theory, we demonstrated that biotic interactions affect predictions of ecosystem functions. Specifically, we developed a simple function to model the mycorrhizal switch in function from plant symbiont to decomposer. In conclusion, we show that including mycorrhizal fungi with the flexibility of mutualistic and saprotrophic lifestyles alters predictions of ecosystem function.« less

Towards a model-based inventory of soil organic carbon in agricultural soils for the Swiss greenhouse gas reporting

NASA Astrophysics Data System (ADS)

Staudt, K.; Leifeld, J.; Bretscher, D.; Fuhrer, J.

2012-04-01

The Swiss inventory submission under the United Nations Framework Convention on Climate Change (UNFCCC) reports on changes in soil organic carbon stocks under different land-uses and land-use changes. The approach currently employed for cropland and grassland soils combines Tier 1 and Tier 2 methods and is considered overly simplistic. As the UNFCC encourages countries to develop Tier 3 methods for national greenhouse gas reporting, we aim to build up a model-based inventory of soil organic carbon in agricultural soils in Switzerland. We conducted a literature research on currently employed higher-tier methods using process-based models in four countries: Denmark, Sweden, Finland and the USA. The applied models stem from two major groups differing in complexity - those belonging to the group of general ecosystem models that include a plant-growth submodel, e.g. Century, and those that simulate soil organic matter turnover but not plant-growth, e.g. ICBM. For the latter group, carbon inputs to the soil from plant residues and roots have to be determined separately. We will present some aspects of the development of a model-based inventory of soil organic carbon in agricultural soils in Switzerland. Criteria for model evaluation are, among others, modeled land-use classes and land-use changes, spatial and temporal resolution, and coverage of relevant processes. For model parameterization and model evaluation at the field scale, data from several long-term agricultural experiments and monitoring sites in Switzerland is available. A subsequent regional application of a model requires the preparation of regional input data for the whole country - among others spatio-temporal meteorological data, agricultural and soil data. Following the evaluation of possible models and of available data, preference for application in the Swiss inventory will be given to simpler model structures, i.e. models without a plant-growth module. Thus, we compared different allometric relations for the estimation of plant carbon inputs to the soil from yield data that are usually provided with the models. Calculated above- and below-ground carbon inputs vary substantially between methods and exhibit different sensitivities to yield data. As a benchmark, inputs to the soil from above- and below-ground crop residues are calculated with the IPCC default method. Furthermore, the suitability of these estimation methods for Swiss conditions is tested.

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.

Soil mechanics: breaking ground.

PubMed

Einav, Itai

2007-12-15

In soil mechanics, student's models are classified as simple models that teach us unexplained elements of behaviour; an example is the Cam clay constitutive models of critical state soil mechanics (CSSM). 'Engineer's models' are models that elaborate the theory to fit more behavioural trends; this is usually done by adding fitting parameters to the student's models. Can currently unexplained behavioural trends of soil be explained without adding fitting parameters to CSSM models, by developing alternative student's models based on modern theories?Here I apply an alternative theory to CSSM, called 'breakage mechanics', and develop a simple student's model for sand. Its unique and distinctive feature is the use of an energy balance equation that connects grain size reduction to consumption of energy, which enables us to predict how grain size distribution (gsd) evolves-an unprecedented capability in constitutive modelling. With only four parameters, the model is physically clarifying what CSSM cannot for sand: the dependency of yielding and critical state on the initial gsd and void ratio.

A SOIL SPATIAL DATA FRAMEWORK FOR ENVIRONMENTAL MODELING IN THE CONTIGUOUS US

EPA Science Inventory

A suite of soil and related data-layers have been developed for environmental assessments of the effects of tropospheric ozone exposure and nitrogen deposition on forests, and global change (soil C pools and landuse impacts, water balance modeling). These spatial data depict s...

Soil-geographical regionalization as a basis for digital soil mapping: Karelia case study

NASA Astrophysics Data System (ADS)

Krasilnikov, P.; Sidorova, V.; Dubrovina, I.

2010-12-01

Recent development of digital soil mapping (DSM) allowed improving significantly the quality of soil maps. We tried to make a set of empirical models for the territory of Karelia, a republic at the North-East of the European territory of Russian Federation. This territory was selected for the pilot study for DSM for two reasons. First, the soils of the region are mainly monogenetic; thus, the effect of paleogeographic environment on recent soils is reduced. Second, the territory was poorly mapped because of low agricultural development: only 1.8% of the total area of the republic is used for agriculture and has large-scale soil maps. The rest of the territory has only small-scale soil maps, compiled basing on the general geographic concepts rather than on field surveys. Thus, the only solution for soil inventory was the predictive digital mapping. The absence of large-scaled soil maps did not allow data mining from previous soil surveys, and only empirical models could be applied. For regionalization purposes, we accepted the division into Northern and Southern Karelia, proposed in the general scheme of soil regionalization of Russia; boundaries between the regions were somewhat modified. Within each region, we specified from 15 (Northern Karelia) to 32 (Southern Karelia) individual soilscapes and proposed soil-topographic and soil-lithological relationships for every soilscape. Further field verification is needed to adjust the models.

When and where does preferential flow matter - from observation to large scale modelling

NASA Astrophysics Data System (ADS)

Weiler, Markus; Leistert, Hannes; Steinbrich, Andreas

2017-04-01

Preferential flow can be of relevance in a wide range of soils and the interaction of different processes and factors are still difficult to assess. As most studies (including our own studies) focusing on the effect of preferential flow are based on relatively high precipitation rates, there is always the question how relevant preferential flow is under natural conditions, considering the site specific precipitation characteristics, the effect of the drying and wetting cycle on the initial soil water condition and shrinkage cracks, the site specific soil properties, soil structure and rock fragments, and the effect of plant roots and soil fauna (e.g. earthworm channels). In order to assess this question, we developed the distributed, process-based model RoGeR (Runoff Generation Research) to include a large number relevant features and processes of preferential flow in soils. The model was developed from a large number of process based research and experiments and includes preferential flow in roots, earthworm channels, along rock fragments and shrinkage cracks. We parameterized the uncalibrated model at a high spatial resolution of 5x5m for the whole state of Baden-Württemberg in Germany using LiDAR data, degree of sealing, landuse, soil properties and geology. As the model is an event based model, we derived typical event based precipitation characteristics based on rainfall duration, mean intensity and amount. Using the site-specific variability of initial soil moisture derived from a water balance model based on the same dataset, we simulated the infiltration and recharge amounts of all event classes derived from the event precipitation characteristics and initial soil moisture conditions. The analysis of the simulation results allowed us to extracts the relevance of preferential flow for infiltration and recharge considering all factors above. We could clearly see a strong effect of the soil properties and land-use, but also, particular for clay rich soils a strong effect of the initial conditions due to the development of soil cracks. Not too surprisingly, the relevance of preferential flow was much lower when considering the whole range of precipitation events as only considering events with a high rainfall intensity. Also, the influence on infiltration and recharge were different. Despite the model can still be improved in particular considering more realistic information about the spatial and temporal variability of preferential flow by soil fauna and plants, the model already shows under what situation we need to be very careful when predicting infiltration and recharge with models considering only longer time steps (daily) or only matrix flow.

Large-area Soil Moisture Surveys Using a Cosmic-ray Rover: Approaches and Results from Australia

NASA Astrophysics Data System (ADS)

Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.

2017-12-01

Recent improvements in satellite instrumentation has increased the resolution and frequency of soil moisture observations, and this in turn has supported the development of higher resolution land surface process models. Calibration and validation of these products is restricted by the mismatch of scales between remotely sensed and contemporary ground based observations. Although the cosmic ray neutron soil moisture probe can provide estimates soil moisture at a scale useful for the calibration and validation purposes, it is spatially limited to a single, fixed location. This scaling issue has been addressed with the development of mobile soil moisture monitoring systems that utilizes the cosmic ray neutron method, typically referred to as a `rover'. This manuscript describes a project designed to develop approaches for undertaking rover surveys to produce soil moisture estimates at scales comparable to satellite observations and land surface process models. A custom designed, trailer-mounted rover was used to conduct repeat surveys at two scales in the Mallee region of Victoria, Australia. A broad scale survey was conducted at 36 x 36 km covering an area of a standard SMAP pixel and an intensive scale survey was conducted over a 10 x 10 km portion of the broad scale survey, which is at a scale equivalent to that used for national water balance modelling. We will describe the design of the rover, the methods used for converting neutron counts into soil moisture and discuss factors controlling soil moisture variability. We found that the intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution and the broad scale at 9 km resolution. We conclude that these products are well suited for future analysis of satellite soil moisture retrievals and finer scale soil moisture models.

A Tale of Four Stories: Soil Ecology, Theory, Evolution and the Publication System

PubMed Central

Barot, Sébastien; Blouin, Manuel; Fontaine, Sébastien; Jouquet, Pascal; Lata, Jean-Christophe; Mathieu, Jérôme

2007-01-01

Background Soil ecology has produced a huge corpus of results on relations between soil organisms, ecosystem processes controlled by these organisms and links between belowground and aboveground processes. However, some soil scientists think that soil ecology is short of modelling and evolutionary approaches and has developed too independently from general ecology. We have tested quantitatively these hypotheses through a bibliographic study (about 23000 articles) comparing soil ecology journals, generalist ecology journals, evolutionary ecology journals and theoretical ecology journals. Findings We have shown that soil ecology is not well represented in generalist ecology journals and that soil ecologists poorly use modelling and evolutionary approaches. Moreover, the articles published by a typical soil ecology journal (Soil Biology and Biochemistry) are cited by and cite low percentages of articles published in generalist ecology journals, evolutionary ecology journals and theoretical ecology journals. Conclusion This confirms our hypotheses and suggests that soil ecology would benefit from an effort towards modelling and evolutionary approaches. This effort should promote the building of a general conceptual framework for soil ecology and bridges between soil ecology and general ecology. We give some historical reasons for the parsimonious use of modelling and evolutionary approaches by soil ecologists. We finally suggest that a publication system that classifies journals according to their Impact Factors and their level of generality is probably inadequate to integrate “particularity” (empirical observations) and “generality” (general theories), which is the goal of all natural sciences. Such a system might also be particularly detrimental to the development of a science such as ecology that is intrinsically multidisciplinary. PMID:18043755

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.

Substrate and environmental controls on microbial assimilation of soil organic carbon: a framework for Earth System Models

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

Xu, Xiaofeng; Schimel, Joshua; Thornton, Peter E

2014-01-01

Microbial assimilation of soil organic carbon is one of the fundamental processes of global carbon cycling and it determines the magnitude of microbial biomass in soils. Mechanistic understanding of microbial assimilation of soil organic carbon and its controls is important for to improve Earth system models ability to simulate carbon-climate feedbacks. Although microbial assimilation of soil organic carbon is broadly considered to be an important parameter, it really comprises two separate physiological processes: one-time assimilation efficiency and time-dependent microbial maintenance energy. Representing of these two mechanisms is crucial to more accurately simulate carbon cycling in soils. In this study, amore » simple modeling framework was developed to evaluate the substrate and environmental controls on microbial assimilation of soil organic carbon using a new term: microbial annual active period (the length of microbes remaining active in one year). Substrate quality has a positive effect on microbial assimilation of soil organic carbon: higher substrate quality (lower C:N ratio) leads to higher ratio of microbial carbon to soil organic carbon and vice versa. Increases in microbial annual active period from zero stimulate microbial assimilation of soil organic carbon; however, when microbial annual active period is longer than an optimal threshold, increasing this period decreases microbial biomass. The simulated ratios of soil microbial biomass to soil organic carbon are reasonably consistent with a recently compiled global dataset at the biome-level. The modeling framework of microbial assimilation of soil organic carbon and its controls developed in this study offers an applicable ways to incorporate microbial contributions to the carbon cycling into Earth system models for simulating carbon-climate feedbacks and to explain global patterns of microbial biomass.« less

[New paradigm for soil and water conservation: a method based on watershed process modeling and scenario analysis].

PubMed

Zhu, A-Xing; Chen, La-Jiao; Qin, Cheng-Zhi; Wang, Ping; Liu, Jun-Zhi; Li, Run-Kui; Cai, Qiang-Guo

2012-07-01

With the increase of severe soil erosion problem, soil and water conservation has become an urgent concern for sustainable development. Small watershed experimental observation is the traditional paradigm for soil and water control. However, the establishment of experimental watershed usually takes long time, and has the limitations of poor repeatability and high cost. Moreover, the popularization of the results from the experimental watershed is limited for other areas due to the differences in watershed conditions. Therefore, it is not sufficient to completely rely on this old paradigm for soil and water loss control. Recently, scenario analysis based on watershed modeling has been introduced into watershed management, which can provide information about the effectiveness of different management practices based on the quantitative simulation of watershed processes. Because of its merits such as low cost, short period, and high repeatability, scenario analysis shows great potential in aiding the development of watershed management strategy. This paper elaborated a new paradigm using watershed modeling and scenario analysis for soil and water conservation, illustrated this new paradigm through two cases for practical watershed management, and explored the future development of this new soil and water conservation paradigm.

Integrated process-based hydrologic and ephemeral gully modeling for better assessment of soil erosion in small watersheds

NASA Astrophysics Data System (ADS)

Sheshukov, A. Y.; Karimov, V. R.

2017-12-01

Excessive soil erosion in agriculturally dominated watersheds causes degradation of arable land and affects agricultural productivity. Structural and soil-quality best management practices can be beneficial in reducing sheet and rill erosion, however, larger rills, ephemeral gullies, and concentrated flow channels still remain to be significant sources of sediment. A better understanding of channelized soil erosion, underlying physical processes, and ways to mitigate the problem is needed to develop innovative approaches for evaluation of soil losses from various sediment sources. The goal of this study was to develop a novel integrated process-based catchment-scale model for sheet, rill, and ephemeral gully erosion and assess soil erosion mitigation practices. Geospatially, a catchment was divided into ephemeral channels and contributing hillslopes. Surface runoff hydrograph and sheet-rill erosion rates from contributing hillslopes were calculated based on the Water Erosion Prediction Project (WEPP) model. For ephemeral channels, a dynamic ephemeral gully erosion model was developed. Each channel was divided into segments, and channel flow was routed according to the kinematic wave equation. Reshaping of the channel profile in each segment (sediment deposition, soil detachment) was simulated at each time-step according to acting shear stress distribution along the channel boundary and excess shear stress equation. The approach assumed physically-consistent channel shape reconfiguration representing channel walls failure and deposition in the bottom of the channel. Soil erodibility and critical shear stress parameters were dynamically adjusted due to seepage/drainage forces based on computed infiltration gradients. The model was validated on the data obtained from the field study by Karimov et al. (2014) yielding agreement with NSE coefficient of 0.72. The developed model allowed to compute ephemeral gully erosion while accounting for antecedent soil moisture conditions. Results showed significant differences in performance of management practices for initially dry and wet soils. Application of no-till and conversion to grassland significantly reduced the erosion rates compared to conventional tillage for small runoff events, while the efficiency was reduced for large events.

Description and spatial inference of soil drainage using matrix soil colours in the Lower Hunter Valley, New South Wales, Australia

PubMed Central

McBratney, Alex B.; Minasny, Budiman

2018-01-01

Soil colour is often used as a general purpose indicator of internal soil drainage. In this study we developed a necessarily simple model of soil drainage which combines the tacit knowledge of the soil surveyor with observed matrix soil colour descriptions. From built up knowledge of the soils in our Lower Hunter Valley, New South Wales study area, the sequence of well-draining → imperfectly draining → poorly draining soils generally follows the colour sequence of red → brown → yellow → grey → black soil matrix colours. For each soil profile, soil drainage is estimated somewhere on a continuous index of between 5 (very well drained) and 1 (very poorly drained) based on the proximity or similarity to reference soil colours of the soil drainage colour sequence. The estimation of drainage index at each profile incorporates the whole-profile descriptions of soil colour where necessary, and is weighted such that observation of soil colour at depth and/or dominantly observed horizons are given more preference than observations near the soil surface. The soil drainage index, by definition disregards surficial soil horizons and consolidated and semi-consolidated parent materials. With the view to understanding the spatial distribution of soil drainage we digitally mapped the index across our study area. Spatial inference of the drainage index was made using Cubist regression tree model combined with residual kriging. Environmental covariates for deterministic inference were principally terrain variables derived from a digital elevation model. Pearson’s correlation coefficients indicated the variables most strongly correlated with soil drainage were topographic wetness index (−0.34), mid-slope position (−0.29), multi-resolution valley bottom flatness index (−0.29) and vertical distance to channel network (VDCN) (0.26). From the regression tree modelling, two linear models of soil drainage were derived. The partitioning of models was based upon threshold criteria of VDCN. Validation of the regression kriging model using a withheld dataset resulted in a root mean square error of 0.90 soil drainage index units. Concordance between observations and predictions was 0.49. Given the scale of mapping, and inherent subjectivity of soil colour description, these results are acceptable. Furthermore, the spatial distribution of soil drainage predicted in our study area is attuned with our mental model developed over successive field surveys. Our approach, while exclusively calibrated for the conditions observed in our study area, can be generalised once the unique soil colour and soil drainage relationship is expertly defined for an area or region in question. With such rules established, the quantitative components of the method would remain unchanged. PMID:29682425

Description and spatial inference of soil drainage using matrix soil colours in the Lower Hunter Valley, New South Wales, Australia.

PubMed

Malone, Brendan P; McBratney, Alex B; Minasny, Budiman

2018-01-01

Soil colour is often used as a general purpose indicator of internal soil drainage. In this study we developed a necessarily simple model of soil drainage which combines the tacit knowledge of the soil surveyor with observed matrix soil colour descriptions. From built up knowledge of the soils in our Lower Hunter Valley, New South Wales study area, the sequence of well-draining → imperfectly draining → poorly draining soils generally follows the colour sequence of red → brown → yellow → grey → black soil matrix colours. For each soil profile, soil drainage is estimated somewhere on a continuous index of between 5 (very well drained) and 1 (very poorly drained) based on the proximity or similarity to reference soil colours of the soil drainage colour sequence. The estimation of drainage index at each profile incorporates the whole-profile descriptions of soil colour where necessary, and is weighted such that observation of soil colour at depth and/or dominantly observed horizons are given more preference than observations near the soil surface. The soil drainage index, by definition disregards surficial soil horizons and consolidated and semi-consolidated parent materials. With the view to understanding the spatial distribution of soil drainage we digitally mapped the index across our study area. Spatial inference of the drainage index was made using Cubist regression tree model combined with residual kriging. Environmental covariates for deterministic inference were principally terrain variables derived from a digital elevation model. Pearson's correlation coefficients indicated the variables most strongly correlated with soil drainage were topographic wetness index (-0.34), mid-slope position (-0.29), multi-resolution valley bottom flatness index (-0.29) and vertical distance to channel network (VDCN) (0.26). From the regression tree modelling, two linear models of soil drainage were derived. The partitioning of models was based upon threshold criteria of VDCN. Validation of the regression kriging model using a withheld dataset resulted in a root mean square error of 0.90 soil drainage index units. Concordance between observations and predictions was 0.49. Given the scale of mapping, and inherent subjectivity of soil colour description, these results are acceptable. Furthermore, the spatial distribution of soil drainage predicted in our study area is attuned with our mental model developed over successive field surveys. Our approach, while exclusively calibrated for the conditions observed in our study area, can be generalised once the unique soil colour and soil drainage relationship is expertly defined for an area or region in question. With such rules established, the quantitative components of the method would remain unchanged.

Towards a paradigm shift in the modeling of soil organic carbon decomposition for earth system models

NASA Astrophysics Data System (ADS)

He, Yujie

Soils are the largest terrestrial carbon pools and contain approximately 2200 Pg of carbon. Thus, the dynamics of soil carbon plays an important role in the global carbon cycle and climate system. Earth System Models are used to project future interactions between terrestrial ecosystem carbon dynamics and climate. However, these models often predict a wide range of soil carbon responses and their formulations have lagged behind recent soil science advances, omitting key biogeochemical mechanisms. In contrast, recent mechanistically-based biogeochemical models that explicitly account for microbial biomass pools and enzyme kinetics that catalyze soil carbon decomposition produce notably different results and provide a closer match to recent observations. However, a systematic evaluation of the advantages and disadvantages of the microbial models and how they differ from empirical, first-order formulations in soil decomposition models for soil organic carbon is still needed. This dissertation consists of a series of model sensitivity and uncertainty analyses and identifies dominant decomposition processes in determining soil organic carbon dynamics. Poorly constrained processes or parameters that require more experimental data integration are also identified. This dissertation also demonstrates the critical role of microbial life-history traits (e.g. microbial dormancy) in the modeling of microbial activity in soil organic matter decomposition models. Finally, this study surveys and synthesizes a number of recently published microbial models and provides suggestions for future microbial model developments.

PPSITE - A New Method of Site Evaluation for Longleaf Pine: Model Development and User's Guide

Treesearch

Constance A. Harrington

1990-01-01

A model was developed to predict site index (base age 50 years) for longleaf pine (Pinus palustris Mill.). The model, named PPSITE, was based on soil characteristics, site location on the landscape, and land history. The model was constrained so that the relationship between site index and each soil-site variable was consistent with what was known...

Derivation of Soil Ecological Criteria for Copper in Chinese Soils

PubMed Central

Wang, Xiaoqing; Wei, Dongpu; Ma, Yibing; McLaughlin, Mike J.

2015-01-01

Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82–0.91. The three-factor predictive models – that took into account the effect of soil organic carbon – were more accurate than two-factor models, with R2 of 0.85–0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils. PMID:26207783

Abiotic/biotic coupling in the rhizosphere: a reactive transport modeling analysis

USGS Publications Warehouse

Lawrence, Corey R.; Steefel, Carl; Maher, Kate

2014-01-01

A new generation of models is needed to adequately simulate patterns of soil biogeochemical cycling in response changing global environmental drivers. For example, predicting the influence of climate change on soil organic matter storage and stability requires models capable of addressing complex biotic/abiotic interactions of rhizosphere and weathering processes. Reactive transport modeling provides a powerful framework simulating these interactions and the resulting influence on soil physical and chemical characteristics. Incorporation of organic reactions in an existing reactive transport model framework has yielded novel insights into soil weathering and development but much more work is required to adequately capture root and microbial dynamics in the rhizosphere. This endeavor provides many advantages over traditional soil biogeochemical models but also many challenges.

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.

Assessing different agricultural managements with the use of soil quality indices in a Mediteranean calcareous soil

NASA Astrophysics Data System (ADS)

Morugán-Coronado, Alicia; García-Orenes, Fuensanta; Mataix-Solera, Jorge; Arcenegui, Vicky; Cerdà, Artemi

2013-04-01

Soil erosion is a major problem in the Mediterranean region due to the arid conditions and torrential rainfalls, which contribute to the degradation of agricultural land. New strategies must be developed to reduce soil losses and recover or maintain soil functionality in order to achieve a sustainable agriculture. An experiment was designed to evaluate the effect of different agricultural management on soil properties and soil quality. Ten different treatments (contact herbicide, systemic herbicide, ploughing, Oat mulch non-plough, Oats mulch plough, leguminous plant, straw rice mulch, chipped pruned branches, residual-herbicide and agro geo-textile, and three control plots including no tillage or control and long agricultural abandonment (shrub on marls and shrub on limestone) were established in 'El Teularet experimental station' located in the Sierra de Enguera (Valencia, Spain). The soil is a Typic Xerorthent developed over Cretaceous marls in an old agricultural terrace. The agricultural management can modify the soil equilibrium and affect its quality. In this work two soil quality indices (models) developed by Zornoza et al. (2007) are used to evaluate the effects of the different agricultural management along 4 years. The models were developed studying different soil properties in undisturbed forest soils in SE Spain, and the relationships between soil parameters were established using multiple linear regressions. Model 1, that explained 92% of the variance in soil organic carbon (SOC) showed that the SOC can be calculated by the linear combination of 6 physical, chemical and biochemical properties (acid phosphatase, water holding capacity (WHC), electrical conductivity (EC), available phosphorus (P), cation exchange capacity (CEC) and aggregate stability (AS). Model 2 explains 89% of the SOC variance, which can be calculated by means of 7 chemical and biochemical properties (urease, phosphatase, and ß-glucosidase activities, pH, EC, P and CEC). We use the residual (difference between calculated SOC by models and real SOC, analyzed in laboratory) as soil quality indices. We consider higher soil quality when the residuals are closer to cero or inside confidence intervals of the models (95%). As expected, the application of the models indicates that in all the treatments and the control plots (shrub on marls and shrub on limestone), the residuals are out of the confidence intervals for the models, showing a disequilibrium among soil properties because these treatments have been submitted to a perturbation such as the agricultural use. However, it can be observed that the residuals in the last sampling in control plots and some of the treatments, the least aggressive with the soil, are lower and therefore the soil it seems to the soil properties is achieving to their equilibrium among them. These soils are: Shrub on limestone and shrub on marls, Chipped pruned branches and Oat mulch non-plough. These results are in agreement with García-Orenes et al. (2010), who showed that the addition of oat straw to soil can be considered an effective soil management, because it produced an important increase of the different fractions of organic carbon and microbial activity, that it will be translated into a rapid improvement of soil quality. The application of the herbicides studied produced a decrease in all the soil parameters; these practices are not recommendable for a sustainable agricultural system in semiarid Mediterranean agro-ecosystem. -García-Orenes, F., Guerrero, C., Roldán, A., Mataix-Solera, J., Cerdà, A. Campoy, M., Zornoza, R., Bárcenas, G., Caravaca, F., (2010). Soil microbial biomass and activity under different agricultural management systems in a semiarid Mediterranean agroecosystem. Soil & Tillage Research 109: 110-115. -Zornoza, R., Mataix-Solera, J., Guerrero, C., Arcenegui, V., Mayoral, A.M., Morales, J. Mataix-Beneyto, J., 2007. Soil properties under natural forest in the Alicante Province of Spain. Geoderma. 142, 334-341 Aknowledgements: The authors acknowledge the 'Teularet experimental station' staff for the collaboration.

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.

Spatial and seasonal dynamics of surface soil carbon in the Luquillo Experimental Forest, Puerto Rico.

Treesearch

Hongqing Wang; Joseph D. Cornell; Charles A.S. Hall; David P. Marley

2002-01-01

We developed a spatially-explicit version of the CENTURY soil model to characterize the storage and flux of soil organic carbon (SOC, 0–30 cm depth) in the Luquillo Experimental Forest (LEF), Puerto Rico as a function of climate, vegetation, and soils. The model was driven by monthly estimates of average air temperature, precipitation, and potential evapotranspiration...

Development of a predictive model to estimate the effect of soil solarization on survival of soilborne inoculum of Phytophthora ramorum and Phytophthora pini

Treesearch

Fumiaki Funahashi; Jennifer L. Parke

2017-01-01

Soil solarization has been shown to be an effective tool to manage Phytophthora spp. within surface soils, but estimating the minimum time required to complete local eradication under variable weather conditions remains unknown. A mathematical model could help predict the effectiveness of solarization at different sites and soil depths....

Topographic soil wetness index derived from combined Alaska-British Columbia datasets for the Gulf of Alaska region

NASA Astrophysics Data System (ADS)

D'Amore, D. V.; Biles, F. E.

2016-12-01

The flow of water is often highlighted as a priority in land management planning and assessments related to climate change. Improved measurement and modeling of soil moisture is required to develop predictive estimates for plant distributions, soil moisture, and snowpack, which all play important roles in ecosystem planning in the face of climate change. Drainage indexes are commonly derived from GIS tools with digital elevation models. Soil moisture classes derived from these tools are useful digital proxies for ecosystem functions associated with the concentration of water on the landscape. We developed a spatially explicit topographically derived soil wetness index (TWI) across the perhumid coastal temperate rainforest (PCTR) of Alaska and British Columbia. Developing applicable drainage indexes in complex terrain and across broad areas required careful application of the appropriate DEM, caution with artifacts in GIS covers and mapping realistic zones of wetlands with the indicator. The large spatial extent of the model has facilitated the mapping of forest habitat and the development of water table depth mapping in the region. A key element of the TWI is the merging of elevation datasets across the US-Canada border where major rivers transect the international boundary. The unified TWI allows for seemless mapping across the international border and unified ecological applications. A python program combined with the unified DEM allows end users to quickly apply the TWI to all areas of the PCTR. This common platform can facilitate model comparison and improvements to local soil moisture conditions, generation of streamflow, and ecological site conditions. In this presentation we highlight the application of the TWI for mapping risk factors related to forest decline and the development of a regional water table depth map. Improved soil moisture maps are critical for deriving spatial models of changes in soil moisture for both plant growth and streamflow across future climate conditions.

Numerical Simulation of Rocket Exhaust Interaction with Lunar Soil

NASA Technical Reports Server (NTRS)

Liever, Peter; Tosh, Abhijit; Curtis, Jennifer

2012-01-01

This technology development originated from the need to assess the debris threat resulting from soil material erosion induced by landing spacecraft rocket plume impingement on extraterrestrial planetary surfaces. The impact of soil debris was observed to be highly detrimental during NASA s Apollo lunar missions and will pose a threat for any future landings on the Moon, Mars, and other exploration targets. The innovation developed under this program provides a simulation tool that combines modeling of the diverse disciplines of rocket plume impingement gas dynamics, granular soil material liberation, and soil debris particle kinetics into one unified simulation system. The Unified Flow Solver (UFS) developed by CFDRC enabled the efficient, seamless simulation of mixed continuum and rarefied rocket plume flow utilizing a novel direct numerical simulation technique of the Boltzmann gas dynamics equation. The characteristics of the soil granular material response and modeling of the erosion and liberation processes were enabled through novel first principle-based granular mechanics models developed by the University of Florida specifically for the highly irregularly shaped and cohesive lunar regolith material. These tools were integrated into a unique simulation system that accounts for all relevant physics aspects: (1) Modeling of spacecraft rocket plume impingement flow under lunar vacuum environment resulting in a mixed continuum and rarefied flow; (2) Modeling of lunar soil characteristics to capture soil-specific effects of particle size and shape composition, soil layer cohesion and granular flow physics; and (3) Accurate tracking of soil-borne debris particles beginning with aerodynamically driven motion inside the plume to purely ballistic motion in lunar far field conditions. In the earlier project phase of this innovation, the capabilities of the UFS for mixed continuum and rarefied flow situations were validated and demonstrated for lunar lander rocket plume flow impingement under lunar vacuum conditions. Applications and improvements to the granular flow simulation tools contributed by the University of Florida were tested against Earth environment experimental results. Requirements for developing, validating, and demonstrating this solution environment were clearly identified, and an effective second phase execution plan was devised. In this phase, the physics models were refined and fully integrated into a production-oriented simulation tool set. Three-dimensional simulations of Apollo Lunar Excursion Module (LEM) and Altair landers (including full-scale lander geometry) established the practical applicability of the UFS simulation approach and its advanced performance level for large-scale realistic problems.

Multiple soil nutrient competition between plants, microbes, and mineral surfaces: model development, parameterization, and example applications in several tropical forests

NASA Astrophysics Data System (ADS)

Zhu, Q.; Riley, W. J.; Tang, J.; Koven, C. D.

2015-03-01

Soil is a complex system where biotic (e.g., plant roots, micro-organisms) and abiotic (e.g., mineral surfaces) consumers compete for resources necessary for life (e.g., nitrogen, phosphorus). This competition is ecologically significant, since it regulates the dynamics of soil nutrients and controls aboveground plant productivity. Here we develop, calibrate, and test a nutrient competition model that accounts for multiple soil nutrients interacting with multiple biotic and abiotic consumers. As applied here for tropical forests, the Nutrient COMpetition model (N-COM) includes three primary soil nutrients (NH4+, NO3-, and POx (representing the sum of PO43-, HPO42-, and H2PO4-)) and five potential competitors (plant roots, decomposing microbes, nitrifiers, denitrifiers, and mineral surfaces). The competition is formulated with a quasi-steady-state chemical equilibrium approximation to account for substrate (multiple substrates share one consumer) and consumer (multiple consumers compete for one substrate) effects. N-COM successfully reproduced observed soil heterotrophic respiration, N2O emissions, free phosphorus, sorbed phosphorus, and free NH4+ at a tropical forest site (Tapajos). The overall model posterior uncertainty was moderately well constrained. Our sensitivity analysis revealed that soil nutrient competition was primarily regulated by consumer-substrate affinity rather than environmental factors such as soil temperature or soil moisture. Our results imply that the competitiveness (from most to least competitive) followed this order: (1) for NH4+, nitrifiers ~ decomposing microbes > plant roots, (2) for NO3-, denitrifiers ~ decomposing microbes > plant roots, (3) for POx, mineral surfaces > decomposing microbes ~ plant roots. Although smaller, plant relative competitiveness is of the same order of magnitude as microbes. We then applied the N-COM model to analyze field nitrogen and phosphorus perturbation experiments in two tropical forest sites (in Hawaii and Puerto Rico) not used in model development or calibration. Under soil inorganic nitrogen and phosphorus elevated conditions, the model accurately replicated the experimentally observed competition among different nutrient consumers. Although we used as many observations as we could obtain, more nutrient addition experiments in tropical systems would greatly benefit model testing and calibration. In summary, the N-COM model provides an ecologically consistent representation of nutrient competition appropriate for land BGC models integrated in Earth System Models.

Smsynth: AN Imagery Synthesis System for Soil Moisture Retrieval

NASA Astrophysics Data System (ADS)

Cao, Y.; Xu, L.; Peng, J.

2018-04-01

Soil moisture (SM) is a important variable in various research areas, such as weather and climate forecasting, agriculture, drought and flood monitoring and prediction, and human health. An ongoing challenge in estimating SM via synthetic aperture radar (SAR) is the development of the retrieval SM methods, especially the empirical models needs as training samples a lot of measurements of SM and soil roughness parameters which are very difficult to acquire. As such, it is difficult to develop empirical models using realistic SAR imagery and it is necessary to develop methods to synthesis SAR imagery. To tackle this issue, a SAR imagery synthesis system based on the SM named SMSynth is presented, which can simulate radar signals that are realistic as far as possible to the real SAR imagery. In SMSynth, SAR backscatter coefficients for each soil type are simulated via the Oh model under the Bayesian framework, where the spatial correlation is modeled by the Markov random field (MRF) model. The backscattering coefficients simulated based on the designed soil parameters and sensor parameters are added into the Bayesian framework through the data likelihood where the soil parameters and sensor parameters are set as realistic as possible to the circumstances on the ground and in the validity range of the Oh model. In this way, a complete and coherent Bayesian probabilistic framework is established. Experimental results show that SMSynth is capable of generating realistic SAR images that suit the needs of a large amount of training samples of empirical models.

Pedotransfer functions in Earth system science: challenges and perspectives

NASA Astrophysics Data System (ADS)

Van Looy, K.; Minasny, B.; Nemes, A.; Verhoef, A.; Weihermueller, L.; Vereecken, H.

2017-12-01

We make a stronghold for a new generation of Pedotransfer functions (PTFs) that is currently developed in the different disciplines of Earth system science, offering strong perspectives for improvement of integrated process-based models, from local to global scale applications. PTFs are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. To meet the methodological challenges for a successful application in Earth system modeling, we highlight how PTF development needs to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly capture the spatial heterogeneity of soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration and organic carbon content, root density and vegetation water uptake. We present an outlook and stepwise approach to the development of a comprehensive set of PTFs that can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques and soil information availability provide a true breakthrough for this, yet further improvements are necessary in three domains: 1) the determining of unknown relationships and dealing with uncertainty in Earth system modeling; 2) the step of spatially deploying this knowledge with PTF validation at regional to global scales; and 3) the integration and linking of the complex model parameterizations (coupled parameterization). Integration is an achievable goal we will show.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Space environment and lunar surface processes

NASA Technical Reports Server (NTRS)

Comstock, G. M.

1979-01-01

The development of a general rock/soil model capable of simulating in a self consistent manner the mechanical and exposure history of an assemblage of solid and loose material from submicron to planetary size scales, applicable to lunar and other space exposed planetary surfaces is discussed. The model was incorporated into a computer code called MESS.2 (model for the evolution of space exposed surfaces). MESS.2, which represents a considerable increase in sophistication and scope over previous soil and rock surface models, is described. The capabilities of previous models for near surface soil and rock surfaces are compared with the rock/soil model, MESS.2.

Predicting the particle size distribution of eroded sediment using artificial neural networks.

PubMed

Lagos-Avid, María Paz; Bonilla, Carlos A

2017-03-01

Water erosion causes soil degradation and nonpoint pollution. Pollutants are primarily transported on the surfaces of fine soil and sediment particles. Several soil loss models and empirical equations have been developed for the size distribution estimation of the sediment leaving the field, including the physically-based models and empirical equations. Usually, physically-based models require a large amount of data, sometimes exceeding the amount of available data in the modeled area. Conversely, empirical equations do not always predict the sediment composition associated with individual events and may require data that are not always available. Therefore, the objective of this study was to develop a model to predict the particle size distribution (PSD) of eroded soil. A total of 41 erosion events from 21 soils were used. These data were compiled from previous studies. Correlation and multiple regression analyses were used to identify the main variables controlling sediment PSD. These variables were the particle size distribution in the soil matrix, the antecedent soil moisture condition, soil erodibility, and hillslope geometry. With these variables, an artificial neural network was calibrated using data from 29 events (r 2 =0.98, 0.97, and 0.86; for sand, silt, and clay in the sediment, respectively) and then validated and tested on 12 events (r 2 =0.74, 0.85, and 0.75; for sand, silt, and clay in the sediment, respectively). The artificial neural network was compared with three empirical models. The network presented better performance in predicting sediment PSD and differentiating rain-runoff events in the same soil. In addition to the quality of the particle distribution estimates, this model requires a small number of easily obtained variables, providing a convenient routine for predicting PSD in eroded sediment in other pollutant transport models. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling multidomain hydraulic properties of shrink-swell soils

NASA Astrophysics Data System (ADS)

Stewart, Ryan D.; Abou Najm, Majdi R.; Rupp, David E.; Selker, John S.

2016-10-01

Shrink-swell soils crack and become compacted as they dry, changing properties such as bulk density and hydraulic conductivity. Multidomain models divide soil into independent realms that allow soil cracks to be incorporated into classical flow and transport models. Incongruously, most applications of multidomain models assume that the porosity distributions, bulk density, and effective saturated hydraulic conductivity of the soil are constant. This study builds on a recently derived soil shrinkage model to develop a new multidomain, dual-permeability model that can accurately predict variations in soil hydraulic properties due to dynamic changes in crack size and connectivity. The model only requires estimates of soil gravimetric water content and a minimal set of parameters, all of which can be determined using laboratory and/or field measurements. We apply the model to eight clayey soils, and demonstrate its ability to quantify variations in volumetric water content (as can be determined during measurement of a soil water characteristic curve) and transient saturated hydraulic conductivity, Ks (as can be measured using infiltration tests). The proposed model is able to capture observed variations in Ks of one to more than two orders of magnitude. In contrast, other dual-permeability models assume that Ks is constant, resulting in the potential for large error when predicting water movement through shrink-swell soils. Overall, the multidomain model presented here successfully quantifies fluctuations in the hydraulic properties of shrink-swell soil matrices, and are suitable for use in physical flow and transport models based on Darcy's Law, the Richards Equation, and the advection-dispersion equation.

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.

Simulating the fate of water in field soil crop environment

NASA Astrophysics Data System (ADS)

Cameira, M. R.; Fernando, R. M.; Ahuja, L.; Pereira, L.

2005-12-01

This paper presents an evaluation of the Root Zone Water Quality Model(RZWQM) for assessing the fate of water in the soil-crop environment at the field scale under the particular conditions of a Mediterranean region. The RZWQM model is a one-dimensional dual porosity model that allows flow in macropores. It integrates the physical, biological and chemical processes occurring in the root zone, allowing the simulation of a wide spectrum of agricultural management practices. This study involved the evaluation of the soil, hydrologic and crop development sub-models within the RZWQM for two distinct agricultural systems, one consisting of a grain corn planted in a silty loam soil, irrigated by level basins and the other a forage corn planted in a sandy soil, irrigated by sprinklers. Evaluation was performed at two distinct levels. At the first level the model capability to fit the measured data was analyzed (calibration). At the second level the model's capability to extrapolate and predict the system behavior for conditions different than those used when fitting the model was assessed (validation). In a subsequent paper the same type of evaluation is presented for the nitrogen transformation and transport model. At the first level a change in the crop evapotranspiration (ETc) formulation was introduced, based upon the definition of the effective leaf area, resulting in a 51% decrease in the root mean square error of the ETc simulations. As a result the simulation of the root water uptake was greatly improved. A new bottom boundary condition was implemented to account for the presence of a shallow water table. This improved the simulation of the water table depths and consequently the soil water evolution within the root zone. The soil hydraulic parameters and the crop variety specific parameters were calibrated in order to minimize the simulation errors of soil water and crop development. At the second level crop yield was predicted with an error of 1.1 and 2.8% for grain and forage corn, respectively. Soil water was predicted with an efficiency ranging from 50 to 95% for the silty loam soil and between 56 and 72% for the sandy soil. The purposed calibration procedure allowed the model to predict crop development, yield and the water balance terms, with accuracy that is acceptable in practical applications for complex and spatially variable field conditions. An iterative method was required to account for the strong interaction between the different model components, based upon detailed experimental data on soils and crops.

Inclusion of Solar Elevation Angle in Land Surface Albedo Parameterization Over Bare Soil Surface.

PubMed

Zheng, Zhiyuan; Wei, Zhigang; Wen, Zhiping; Dong, Wenjie; Li, Zhenchao; Wen, Xiaohang; Zhu, Xian; Ji, Dong; Chen, Chen; Yan, Dongdong

2017-12-01

Land surface albedo is a significant parameter for maintaining a balance in surface energy. It is also an important parameter of bare soil surface albedo for developing land surface process models that accurately reflect diurnal variation characteristics and the mechanism behind the solar spectral radiation albedo on bare soil surfaces and for understanding the relationships between climate factors and spectral radiation albedo. Using a data set of field observations, we conducted experiments to analyze the variation characteristics of land surface solar spectral radiation and the corresponding albedo over a typical Gobi bare soil underlying surface and to investigate the relationships between the land surface solar spectral radiation albedo, solar elevation angle, and soil moisture. Based on both solar elevation angle and soil moisture measurements simultaneously, we propose a new two-factor parameterization scheme for spectral radiation albedo over bare soil underlying surfaces. The results of numerical simulation experiments show that the new parameterization scheme can more accurately depict the diurnal variation characteristics of bare soil surface albedo than the previous schemes. Solar elevation angle is one of the most important factors for parameterizing bare soil surface albedo and must be considered in the parameterization scheme, especially in arid and semiarid areas with low soil moisture content. This study reveals the characteristics and mechanism of the diurnal variation of bare soil surface solar spectral radiation albedo and is helpful in developing land surface process models, weather models, and climate models.

Soils as relative-age dating tools

USGS Publications Warehouse

Markewich, Helaine Walsh; Pavich, Milan J.; Wysocki, Douglas A.

2017-01-01

Soils develop at the earth's surface via multiple processes that act through time. Precluding burial or disturbance, soil genetic horizons form progressively and reflect the balance among formation processes, surface age, and original substrate composition. Soil morphology provides a key link between process and time (soil age), enabling soils to serve as both relative and numerical dating tools for geomorphic studies and landscape evolution. Five major factors define the contemporary state of all soils: climate, organisms, topography, parent material, and time. Soils developed on similar landforms and parent materials within a given landscape comprise what we term a soil/landform/substrate complex. Soils on such complexes that differ in development as a function of time represent a soil chronosequence. In a soil chronosequence, time constitutes the only independent formation factor; the other factors act through time. Time dictates the variations in soil development or properties (field or laboratory measured) on a soil/landform/substrate complex. Using a dataset within the chronosequence model, we can also formulate various soil development indices based upon one or a combination of soil properties, either for individual soil horizons or for an entire profile. When we evaluate soil data or soil indices mathematically, the resulting equation creates a chronofunction. Chronofunctions help quantify processes and mechanisms involved in soil development, and relate them mathematically to time. These rigorous kinds of comparisons among and within soil/landform complexes constitute an important tool for relative-age dating. After determining one or more absolute ages for a soil/landform complex, we can calculate quantitative soil formation, and or landform-development rates. Multiple dates for several complexes allow rate calculations for soil/landform-chronosequence development and soil-chronofunction calibration.

EPR-based material modelling of soils

NASA Astrophysics Data System (ADS)

Faramarzi, Asaad; Alani, Amir M.

2013-04-01

In the past few decades, as a result of the rapid developments in computational software and hardware, alternative computer aided pattern recognition approaches have been introduced to modelling many engineering problems, including constitutive modelling of materials. The main idea behind pattern recognition systems is that they learn adaptively from experience and extract various discriminants, each appropriate for its purpose. In this work an approach is presented for developing material models for soils based on evolutionary polynomial regression (EPR). EPR is a recently developed hybrid data mining technique that searches for structured mathematical equations (representing the behaviour of a system) using genetic algorithm and the least squares method. Stress-strain data from triaxial tests are used to train and develop EPR-based material models for soil. The developed models are compared with some of the well-known conventional material models and it is shown that EPR-based models can provide a better prediction for the behaviour of soils. The main benefits of using EPR-based material models are that it provides a unified approach to constitutive modelling of all materials (i.e., all aspects of material behaviour can be implemented within a unified environment of an EPR model); it does not require any arbitrary choice of constitutive (mathematical) models. In EPR-based material models there are no material parameters to be identified. As the model is trained directly from experimental data therefore, EPR-based material models are the shortest route from experimental research (data) to numerical modelling. Another advantage of EPR-based constitutive model is that as more experimental data become available, the quality of the EPR prediction can be improved by learning from the additional data, and therefore, the EPR model can become more effective and robust. The developed EPR-based material models can be incorporated in finite element (FE) analysis.

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

NASA Astrophysics Data System (ADS)

Moradizadeh, Mina; Saradjian, Mohammad R.

2018-03-01

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

Modeling forest development after fire disturbance: Climate, soil organic layer, and nitrogen jointly affect forest canopy species and long-term ecosystem carbon accumulation in the North American boreal forest

NASA Astrophysics Data System (ADS)

Trugman, A. T.; Fenton, N.; Bergeron, Y.; Xu, X.; Welp, L.; Medvigy, D.

2015-12-01

Soil organic layer dynamics strongly affect boreal forest development after fire. Field studies show that soil organic layer thickness exerts a species-specific control on propagule establishment in the North American boreal forest. On organic soils thicker than a few centimeters, all propagules are less able to recruit, but broadleaf trees recruit less effectively than needleleaf trees. In turn, forest growth controls organic layer accumulation through modulating litter input and litter quality. These dynamics have not been fully incorporated into models, but may be essential for accurate projections of ecosystem carbon storage. Here, we develop a data-constrained model for understanding boreal forest development after fire. We update the ED2 model to include new aspen and black spruce species-types, species-specific propagule survivorship dependent on soil organic layer depth, species-specific litter decay rates, dynamically accumulating moss and soil organic layers, and nitrogen fixation by cyanobacteria associated with moss. The model is validated against diverse observations ranging from monthly to centennial timescales and spanning a climate gradient in Alaska, central Canada, and Quebec. We then quantify differences in forest development that result from changes in organic layer accumulation, temperature, and nitrogen. We find that (1) the model accurately reproduces a range of observations throughout the North American boreal forest; (2) the presence of a thick organic layer results in decreased decomposition and decreased aboveground productivity, effects that can increase or decrease ecosystem carbon uptake depending on location-specific attributes; (3) with a mean warming of 4°C, some forests switch from undergoing succession to needleleaf forests to recruiting multiple cohorts of broadleaf trees, decreasing ecosystem accumulation by ~30% after 300 years; (4) the availability of nitrogen regulates successional dynamics such than broadleaf species are less able to compete with needleleaf trees under low nitrogen regimes. We conclude that a joint regulation between the soil organic layer, temperature, and nitrogen will likely play an important role in influencing boreal forests development after fire in future climates, and should be represented in models.

Rapid prediction of particulate, humus and resistant fractions of soil organic carbon in reforested lands using infrared spectroscopy.

PubMed

Madhavan, Dinesh B; Baldock, Jeff A; Read, Zoe J; Murphy, Simon C; Cunningham, Shaun C; Perring, Michael P; Herrmann, Tim; Lewis, Tom; Cavagnaro, Timothy R; England, Jacqueline R; Paul, Keryn I; Weston, Christopher J; Baker, Thomas G

2017-05-15

Reforestation of agricultural lands with mixed-species environmental plantings can effectively sequester C. While accurate and efficient methods for predicting soil organic C content and composition have recently been developed for soils under agricultural land uses, such methods under forested land uses are currently lacking. This study aimed to develop a method using infrared spectroscopy for accurately predicting total organic C (TOC) and its fractions (particulate, POC; humus, HOC; and resistant, ROC organic C) in soils under environmental plantings. Soils were collected from 117 paired agricultural-reforestation sites across Australia. TOC fractions were determined in a subset of 38 reforested soils using physical fractionation by automated wet-sieving and 13 C nuclear magnetic resonance (NMR) spectroscopy. Mid- and near-infrared spectra (MNIRS, 6000-450 cm -1 ) were acquired from finely-ground soils from environmental plantings and agricultural land. Satisfactory prediction models based on MNIRS and partial least squares regression (PLSR) were developed for TOC and its fractions. Leave-one-out cross-validations of MNIRS-PLSR models indicated accurate predictions (R 2  > 0.90, negligible bias, ratio of performance to deviation > 3) and fraction-specific functional group contributions to beta coefficients in the models. TOC and its fractions were predicted using the cross-validated models and soil spectra for 3109 reforested and agricultural soils. The reliability of predictions determined using k-nearest neighbour score distance indicated that >80% of predictions were within the satisfactory inlier limit. The study demonstrated the utility of infrared spectroscopy (MNIRS-PLSR) to rapidly and economically determine TOC and its fractions and thereby accurately describe the effects of land use change such as reforestation on agricultural soils. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparing root architectural models

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Javaux, Mathieu; Vanderborght, Jan

2017-04-01

Plant roots play an important role in several soil processes (Gregory 2006). Root architecture development determines the sites in soil where roots provide input of carbon and energy and take up water and solutes. However, root architecture is difficult to determine experimentally when grown in opaque soil. Thus, root architectural models have been widely used and been further developed into functional-structural models that are able to simulate the fate of water and solutes in the soil-root system (Dunbabin et al. 2013). Still, a systematic comparison of the different root architectural models is missing. In this work, we focus on discrete root architecture models where roots are described by connected line segments. These models differ (a) in their model concepts, such as the description of distance between branches based on a prescribed distance (inter-nodal distance) or based on a prescribed time interval. Furthermore, these models differ (b) in the implementation of the same concept, such as the time step size, the spatial discretization along the root axes or the way stochasticity of parameters such as root growth direction, growth rate, branch spacing, branching angles are treated. Based on the example of two such different root models, the root growth module of R-SWMS and RootBox, we show the impact of these differences on simulated root architecture and aggregated information computed from this detailed simulation results, taking into account the stochastic nature of those models. References Dunbabin, V.M., Postma, J.A., Schnepf, A., Pagès, L., Javaux, M., Wu, L., Leitner, D., Chen, Y.L., Rengel, Z., Diggle, A.J. Modelling root-soil interactions using three-dimensional models of root growth, architecture and function (2013) Plant and Soil, 372 (1-2), pp. 93 - 124. Gregory (2006) Roots, rhizosphere and soil: the route to a better understanding of soil science? European Journal of Soil Science 57: 2-12.

RUSLE2015, GIS-RWEQ and CENTURY: new modelling integration for soil loss and carbon fluxes at European scale

NASA Astrophysics Data System (ADS)

Panagos, Panos; Borrelli, Pasquale; Lugato, Emanuele

2016-04-01

Land degradation through erosion has been identified as major threat to European soils and agriculture. During the last years, the Directorates General for Agriculture and for Environment (plus EUROSTAT) require formal assessments and indicators on the state of soil erosion for the European Union. Moreover, the European Soil Data Centre (ESDAC) is the main data repository for soil threats at European scale. To meet these needs we have worked with recognized research institutes and scientists to develop a series of pan-EU modelling tools that estimate soil erosion by water and wind. Over the past three years, the European Commission Joint Research Centre has worked to develop a modified RUSLE modelling approach, named RUSLE2015 and the necessary input factors. These have all been peer reviewed and published as individual papers in different refereed journals. The published soil erodibility map for Europe has been modelled with the latest state of the art soil data (LUCAS) and a robust geo-statistical model (Science of Total Environment, 479-480: 189-200). Rainfall erosivity has been modelled after an extensive data collection of high temporal resolution rainfall data and the compilation of Rainfall Erosivity Database at European Scale (REDES) (Science of Total Environment, 511: 801-814). Cover-Management factor has been modelled taking into account crop composition, management practices (reduced tillage, plant residues, cover crops) and remote sensing data on vegetation density (Land Use policy, 48C: 38-50). Topography has been modelled with the recently published Digital Elevation Model at 25m resolution (Geosciences, 5: 117-126). Conservation and support practices have included the Good Agricultural Environmental Condition (GAEC database) and the 270,000 earth observations of LUCAS survey (Environmental Science & Policy 51: 23-34). The new assessment of soil erosion by water in Europe has been recently published (Environmental Science & Policy. 54: 438-447) and subsequently the core message focusing on soil erosion in agricultural lands was published in a recent correspondence in Nature (Nature, 526, 195). Additionally, the soil erosion potential for the European Union's forests was modelled using the high-resolution Global Forest Cover Loss map (2000-2012) and taking into consideration the lodging, forest cuts and forest fires (Ecological Indicators, 60:1208-1220). The first qualitative assessment of wind erosion at European scale has been done using the Index of Land Susceptibility to Wind Erosion (ILSWE) (Sustainability, 7(7): 8823-8836). The wind-erodible fraction of soil (EF) is one of the key parameters for estimating the susceptibility of soil to wind erosion (Geoderma, 232-234: 471-478). ILSWE was created by combining spatiotemporal variations of the most influential wind erosion factors such as climatic erosivity, soil erodibility, vegetation cover and landscape roughness) (Land Degradation & Development, 10.1002/ldr.2318). The quantitative assessment of wind erosion has been concluded recently using Revised Wind Erosion Equation (GIS-RWEQ). Modelling the lateral carbon fluxes due to soil erosion both at national scale (Land Use Policy, 50: 408-421) and at European scale (Global Change Biology, 10.1111/gcb.13198) is an important milestone in climate change perspective. We coupled soil erosion into a biogeochemistry model, running at 1 km2 resolution across the agricultural soils of the European Union (EU). In the future, the soil erosion (by water and wind) modelling activities will incorporate temporal variability, sediment transport and economic assessments of land degradation.

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

Moore, J. A. M.; Jiang, J.; Post, W. M.

Carbon cycle models often lack explicit belowground organism activity, yet belowground organisms regulate carbon storage and release in soil. Ectomycorrhizal fungi are important players in the carbon cycle because they are a conduit into soil for carbon assimilated by the plant. It is hypothesized that ectomycorrhizal fungi can also be active decomposers when plant carbon allocation to fungi is low. Here, we reviewed the literature on ectomycorrhizal decomposition and we developed a simulation model of the plant-mycorrhizae interaction where a reduction in plant productivity stimulates ectomycorrhizal fungi to decompose soil organic matter. Our review highlights evidence demonstrating the potential formore » ectomycorrhizal fungi to decompose soil organic matter. Our model output suggests that ectomycorrhizal activity accounts for a portion of carbon decomposed in soil, but this portion varied with plant productivity and the mycorrhizal carbon uptake strategy simulated. Lower organic matter inputs to soil were largely responsible for reduced soil carbon storage. Using mathematical theory, we demonstrated that biotic interactions affect predictions of ecosystem functions. Specifically, we developed a simple function to model the mycorrhizal switch in function from plant symbiont to decomposer. In conclusion, we show that including mycorrhizal fungi with the flexibility of mutualistic and saprotrophic lifestyles alters predictions of ecosystem function.« less

Event-based soil loss models for construction sites

NASA Astrophysics Data System (ADS)

Trenouth, William R.; Gharabaghi, Bahram

2015-05-01

The elevated rates of soil erosion stemming from land clearing and grading activities during urban development, can result in excessive amounts of eroded sediments entering waterways and causing harm to the biota living therein. However, construction site event-based soil loss simulations - required for reliable design of erosion and sediment controls - are one of the most uncertain types of hydrologic models. This study presents models with improved degree of accuracy to advance the design of erosion and sediment controls for construction sites. The new models are developed using multiple linear regression (MLR) on event-based permutations of the Universal Soil Loss Equation (USLE) and artificial neural networks (ANN). These models were developed using surface runoff monitoring datasets obtained from three sites - Greensborough, Cookstown, and Alcona - in Ontario and datasets mined from the literature for three additional sites - Treynor, Iowa, Coshocton, Ohio and Cordoba, Spain. The predictive MLR and ANN models can serve as both diagnostic and design tools for the effective sizing of erosion and sediment controls on active construction sites, and can be used for dynamic scenario forecasting when considering rapidly changing land use conditions during various phases of construction.

Environmental analyse of soil organic carbon stock changes in Slovakia

NASA Astrophysics Data System (ADS)

Koco, Š.; Barančíková, G.; Skalský, R.; Tarasovičová, Z.; Gutteková, M.; Halas, J.; Makovníková, J.; Novákova, M.

2012-04-01

The content and quality of soil organic matter is one of the basic soil parameters on which soil production functioning depends as well as it is active in non production soil functions like an ecological one especially. Morphologic segmentation of Slovakia has significant influence of structure in using agricultural soil in specific areas of our territory. Also social changes of early 90´s of 20´th century made their impact on change of using of agricultural soil (transformation from large farms to smaller ones, decreasing the number of livestock). This research is studying changes of development of soil organic carbon stock (SOC) in agricultural soil of Slovakia as results of climatic as well as social and political changes which influenced agricultury since last 40 years. The main goal of this research is an analysis of soil organic carbon stock since 1970 until now at specific agroclimatic regions of Slovakia and statistic analysis of relation between modelled data of SOC stock and soil quality index value. Changes of SOC stock were evaluated on the basis SOC content modeling using RothC-26.3 model. From modeling of SOC stock results the outcome is that in that time the soil organic carbon stock was growing until middle 90´s years of 20´th century with the highest value in 1994. Since that year until new millennium SOC stock is slightly decreasing. After 2000 has slightly increased SOC stock so far. According to soil management SOC stock development on arable land is similar to overall evolution. In case of grasslands after slight growth of SOC stock since 1990 the stock is in decline. This development is result of transformational changes after 1989 which were specific at decreasing amount of organic carbon input from organic manure at grassland areas especially. At warmer agroclimatic regions where mollic fluvisols and chernozems are present and where are soils with good quality and steady soil organic matter (SOM) the amount of SOC in monitored time is still growing. At colder agroclimatic regions, at flysch region especially where cambisols are present with low of SOM stability since 1994 stability or decreasing of SOC stock is resulting. This is result of climatic impact (lower temperatures, higher humidity) as well as the way of soil management because at colder region the number of glasslands is increased in comparison to arable land. Close relationship between SOC stock and soil production potential index representing the official basis for soil quality evaluation in Slovakia was also determined and a polynomial model was found which describes the relation at the 95% confidence level. From the obtained results it can be concluded, that the amount of crop residues and farmyard manure coming to the soil both in the first and second simulation period (1970 - 1995 and 1996 - 2007) was responsible for general trends in SOC stock dynamics. Achieved results also show different amount and changes of SOC stock in different agroclimatic regions. It was also found that that value of soil production potential index generally used for soil quality assessment in Slovakia corresponds well with simulated values of SOC stocks in top-soils of cropland soils. Key words Soil organic carbon stock, modelling, agricultural soils, agroclimatic regions, Slovakia Acknowledgements This work was supported by the Slovak Research and Development Agency under the contract No. APVV-0333-06.

DISTRIBUTION OF PARAMETERS DETERMINING BIOAVAILABILITY OF METALS IN EUROPEAN SOILS

EPA Science Inventory

As part of a program to develop a predictive model of bioavailability and toxicity of copper in soils to terrestrial organisms, 19 soils from 9 countries of the EU were collected and analyzed for use in bioavailability tests. However, it is desired that the model be of use on a ...

Drawing a representative sample from the NCSS soil database: Building blocks for the national wind erosion network

USDA-ARS?s Scientific Manuscript database

Developing national wind erosion models for the continental United States requires a comprehensive spatial representation of continuous soil particle size distributions (PSD) for model input. While the current coverage of soil survey is nearly complete, the most detailed particle size classes have c...

Development a fluvial detachment rate model to predict the erodibility of cohesive soils under the influence of seepage

USDA-ARS?s Scientific Manuscript database

Seepage influences the erodibility of streambanks, streambeds, dams, and embankments. Usually the erosion rate of cohesive soils due to fluvial forces is computed using an excess shear stress model, dependent on two major soil parameters: the critical shear stress (tc) and the erodibility coefficie...

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

NASA Astrophysics Data System (ADS)

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, Anthony D.; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-12-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

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

He, Yujie; Yang, Jinyan; Zhuang, Qianlai

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbialmore » dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO 2 efflux (R H) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 PgCyr -1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.« less

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

USGS Publications Warehouse

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, A. David; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-01-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr−1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

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.

A multiisotope C and N modeling analysis of soil organic matter turnover and transport as a function of soil depth in a California annual grassland soil chronosequence

USGS Publications Warehouse

Baisden, W.T.; Amundson, Ronald; Brenner, D.L.; Cook, A.C.; Kendall, C.; Harden, J.W.

2002-01-01

We examine soil organic matter (SOM) turnover and transport using C and N isotopes in soil profiles sampled circa 1949, 1978, and 1998 (a period spanning pulse thermonuclear 14C enrichment of the atmosphere) along a 3-million-year annual grassland soil chronosequence. Temporal differences in soil ??14C profiles indicate that inputs of recently living organic matter (OM) occur primarily in the upper 20-30 cm but suggest that OM inputs can occur below the primary rooting zone. A three-pool SOM model with downward transport captures most observed variation in ??14C, percentages of C and N, ??13C, and ??15N, supporting the commonly accepted concept of three distinct SOM pools. The model suggests that the importance of the decadal SOM pool in N dynamics is greatest in young and old soils. Altered hydrology and possibly low pH and/or P dynamics in highly developed old soils cause changes in soil C and N turnover and transport of importance for soil biogeochemistry models.

What is the philosophy of modelling soil moisture movement?

NASA Astrophysics Data System (ADS)

Chen, J.; Wu, Y.

2009-12-01

In laboratory, the soil moisture movement in the different soil textures has been analysed. From field investigation, at a spot, the soil moisture movement in the root zone, vadose zone and shallow aquifer has been explored. In addition, on ground slopes, the interflow in the near surface soil layers has been studied. Along the regions near river reaches, the expansion and shrink of the saturated area due to rainfall occurrences have been observed. From those previous explorations regarding soil moisture movement, numerical models to represent this hydrologic process have been developed. However, generally, due to high heterogeneity and stratification of soil in a basin, modelling soil moisture movement is rather challenging. Normally, some empirical equations or artificial manipulation are employed to adjust the soil moisture movement in various numerical models. In this study, we inspect the soil moisture movement equations used in a watershed model, SWAT (Soil and Water Assessment Tool) (Neitsch et al., 2005), to examine the limitations of our knowledge in such a hydrologic process. Then, we adopt the features of a topographic-information based on a hydrologic model, TOPMODEL (Beven and Kirkby, 1979), to enhance the representation of soil moisture movement in SWAT. Basically, the results of the study reveal, to some extent, the philosophy of modelling soil moisture movement in numerical models, which will be presented in the conference. Beven, K.J. and Kirkby, M.J., 1979. A physically based variable contributing area model of basin hydrology. Hydrol. Science Bulletin, 24: 43-69. Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R. and King, K.W., 2005. Soil and Water Assessment Tool Theoretical Documentation, Grassland, soil and research service, Temple, TX.

A Moisture Function of Soil Heterotrophic Respiration Derived from Pore-scale Mechanisms

NASA Astrophysics Data System (ADS)

Yan, Z.; Todd-Brown, K. E.; Bond-Lamberty, B. P.; Bailey, V.; Liu, C.

2017-12-01

Soil heterotrophic respiration (HR) is an important process controlling carbon (C) flux, but its response to changes in soil water content (θ) is poorly understood. Earth system models (ESMs) use empirical moisture functions developed from specific sites to describe the HR-θ relationship in soils, introducing significant uncertainty. Generalized models derived from mechanisms that control substrate availability and microbial respiration are thus urgently needed. Here we derive, present, and test a novel moisture function fp developed from pore-scale mechanisms. This fp encapsulates primary physicochemical and biological processes controlling HR response to moisture variation in soils. We tested fp against a wide range of published data for different soil types, and found that fp reliably predicted diverse HR- relationships. The mathematical relationship between the parameters in fp and macroscopic soil properties such as porosity and organic C content was also established, enabling to estimate fp using soil properties. Compared with empirical moisture functions used in ESMs, this derived fp could reduce uncertainty in predicting the response of soil organic C stock to climate changes. In addition, this work is one of the first studies to upscale a mechanistic soil HR model based on pore-scale processes, thus linking the pore-scale mechanisms with macroscale observations.

Upscaling soil saturated hydraulic conductivity from pore throat characteristics

NASA Astrophysics Data System (ADS)

Ghanbarian, Behzad; Hunt, Allen G.; Skaggs, Todd H.; Jarvis, Nicholas

2017-06-01

Upscaling and/or estimating saturated hydraulic conductivity Ksat at the core scale from microscopic/macroscopic soil characteristics has been actively under investigation in the hydrology and soil physics communities for several decades. Numerous models have been developed based on different approaches, such as the bundle of capillary tubes model, pedotransfer functions, etc. In this study, we apply concepts from critical path analysis, an upscaling technique first developed in the physics literature, to estimate saturated hydraulic conductivity at the core scale from microscopic pore throat characteristics reflected in capillary pressure data. With this new model, we find Ksat estimations to be within a factor of 3 of the average measured saturated hydraulic conductivities reported by Rawls et al. (1982) for the eleven USDA soil texture classes.

Assessing the use of treated waste water for irrigation agricultural lands by using soil quality indices

NASA Astrophysics Data System (ADS)

Arcenegui, V.; Morugán, A.; García-Orenes, F.; Zornoza, R.; Mataix-Solera, J.; Navarro, M. A.; Guerrero, C.; Mataix-Beneyto, J.

2009-04-01

The use of treated wastewater for the irrigation of agricultural soils is an alternative to utilizing better-quality water, especially in semiarid regions where water shortage is a very serious problem. However, this practise can modify the soil equilibrium and affect its quality. In this work two soil quality indices (models) are used to evaluate the effects of long-term irrigation with treated wastewater in soil. The models were developed studying different soil properties in undisturbed forest soils in SE Spain, and the relationships between soil parameters were established using multiple linear regressions. Model 1, that explained 92% of the variance in soil organic carbon (SOC) showed that the SOC can be calculated by the linear combination of 6 physical, chemical and biochemical properties (acid phosphatase, water holding capacity (WHC), electrical conductivity (EC), available phosphorus (P), cation exchange capacity (CEC) and aggregate stability (AS)). Model 2 explains 89% of the SOC variance, which can be calculated by means of 7 chemical and biochemical properties (urease, phosphatase, and

Relationships between soil properties and toxicity of copper and nickel to bok choy and tomato in Chinese soils.

PubMed

Li, Bo; Zhang, Hongtao; Ma, Yibing; McLaughlin, Mike J

2013-10-01

The toxicity of copper (Cu) and nickel (Ni) to bok choy and tomato shoot growth was investigated in a wide range of Chinese soils with and without leaching with artificial rainwater. The results showed that the variations of Ni toxicity induced by soil properties were wider than those of Cu toxicity to both tomato and bok choy plant growth. Leaching generally decreased the toxicity of Cu and Ni added to soils, which also depended on soils, metals, and test plant species. Soil factors controlling metal phytotoxicity were found to be soil pH and soil organic carbon content for Cu, and soil pH for Ni. It was also found that soil pH had stronger effects on Ni toxicity than on Cu toxicity. Predictive toxicity models based on these soil factors were developed. These toxicity models for Cu and Ni toxicity to tomato plant growth were validated using an independent data set for European soils. These models could be applied to predict the Cu and Ni phytotoxicity in not only Chinese soils but also European soils. © 2013 SETAC.

Empirical relationships between soil moisture, albedo, and the planetary boundary layer height: a two-layer bucket model approach

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Z. M.; Papuga, S. A.

2013-12-01

In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moisture-precipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used data from the Santa Rita Creosote Ameriflux site and Tucson Airport atmospheric sounding to generate empirical relationships between soil moisture, albedo and PBLh. We developed empirical relationships and show that at least 50% of the variation in PBLh can be explained by soil moisture and albedo. Then, we used a stochastically driven two-layer bucket model of soil moisture dynamics and our empirical relationships to model PBLh. We explored soil moisture dynamics under three different mean annual precipitation regimes: current, increase, and decrease, to evaluate at the influence on soil moisture on land surface-atmospheric processes. While our precipitation regimes are simple, they represent future precipitation regimes that can influence the two soil layers in our conceptual framework. For instance, an increase in annual precipitation, could impact on deep soil moisture and atmospheric processes if precipitation events remain intense. We observed that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface - atmosphere applications are of great value.

Catchment hydrological change from soil degradation: A model study for assessing urbanization on the terrestrial water cycle

NASA Astrophysics Data System (ADS)

Shu, L.; Duffy, C.

2015-12-01

It is commonly held that land cover and land use changes from agriculture and urbanization impact the terrestrial water cycle primarily through changes in the land surface and canopy energy balance. Another, and in some cases more important factor is the role that landuse changes have on soil structure, compaction, and loss of carbon on hydrologic performance. The consequential change on soil properties, such as aggregation of soil particles, reduction of voids, impacts on matrix conductivity and macropore fractions, alter the hydrological processes in a watershed. Macropores promote rapid water and gas movement under wet conditions while the soil matrix preserves the water-holding capacity necessary for plant growth. The physically-based Penn State Integrated Hydrologic Model (PIHM) simulates water movement in soil with Richard's equation using an effective matrix-macropore conductivity. The model is able to capture the preferential flow and soil water storage in vertical and horizontal directions. Soil degradation leads to a reduction of the macropore fraction with dramatic changes in overall hydrologic performance under urban development and agricultural landuse practices. The effects on the terrestrial water cycle in the catchment reduce infiltration, soil water availability, recharge and subsurface baseflow to streams, while increasing heavy surface runoff and erosion. The Lancaster area and surrounding watershed in eastern Pennsylvania, USA is a benchmark watershed comprised of urban (24%), agricultural (58%) and forest lands (18%) respectively. After parameter estimation from national geospatial soils, landuse and historical climate reanalysis, three landuse scenarios were developed. 1) Pre-development forest landuse (<1700 AD), (2) deforestation for agriculture and light urban landuse (1700-1900), (3) urban-suburban development (1900-pres.). The watershed model was used to evaluate hydrologic changes due to landuse change and soil degradation. The effects of macropore reduction and compaction on hydrologic performance were found to be of the same order or greater magnitude than for changes in landuse practices alone. The research, funded by the US EPA, illustrates the complex interaction of landuse and soil changes on the terrestrial water cycle.

Exchangeable lead from prediction models relates to vetiver lead uptake in different soil types.

PubMed

Andra, Syam S; Sarkar, Dibyendu; Saminathan, Sumathi K M; Datta, Rupali

2011-12-01

Prediction models for exchangeable soil lead, published earlier in this journal (Andra et al. 2010a), were developed using a suite of native lead (Pb) paint-contaminated residential soils from two US cities heavily populated with homes constructed prior to Pb ban in paints. In this study, we tested the feasibility and practical applications of these prediction models for developing a phytoremediation design using vetiver grass (Vetiveria zizanioides), a Pb-tolerant plant. The models were used to estimate the exchangeable fraction of Pb available for vetiver uptake in four lead-spiked soil types, both acidic and alkaline, with varying physico-chemical properties and that are different from those used to build the prediction models. Results indicate a strong correlation for predictable exchangeable Pb with the observed fraction and as well with total Pb accumulated by vetiver grass grown in these soils. The correlation coefficient for the predicted vs. observed exchangeable Pb with p < 0.001 was 0.999, 0.996, 0.949, and 0.998 in the Immokalee, Millhopper, Pahokee Muck, and Tobosa soil type, respectively. Similarly, the correlation coefficient for the predicted exchangeable Pb vs. accumulated Pb in vetiver grass with p < 0.001 was 0.948, 0.983, 0.929, and 0.969 for each soil type, respectively. This study suggests that the success of a phytoremediation design could be assessed upfront by predicting the exchangeable Pb fraction in a given soil type based on its properties. This helps in modifying the soil conditions to enhance phytoextraction of Pb from contaminated soils.

Development of EOS data for granular material like sand by using micromodels

NASA Astrophysics Data System (ADS)

Larcher, M.; Gebbeken, N.

2012-08-01

Detonations in soil can occur due to several reasons: e.g. land mines or bombs from the Second World War. Soil is also often used as a protective barrier. In all cases the behaviour of soil loaded by shock waves is important. The simulation of shock wave loaded soil using hydro-codes like AUTODYN needs a failure model as well as an equation of state (EOS). The parameters for these models are often not known. The popular material law for sand from Laine and Sandvik [1], e.g., is a first approximation, but it can only be used for dry sand with a certain grain grading. The parameters porosity, grain grading, and humidity have a big influence on the material behaviour of cohesive soils. Micro-mechanic models can be used to develop the material behaviour of granular materials. EOS data can be obtained by numerically loading micro-mechanically modelled grains and measuring the density under a certain pressure in the finite element model. The influence of porosity, grain grading, and humidity can be easily investigated. EOS data are determined in this work for cohesive soils depending on these parameters.

Projected loss of soil organic carbon in temperate agricultural soils in the 21st century: effects of climate change and carbon input trends

PubMed Central

Wiesmeier, Martin; Poeplau, Christopher; Sierra, Carlos A.; Maier, Harald; Frühauf, Cathleen; Hübner, Rico; Kühnel, Anna; Spörlein, Peter; Geuß, Uwe; Hangen, Edzard; Schilling, Bernd; von Lützow, Margit; Kögel-Knabner, Ingrid

2016-01-01

Climate change and stagnating crop yields may cause a decline of SOC stocks in agricultural soils leading to considerable CO2 emissions and reduced agricultural productivity. Regional model-based SOC projections are needed to evaluate these potential risks. In this study, we simulated the future SOC development in cropland and grassland soils of Bavaria in the 21st century. Soils from 51 study sites representing the most important soil classes of Central Europe were fractionated and derived SOC pools were used to initialize the RothC soil carbon model. For each site, long-term C inputs were determined using the C allocation method. Model runs were performed for three different C input scenarios as a realistic range of projected yield development. Our modelling approach revealed substantial SOC decreases of 11–16% under an expected mean temperature increase of 3.3 °C assuming unchanged C inputs. For the scenario of 20% reduced C inputs, agricultural SOC stocks are projected to decline by 19–24%. Remarkably, even the optimistic scenario of 20% increased C inputs led to SOC decreases of 3–8%. Projected SOC changes largely differed among investigated soil classes. Our results indicated that C inputs have to increase by 29% to maintain present SOC stocks in agricultural soils. PMID:27585648

A first attempt to reproduce basaltic soil chronosequences using a process-based soil profile model: implications for our understanding of soil evolution

NASA Astrophysics Data System (ADS)

Johnson, M.; Gloor, M.; Lloyd, J.

2012-04-01

Soils are complex systems which hold a wealth of information on both current and past conditions and many biogeochemical processes. The ability to model soil forming processes and predict soil properties will enable us to quantify such conditions and contribute to our understanding of long-term biogeochemical cycles, particularly the carbon cycle and plant nutrient cycles. However, attempts to confront such soil model predictions with data are rare, although increasingly more data from chronosquence studies is becoming available for such a purpose. Here we present initial results of an attempt to reproduce soil properties with a process-based soil evolution model similar to the model of Kirkby (1985, J. Soil Science). We specifically focus on the basaltic soils in both Hawaii and north Queensland, Australia. These soils are formed on a series of volcanic lava flows which provide sequences of different aged soils all with a relatively uniform parent material. These soil chronosequences provide a snapshot of a soil profile during different stages of development. Steep rainfall gradients in these regions also provide a system which allows us to test the model's ability to reproduce soil properties under differing climates. The mechanistic, soil evolution model presented here includes the major processes of soil formation such as i) mineral weathering, ii) percolation of rainfall through the soil, iii) leaching of solutes out of the soil profile iv) surface erosion and v) vegetation and biotic interactions. The model consists of a vertical profile and assumes simple geometry with a constantly sloping surface. The timescales of interest are on the order of tens to hundreds of thousand years. The specific properties the model predicts are, soil depth, the proportion of original elemental oxides remaining in each soil layer, pH of the soil solution, organic carbon distribution and CO2 production and concentration. The presentation will focus on a brief introduction of the model, followed by a description of novel methods using tracers such as optically stimulated luminescence (OSL) dates and meteoric 10Be to evaluate the modelled processes of bioturbation and surface erosion. We will also discuss comparisons of modelled properties with observations and conclude with implications on our understanding of soil evolution.

Simulating carbon capture by enhanced weathering with croplands: an overview of key processes highlighting areas of future model development

PubMed Central

Quegan, Shaun; Banwart, Steven A.

2017-01-01

Enhanced weathering (EW) aims to amplify a natural sink for CO2 by incorporating powdered silicate rock with high reactive surface area into agricultural soils. The goal is to achieve rapid dissolution of minerals and release of alkalinity with accompanying dissolution of CO2 into soils and drainage waters. EW could counteract phosphorus limitation and greenhouse gas (GHG) emissions in tropical soils, and soil acidification, a common agricultural problem studied with numerical process models over several decades. Here, we review the processes leading to soil acidification in croplands and how the soil weathering CO2 sink is represented in models. Mathematical models capturing the dominant processes and human interventions governing cropland soil chemistry and GHG emissions neglect weathering, while most weathering models neglect agricultural processes. We discuss current approaches to modelling EW and highlight several classes of model having the potential to simulate EW in croplands. Finally, we argue for further integration of process knowledge in mathematical models to capture feedbacks affecting both longer-term CO2 consumption and crop growth and yields. PMID:28381633

Impact of vegetation on stability of slopes subjected to rainfall - numerical aspect

NASA Astrophysics Data System (ADS)

Switala, Barbara Maria; Tamagnini, Roberto; Sudan Acharya, Madhu; Wu, Wei

2015-04-01

Recent years brought a significant development of soil bioengineering methods, considered as an ecological and economically effective measure for slope stabilization. This work aims to show the advantages of the soil bioengineering solutions for a slope subjected to a heavy rainfall, with the help of a numerical model, which integrates most of the significant plant and slope features. There are basically two different ways in which vegetation can affect stability of a slope: root reinforcement (mechanical impact) and root water uptake (evapotranspiration). In the numerical model, the first factor is modelled using the Cam-Clay model extended for unsaturated conditions by Tamagnini (2004). The original formulation of a constitutive model is modified by introducing an additional constitutive parameter, which causes an expansion of the yield surface as a consequence of an increase in root mass in a representative soil element. The second factor is the root water uptake, which is defined as a volumetric sink term in the continuity equation of groundwater flow. Water removal from the soil mass causes an increase in suction in the vicinity of the root zone, which leads to an increase in the soil cohesion and provides additional strength to the soil-root composite. The developed numerical model takes into account the above mentioned effects of plants and thus considers the multi-phase nature of the soil-plant-water relationship. Using the developed method, stability of some vegetated and non-vegetated slopes subjected to rainfall are investigated. The performance of each slope is evaluated by the time at which slope failure occurs. Different slope geometries and soil mechanical and hydrological properties are considered. Comparison of the results obtained from the analyses of vegetated and non-vegetated slopes leads to the conclusion, that the use of soil bioengineering methods for slope stabilization can be effective and can significantly delay the occurrence of a rainfall induced landslide. On the contrary, vegetation removal can have serious consequences, especially on steep and forested slopes.

Chemical-Specific Representation of Air-Soil Exchange and Soil Penetration in Regional Multimedia Models

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

McKone, T.E.; Bennett, D.H.

2002-08-01

In multimedia mass-balance models, the soil compartment is an important sink as well as a conduit for transfers to vegetation and shallow groundwater. Here a novel approach for constructing soil transport algorithms for multimedia fate models is developed and evaluated. The resulting algorithms account for diffusion in gas and liquid components; advection in gas, liquid, or solid phases; and multiple transformation processes. They also provide an explicit quantification of the characteristic soil penetration depth. We construct a compartment model using three and four soil layers to replicate with high reliability the flux and mass distribution obtained from the exact analyticalmore » solution describing the transient dispersion, advection, and transformation of chemicals in soil with fixed properties and boundary conditions. Unlike the analytical solution, which requires fixed boundary conditions, the soil compartment algorithms can be dynamically linked to other compartments (air, vegetation, ground water, surface water) in multimedia fate models. We demonstrate and evaluate the performance of the algorithms in a model with applications to benzene, benzo(a)pyrene, MTBE, TCDD, and tritium.« less

Plasticity solutions for soil behaviour around contracting cavities and tunnels

NASA Astrophysics Data System (ADS)

Yu, H. S.; Rowe, R. K.

1999-10-01

The action of tunnel excavation reduces the in-situ stresses along the excavated circumference and can therefore be simulated by unloading of cavities from the in-situ stress state. Increasing evidence suggests that soil behavior in the plane perpendicular to the tunnel axis can be modelled reasonably by a contracting cylindrical cavity, while movements ahead of an advancing tunnel heading can be better predicted by spherical cavity contraction theory. In the past, solutions for unloading of cavities from in-situ stresses in cohesive-frictional soils have mainly concentrated on the small strain, cylindrical cavity model. Large strain spherical cavity contraction solutions with a non-associated Mohr-Coulomb model do not seem to be widely available for tunnel applications. Also, cavity unloading solutions in undrained clays have been developed only in terms of total stresses with a linear elastic-perfectly plastic soil model. The total stress analyses do not account for the effects of strain hardening/softening, variable soil stiffness, and soil stress history (OCR). The effect of these simplifying assumptions on the predicted soil behavior around tunnels is not known.In this paper, analytical and semi-analytical solutions are presented for unloading of both cylindrical and spherical cavities from in-situ state of stresses under both drained and undrained conditions. The non-associated Mohr-Coulomb model and various critical state theories are used respectively to describe the drained and undrained stress-strain behaviors of the soils. The analytical solutions presented in this paper are developed in terms of large strain formulations. These solutions can be used to serve two main purposes: (1) to provide models for predicting soil behavior around tunnels; (2) to provide valuable benchmark solutions for verifying various numerical methods involving both Mohr-Coulomb and critical state plasticity models.

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.

Creep model of unsaturated sliding zone soils and long-term deformation analysis of landslides

NASA Astrophysics Data System (ADS)

Zou, Liangchao; Wang, Shimei; Zhang, Yeming

2015-04-01

Sliding zone soil is a special soil layer formed in the development of a landslide. Its creep behavior plays a significant role in long-term deformation of landslides. Due to rainfall infiltration and reservoir water level fluctuation, the soils in the slide zone are often in unsaturated state. Therefore, the investigation of creep behaviors of the unsaturated sliding zone soils is of great importance for understanding the mechanism of the long-term deformation of a landslide in reservoir areas. In this study, the full-process creep curves of the unsaturated soils in the sliding zone in different net confining pressure, matric suctions and stress levels were obtained from a large number of laboratory triaxial creep tests. A nonlinear creep model for unsaturated soils and its three-dimensional form was then deduced based on the component model theory and unsaturated soil mechanics. This creep model was validated with laboratory creep data. The results show that this creep model can effectively and accurately describe the nonlinear creep behaviors of the unsaturated sliding zone soils. In order to apply this creep model to predict the long-term deformation process of landslides, a numerical model for simulating the coupled seepage and creep deformation of unsaturated sliding zone soils was developed based on this creep model through the finite element method (FEM). By using this numerical model, we simulated the deformation process of the Shuping landslide located in the Three Gorges reservoir area, under the cycling reservoir water level fluctuation during one year. The simulation results of creep displacement were then compared with the field deformation monitoring data, showing a good agreement in trend. The results show that the creeping deformations of landslides have strong connections with the changes of reservoir water level. The creep model of unsaturated sliding zone soils and the findings obtained by numerical simulations in this study are conducive to reveal the mechanisms of the dynamic process of landslide deformation, and serve as an important basis for the prediction and evaluation of landslides.

Boundary Condition Effects on Hillslope Form and Soil Development Along a Climatic Gradient From Semiarid to Hyperarid in Northern Chile

NASA Astrophysics Data System (ADS)

Owen, J. J.; Dietrich, W. E.; Nishiizumi, K.; Bellugi, D.; Amundson, R.

2008-12-01

Modeling the development of hillslopes using mass balance equations has generated many testable hypotheses related to morphology, process rates, and soil properties, however it is only relatively recently that techniques for constraining these models (such as cosmogenic radionuclides) have become commonplace. As such, many hypotheses related to the effects of boundary conditions or climate on process rates and soil properties have been left untested. We selected pairs of hillslopes along a precipitation gradient in northern Chile (24°-30° S) which were either bounded by actively eroding (bedrock-bedded) channels or by stable or aggradational landforms (pediments, colluvial aprons, valley bottoms). For each hillslope we measured soil properties, atmospheric deposition rates, and bedrock denudation rates. We observe significant changes in soil properties with climate: there is a shift from thick, weathered soils in the semiarid south, to the near absence of soil in the arid middle, to salt-rich soils in the hyperarid north. Coincident with these are dramatic changes in the types and rates of processes acting on the soils. We found relatively quick, biotically-driven soil formation and transport in the south, and very slow, salt-driven processes in the north. Additionally, we observe systematic differences between hillslopes of different boundary condition within the same climate zone, such as thicker soils, gentler slopes, and slower erosion rates on hillslopes with a non-eroding boundary versus an eroding boundary. These support general predictions based on hillslope soil mass balance equations and geomorphic transport laws. Using parameters derived from our field data, we attempt to use a mass balance model of hillslope development to explore the effect of changing boundary conditions and/or shifting climate.

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.

Spatial prediction of soil texture in region Centre (France) from summary data

NASA Astrophysics Data System (ADS)

Dobarco, Mercedes Roman; Saby, Nicolas; Paroissien, Jean-Baptiste; Orton, Tom G.

2015-04-01

Soil texture is a key controlling factor of important soil functions like water and nutrient holding capacity, retention of pollutants, drainage, soil biodiversity, and C cycling. High resolution soil texture maps enhance our understanding of the spatial distribution of soil properties and provide valuable information for decision making and crop management, environmental protection, and hydrological planning. We predicted the soil texture of agricultural topsoils in the Region Centre (France) combining regression and area-to-point kriging. Soil texture data was collected from the French soil-test database (BDAT), which is populated with soil analysis performed by farmers' demand. To protect the anonymity of the farms the data was treated by commune. In a first step, summary statistics of environmental covariates by commune were used to develop prediction models with Cubist, boosted regression trees, and random forests. In a second step the residuals of each individual observation were summarized by commune and kriged following the method developed by Orton et al. (2012). This approach allowed to include non-linear relationships among covariates and soil texture while accounting for the uncertainty on areal means in the area-to-point kriging step. Independent validation of the models was done using data from the systematic soil monitoring network of French soils. Future work will compare the performance of these models with a non-stationary variance geostatistical model using the most important covariates and summary statistics of texture data. The results will inform on whether the later and statistically more-challenging approach improves significantly texture predictions or whether the more simple area-to-point regression kriging can offer satisfactory results. The application of area-to-point regression kriging at national level using BDAT data has the potential to improve soil texture predictions for agricultural topsoils, especially when combined with existing maps (i.e., model ensemble).

Geoscience techniques for engineering assessment of Oman to India pipeline route

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

Baerenwald, P.D.; Mullee, J.E.; Campbell, K.J.

1996-12-31

A variety of geoscience techniques were used to define soil conditions and evaluate geologic processes in order to develop design criteria for complex segments of the proposed Oman to Indian pipeline route. Geophysical survey data, seafloor cores, ROV observation of the seafloor, and oceanographic measurements were the principal field data collected. Geotechnical soil testing, and X-ray radiography, detailed geologic logging, and C-14 age dating of cores were carried out. The diverse sets of field data and lab test results were integrated by a multi-disciplined team of geoscientists and engineers to develop geologic and soil models, soil design criteria, a turbidmore » flow model, and seafloor stability models. The integrated approach used here is applicable to other complex areas where seafloor stability needs to be assessed or design criteria need to be developed for active geologic processes.« less

Calibrating Nonlinear Soil Material Properties for Seismic Analysis Using Soil Material Properties Intended for Linear Analysis

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

Spears, Robert Edward; Coleman, Justin Leigh

2015-08-01

Seismic analysis of nuclear structures is routinely performed using guidance provided in “Seismic Analysis of Safety-Related Nuclear Structures and Commentary (ASCE 4, 1998).” This document, which is currently under revision, provides detailed guidance on linear seismic soil-structure-interaction (SSI) analysis of nuclear structures. To accommodate the linear analysis, soil material properties are typically developed as shear modulus and damping ratio versus cyclic shear strain amplitude. A new Appendix in ASCE 4-2014 (draft) is being added to provide guidance for nonlinear time domain SSI analysis. To accommodate the nonlinear analysis, a more appropriate form of the soil material properties includes shear stressmore » and energy absorbed per cycle versus shear strain. Ideally, nonlinear soil model material properties would be established with soil testing appropriate for the nonlinear constitutive model being used. However, much of the soil testing done for SSI analysis is performed for use with linear analysis techniques. Consequently, a method is described in this paper that uses soil test data intended for linear analysis to develop nonlinear soil material properties. To produce nonlinear material properties that are equivalent to the linear material properties, the linear and nonlinear model hysteresis loops are considered. For equivalent material properties, the shear stress at peak shear strain and energy absorbed per cycle should match when comparing the linear and nonlinear model hysteresis loops. Consequently, nonlinear material properties are selected based on these criteria.« less

Modelling carbon and nitrogen turnover in variably saturated soils

NASA Astrophysics Data System (ADS)

Batlle-Aguilar, J.; Brovelli, A.; Porporato, A.; Barry, D. A.

2009-04-01

Natural ecosystems provide services such as ameliorating the impacts of deleterious human activities on both surface and groundwater. For example, several studies have shown that a healthy riparian ecosystem can reduce the nutrient loading of agricultural wastewater, thus protecting the receiving surface water body. As a result, in order to develop better protection strategies and/or restore natural conditions, there is a growing interest in understanding ecosystem functioning, including feedbacks and nonlinearities. Biogeochemical transformations in soils are heavily influenced by microbial decomposition of soil organic matter. Carbon and nutrient cycles are in turn strongly sensitive to environmental conditions, and primarily to soil moisture and temperature. These two physical variables affect the reaction rates of almost all soil biogeochemical transformations, including microbial and fungal activity, nutrient uptake and release from plants, etc. Soil water saturation and temperature are not constants, but vary both in space and time, thus further complicating the picture. In order to interpret field experiments and elucidate the different mechanisms taking place, numerical tools are beneficial. In this work we developed a 3D numerical reactive-transport model as an aid in the investigation the complex physical, chemical and biological interactions occurring in soils. The new code couples the USGS models (MODFLOW 2000-VSF, MT3DMS and PHREEQC) using an operator-splitting algorithm, and is a further development an existing reactive/density-dependent flow model PHWAT. The model was tested using simplified test cases. Following verification, a process-based biogeochemical reaction network describing the turnover of carbon and nitrogen in soils was implemented. Using this tool, we investigated the coupled effect of moisture content and temperature fluctuations on nitrogen and organic matter cycling in the riparian zone, in order to help understand the relative sensitivity of biological transformations to these processes.

Assessing soil erosion using USLE model and MODIS data in the Guangdong, China

NASA Astrophysics Data System (ADS)

Gao, Feng; Wang, Yunpeng; Yang, Jingxue

2017-07-01

In this study, soil erosion in the Guangdong, China during 2012 was quantitatively assessed using Universal Soil Loss Equation (USLE). The parameters of the model were calculated using GIS and MODIS data. The spatial distribution of the average annual soil loss on grid basis was mapped. The estimated average annual soil erosion in Guangdong in 2012 is about 2294.47t/ (km2.a). Four high sensitive area of soil erosion in Guangdong in 2012 was found. The key factors of these four high sensitive areas of soil erosion were significantly contributed to the land cover types, rainfall and Economic development and human activities.

WEPP and ANN models for simulating soil loss and runoff in a semi-arid Mediterranean region.

PubMed

Albaradeyia, Issa; Hani, Azzedine; Shahrour, Isam

2011-09-01

This paper presents the use of both the Water Erosion Prediction Project (WEPP) and the artificial neural network (ANN) for the prediction of runoff and soil loss in the central highland mountainous of the Palestinian territories. Analyses show that the soil erosion is highly dependent on both the rainfall depth and the rainfall event duration rather than on the rainfall intensity as mostly mentioned in the literature. The results obtained from the WEPP model for the soil loss and runoff disagree with the field data. The WEPP underestimates both the runoff and soil loss. Analyses conducted with the ANN agree well with the observation. In addition, the global network models developed using the data of all the land use type show a relatively unbiased estimation for both runoff and soil loss. The study showed that the ANN model could be used as a management tool for predicting runoff and soil loss.

Runoff as a factor in USLE/RUSLE technology

NASA Astrophysics Data System (ADS)

Kinnell, Peter

2014-05-01

Modelling erosion for prediction purposes started with the development of the Universal Soil Loss Equation the focus of which was the prediction of long term (~20) average annul soil loss from field sized areas. That purpose has been maintained in the subsequent revision RUSLE, the most widely used erosion prediction model in the world. The lack of ability to predict short term soil loss saw the development of so-called process based models like WEPP and EUROSEM which focussed on predicting event erosion but failed to improve the prediction of long term erosion where the RUSLE worked well. One of the features of erosion recognised in the so-called process based modes is the fact that runoff is a primary factor in rainfall erosion and some modifications of USLE/RUSLE model have been proposed have included runoff as in independent factor in determining event erosivity. However, these models have ignored fundamental mathematical rules. The USLE-M which replaces the EI30 index by the product of the runoff ratio and EI30 was developed from the concept that soil loss is the product of runoff and sediment concentration and operates in a way that obeys the mathematical rules upon which the USLE/RUSLE model was based. In accounts for event soil loss better that the EI30 index where runoff values are known or predicted adequately. RUSLE2 now includes a capacity to model runoff driven erosion.

A radiosity-based model to compute the radiation transfer of soil surface

NASA Astrophysics Data System (ADS)

Zhao, Feng; Li, Yuguang

2011-11-01

A good understanding of interactions of electromagnetic radiation with soil surface is important for a further improvement of remote sensing methods. In this paper, a radiosity-based analytical model for soil Directional Reflectance Factor's (DRF) distributions was developed and evaluated. The model was specifically dedicated to the study of radiation transfer for the soil surface under tillage practices. The soil was abstracted as two dimensional U-shaped or V-shaped geometric structures with periodic macroscopic variations. The roughness of the simulated surfaces was expressed as a ratio of the height to the width for the U and V-shaped structures. The assumption was made that the shadowing of soil surface, simulated by U or V-shaped grooves, has a greater influence on the soil reflectance distribution than the scattering properties of basic soil particles of silt and clay. Another assumption was that the soil is a perfectly diffuse reflector at a microscopic level, which is a prerequisite for the application of the radiosity method. This radiosity-based analytical model was evaluated by a forward Monte Carlo ray-tracing model under the same structural scenes and identical spectral parameters. The statistics of these two models' BRF fitting results for several soil structures under the same conditions showed the good agreements. By using the model, the physical mechanism of the soil bidirectional reflectance pattern was revealed.

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".

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 mathematical model accuracy estimation of the oil storage tank foundation soil moistening

NASA Astrophysics Data System (ADS)

Gildebrandt, M. I.; Ivanov, R. N.; Gruzin, AV; Antropova, L. B.; Kononov, S. A.

2018-04-01

The oil storage tanks foundations preparation technologies improvement is the relevant objective which achievement will make possible to reduce the material costs and spent time for the foundation preparing while providing the required operational reliability. The laboratory research revealed the nature of sandy soil layer watering with a given amount of water. The obtained data made possible developing the sandy soil layer moistening mathematical model. The performed estimation of the oil storage tank foundation soil moistening mathematical model accuracy showed the experimental and theoretical results acceptable convergence.

Estimating net rainfall, evaporation and water storage of a bare soil from sequential L-band emissivities

NASA Technical Reports Server (NTRS)

Stroosnijder, L.; Lascano, R. J.; Newton, R. W.; Vanbavel, C. H. M.

1984-01-01

A general method to use a time series of L-band emissivities as an input to a hydrological model for continuously monitoring the net rainfall and evaporation as well as the water content over the entire soil profile is proposed. The model requires a sufficiently accurate and general relation between soil emissivity and surface moisture content. A model which requires the soil hydraulic properties as an additional input, but does not need any weather data was developed. The method is shown to be numerically consistent.

Soil mapping and processes models to support climate change mitigation and adaptation strategies: a review

NASA Astrophysics Data System (ADS)

Muñoz-Rojas, Miriam; Pereira, Paulo; Brevik, Eric; Cerda, Artemi; Jordan, Antonio

2017-04-01

As agreed in Paris in December 2015, global average temperature is to be limited to "well below 2 °C above pre-industrial levels" and efforts will be made to "limit the temperature increase to 1.5 °C above pre-industrial levels. Thus, reducing greenhouse gas emissions (GHG) in all sectors becomes critical and appropriate sustainable land management practices need to be taken (Pereira et al., 2017). Mitigation strategies focus on reducing the rate and magnitude of climate change by reducing its causes. Complementary to mitigation, adaptation strategies aim to minimise impacts and maximize the benefits of new opportunities. The adoption of both practices will require developing system models to integrate and extrapolate anticipated climate changes such as global climate models (GCMs) and regional climate models (RCMs). Furthermore, integrating climate models driven by socio-economic scenarios in soil process models has allowed the investigation of potential changes and threats in soil characteristics and functions in future climate scenarios. One of the options with largest potential for climate change mitigation is sequestering carbon in soils. Therefore, the development of new methods and the use of existing tools for soil carbon monitoring and accounting have therefore become critical in a global change context. For example, soil C maps can help identify potential areas where management practices that promote C sequestration will be productive and guide the formulation of policies for climate change mitigation and adaptation strategies. Despite extensive efforts to compile soil information and map soil C, many uncertainties remain in the determination of soil C stocks, and the reliability of these estimates depends upon the quality and resolution of the spatial datasets used for its calculation. Thus, better estimates of soil C pools and dynamics are needed to advance understanding of the C balance and the potential of soils for climate change mitigation. Here, we discuss the most recent advances on the application of soil mapping and modeling to support climate change mitigation and adaptation strategies; and These strategies are a key component of the implementation of sustainable land management policies need to be integrated are critical to. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. Muñoz-Rojas, M., Pereira, P., Brevic, E., Cerda, A., Jordan, A. (2017) Soil mapping and processes models for sustainable land management applied to modern challenges. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

Rich in life but poor in data: the known knowns and known unknowns of modelling how soil biology drives soil structure

NASA Astrophysics Data System (ADS)

Hallett, Paul; Ogden, Mike

2015-04-01

Soil biology has a fascinating capacity to manipulate pore structure by altering or overcoming hydrological and mechanical properties of soil. Many have postulated, quite rightly, that this capacity of soil biology to 'engineer' its habitat drives its diversity, improves competitiveness and increases resilience to external stresses. A large body of observational research has quantified pore structure evolution accompanied by the growth of organisms in soil. Specific compounds that are exuded by organisms or the biological structures they create have been isolated and found to correlate well with observed changes to pore structure or soil stability. This presentation will provide an overview of basic mechanical and hydrological properties of soil that are affected by biology, and consider missing data that are essential to model how they impact soil structure evolution. Major knowledge gaps that prevent progress will be identified and suggestions will be made of how research in this area should progress. We call for more research to gain a process based understanding of structure formation by biology, to complement observational studies of soil structure before and after imposed biological activity. Significant advancement has already been made in modelling soil stabilisation by plant roots, by combining data on root biomechanics, root-soil interactions and soil mechanical properties. Approaches for this work were developed from earlier materials science and geotechnical engineering research, and the same ethos should be adopted to model the impacts of other biological compounds. Fungal hyphae likely reinforce soils in a similar way to plant roots, with successful biomechanical measurements of these micron diameter structures achieved with micromechanical test frames. Extending root reinforcement models to fungi would not be a straightforward exercise, however, as interparticle bonding and changes to pore water caused by fungal exudates could have a major impact on structure formation and stability. Biological exudates from fungi, bacteria or roots have been found to decrease surface tension and increase viscosity of pore water, with observed impacts to soil strength and water retention. Modelling approaches developed in granular mechanics and geotechnical engineering could be built upon to incorporate biological transformations of hydrological and mechanical properties of soil. With new testing approaches, adapted from materials science, pore scale hydromechanical impacts from biological exudates can be quantified. The research can be complemented with model organisms with differences in biological structures (e.g. root hair mutants), exudation or other properties. Coupled with technological advances that provide 4D imaging of soil structure at relatively rapid capture rates, the potential opportunities to disentangle and model how biology drives soil structure evolution and stability are vast. By quantifying basic soil hydrological and mechanical processes that are driven by soil biology, unknown unknowns may also emerge, providing new insight into how soils function.

Modeling soil erosion and transport on forest landscape

Treesearch

Ge Sun; Steven G McNulty

1998-01-01

Century-long studies on the impacts of forest management in North America suggest sediment can cause major reduction on stream water quality. Soil erosion patterns in forest watersheds are patchy and heterogeneous. Therefore, patterns of soil erosion are difficult to model and predict. The objective of this study is to develop a user friendly management tool for land...

Quantification of colloidal and aqueous element transfer in soils: The dual-phase mass balance model

USGS Publications Warehouse

Bern, Carleton R.; Thompson, Aaron; Chadwick, Oliver A.

2015-01-01

Mass balance models have become standard tools for characterizing element gains and losses and volumetric change during weathering and soil development. However, they rely on the assumption of complete immobility for an index element such as Ti or Zr. Here we describe a dual-phase mass balance model that eliminates the need for an assumption of immobility and in the process quantifies the contribution of aqueous versus colloidal element transfer. In the model, the high field strength elements Ti and Zr are assumed to be mobile only as suspended solids (colloids) and can therefore be used to distinguish elemental redistribution via colloids from redistribution via dissolved aqueous solutes. Calculations are based upon element concentrations in soil, parent material, and colloids dispersed from soil in the laboratory. We illustrate the utility of this model using a catena in South Africa. Traditional mass balance models systematically distort elemental gains and losses and changes in soil volume in this catena due to significant redistribution of Zr-bearing colloids. Applying the dual-phase model accounts for this colloidal redistribution and we find that the process accounts for a substantial portion of the major element (e.g., Al, Fe and Si) loss from eluvial soil. In addition, we find that in illuvial soils along this catena, gains of colloidal material significantly offset aqueous elemental loss. In other settings, processes such as accumulation of exogenous dust can mimic the geochemical effects of colloid redistribution and we suggest strategies for distinguishing between the two. The movement of clays and colloidal material is a major process in weathering and pedogenesis; the mass balance model presented here is a tool for quantifying effects of that process over time scales of soil development.

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.

[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.

A new model integrating short- and long-term aging of copper added to soils

PubMed Central

Zeng, Saiqi; Li, Jumei; Wei, Dongpu

2017-01-01

Aging refers to the processes by which the bioavailability/toxicity, isotopic exchangeability, and extractability of metals added to soils decline overtime. We studied the characteristics of the aging process in copper (Cu) added to soils and the factors that affect this process. Then we developed a semi-mechanistic model to predict the lability of Cu during the aging process with descriptions of the diffusion process using complementary error function. In the previous studies, two semi-mechanistic models to separately predict short-term and long-term aging of Cu added to soils were developed with individual descriptions of the diffusion process. In the short-term model, the diffusion process was linearly related to the square root of incubation time (t1/2), and in the long-term model, the diffusion process was linearly related to the natural logarithm of incubation time (lnt). Both models could predict short-term or long-term aging processes separately, but could not predict the short- and long-term aging processes by one model. By analyzing and combining the two models, we found that the short- and long-term behaviors of the diffusion process could be described adequately using the complementary error function. The effect of temperature on the diffusion process was obtained in this model as well. The model can predict the aging process continuously based on four factors—soil pH, incubation time, soil organic matter content and temperature. PMID:28820888

Application of stochastic models in identification and apportionment of heavy metal pollution sources in the surface soils of a large-scale region.

PubMed

Hu, Yuanan; Cheng, Hefa

2013-04-16

As heavy metals occur naturally in soils at measurable concentrations and their natural background contents have significant spatial variations, identification and apportionment of heavy metal pollution sources across large-scale regions is a challenging task. Stochastic models, including the recently developed conditional inference tree (CIT) and the finite mixture distribution model (FMDM), were applied to identify the sources of heavy metals found in the surface soils of the Pearl River Delta, China, and to apportion the contributions from natural background and human activities. Regression trees were successfully developed for the concentrations of Cd, Cu, Zn, Pb, Cr, Ni, As, and Hg in 227 soil samples from a region of over 7.2 × 10(4) km(2) based on seven specific predictors relevant to the source and behavior of heavy metals: land use, soil type, soil organic carbon content, population density, gross domestic product per capita, and the lengths and classes of the roads surrounding the sampling sites. The CIT and FMDM results consistently indicate that Cd, Zn, Cu, Pb, and Cr in the surface soils of the PRD were contributed largely by anthropogenic sources, whereas As, Ni, and Hg in the surface soils mostly originated from the soil parent materials.

Estimation of liquefaction-induced lateral spread from numerical modeling and its application

NASA Astrophysics Data System (ADS)

Meng, Xianhong

A noncoupled numerical procedure was developed using a scheme of pore water generation that causes shear modulus degradation and shear strength degradation resulting from earthquake cyclic motion. The designed Fast Lagrangian Analysis of Continua (FLAC) model procedure was tested using the liquefaction-induced lateral spread and ground response for Wildlife and Kobe sites. Sixteen well-documented case histories of lateral spread were reviewed and modeled using the modeling procedure. The dynamic residual strength ratios were back-calculated by matching the predicted displacement with the measured lateral spread, or with the displacement predicted by the Yound et al. model. Statistical analysis on the modeling results and soil properties show that most significant parameters governing the residual strength of the liquefied soil are the SPT blow count, fine content and soil particle size of the lateral spread layer. A regression equation was developed to express the residual strength values with these soil properties. Overall, this research demonstrated that a calibrated numerical model can predict the first order effectiveness of liquefaction-induced lateral spread using relatively simple parameters obtained from routine geotechnical investigation. In addition, the model can be used to plan a soil improvement program for cases where liquefaction remediation is needed. This allows the model to be used for design purposes at bridge approaches structured on liquefiable materials.

Developing and using artificial soils to analyze soil microbial processes

NASA Astrophysics Data System (ADS)

Gao, X.; Cheng, H. Y.; Boynton, L.; Masiello, C. A.; Silberg, J. J.

2017-12-01

Microbial diversity and function in soils are governed by soil characteristics such as mineral composition, particles size and aggregations, soil organic matter (SOM), and availability of nutrients and H2O. The spatial and temporal heterogeneity of soils creates a range of niches (hotspots) differing in the availability of O2, H2O, and nutrients, which shapes microbial activities at scales ranging from nanometer to landscape. Synthetic biologists often examine microbial response trigged by their environment conditions in nutrient-rich aqueous media using single strain microbes. While these studies provided useful insight in the role of soil microbes in important soil biogeochemical processes (e.g., C cycling, N cycling, etc.), the results obtained from the over-simplified model systems are often not applicable natural soil systems. On the contrary, soil microbiologists examine microbial processes in natural soils using longer incubation time. However, due to its physical, chemical and biological complexity of natural soils, it is often difficult to examine soil characteristics independently and understand how each characteristic influences soil microbial activities and their corresponding soil functioning. Therefore, it is necessary to bridge the gap and develop a model matrix to exclude unpredictable influences from the environment while still reliably mimicking real environmental conditions. The objective of this study is to design a range of ecologically-relevant artificial soils with varying texture (particle size distribution), structure, mineralogy, SOM content, and nutrient heterogeneity. We thoroughly characterize the artificial soils for pH, active surface area and surface morphology, cation exchange capacity (CEC), and water retention curve. We demonstrate the effectiveness of the artificial soils as useful matrix for microbial processes, such as microbial growth and horizontal gene transfer (HGT), using the gas-reporting biosensors recently developed in our lab.

Kinetic modeling of antimony(III) oxidation and sorption in soils.

PubMed

Cai, Yongbing; Mi, Yuting; Zhang, Hua

2016-10-05

Kinetic batch and saturated column experiments were performed to study the oxidation, adsorption and transport of Sb(III) in two soils with contrasting properties. Kinetic and column experiment results clearly demonstrated the extensive oxidation of Sb(III) in soils, and this can in return influence the adsorption and transport of Sb. Both sorption capacity and kinetic oxidation rate were much higher in calcareous Huanjiang soil than in acid red Yingtan soil. The results indicate that soil serve as a catalyst in promoting oxidation of Sb(III) even under anaerobic conditions. A PHREEQC model with kinetic formulations was developed to simulate the oxidation, sorption and transport of Sb(III) in soils. The model successfully described Sb(III) oxidation and sorption data in kinetic batch experiment. It was less successful in simulating the reactive transport of Sb(III) in soil columns. Additional processes such as colloid facilitated transport need to be quantified and considered in the model. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluation of snow and frozen soil parameterization in a cryosphere land surface modeling framework in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhou, J.

2017-12-01

Snow and frozen soil are important components in the Tibetan Plateau, and influence the water cycle and energy balances through snowpack accumulation and melt and soil freeze-thaw. In this study, a new cryosphere land surface model (LSM) with coupled snow and frozen soil parameterization was developed based on a hydrologically improved LSM (HydroSiB2). First, an energy-balance-based three-layer snow model was incorporated into HydroSiB2 (hereafter HydroSiB2-S) to provide an improved description of the internal processes of the snow pack. Second, a universal and simplified soil model was coupled with HydroSiB2-S to depict soil water freezing and thawing (hereafter HydroSiB2-SF). In order to avoid the instability caused by the uncertainty in estimating water phase changes, enthalpy was adopted as a prognostic variable instead of snow/soil temperature in the energy balance equation of the snow/frozen soil module. The newly developed models were then carefully evaluated at two typical sites of the Tibetan Plateau (TP) (one snow covered and the other snow free, both with underlying frozen soil). At the snow-covered site in northeastern TP (DY), HydroSiB2-SF demonstrated significant improvements over HydroSiB2-F (same as HydroSiB2-SF but using the original single-layer snow module of HydroSiB2), showing the importance of snow internal processes in three-layer snow parameterization. At the snow-free site in southwestern TP (Ngari), HydroSiB2-SF reasonably simulated soil water phase changes while HydroSiB2-S did not, indicating the crucial role of frozen soil parameterization in depicting the soil thermal and water dynamics. Finally, HydroSiB2-SF proved to be capable of simulating upward moisture fluxes toward the freezing front from the underlying soil layers in winter.

An objective analysis of the dynamic nature of field capacity

NASA Astrophysics Data System (ADS)

Twarakavi, Navin K. C.; Sakai, Masaru; Å Imå¯Nek, Jirka

2009-10-01

Field capacity is one of the most commonly used, and yet poorly defined, soil hydraulic properties. Traditionally, field capacity has been defined as the amount of soil moisture after excess water has drained away and the rate of downward movement has materially decreased. Unfortunately, this qualitative definition does not lend itself to an unambiguous quantitative approach for estimation. Because of the vagueness in defining what constitutes "drainage of excess water" from a soil, the estimation of field capacity has often been based upon empirical guidelines. These empirical guidelines are either time, pressure, or flux based. In this paper, we developed a numerical approach to estimate field capacity using a flux-based definition. The resulting approach was implemented on the soil parameter data set used by Schaap et al. (2001), and the estimated field capacity was compared to traditional definitions of field capacity. The developed modeling approach was implemented using the HYDRUS-1D software with the capability of simultaneously estimating field capacity for multiple soils with soil hydraulic parameter data. The Richards equation was used in conjunction with the van Genuchten-Mualem model to simulate variably saturated flow in a soil. Using the modeling approach to estimate field capacity also resulted in additional information such as (1) the pressure head, at which field capacity is attained, and (2) the drainage time needed to reach field capacity from saturated conditions under nonevaporative conditions. We analyzed the applicability of the modeling-based approach to estimate field capacity on real-world soils data. We also used the developed method to create contour diagrams showing the variation of field capacity with texture. It was found that using benchmark pressure heads to estimate field capacity from the retention curve leads to inaccurate results. Finally, a simple analytical equation was developed to predict field capacity from soil hydraulic parameter information. The analytical equation was found to be effective in its ability to predict field capacities.

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 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.

Spectral element modelling of seismic wave propagation in visco-elastoplastic media including excess-pore pressure development

NASA Astrophysics Data System (ADS)

Oral, Elif; Gélis, Céline; Bonilla, Luis Fabián; Delavaud, Elise

2017-12-01

Numerical modelling of seismic wave propagation, considering soil nonlinearity, has become a major topic in seismic hazard studies when strong shaking is involved under particular soil conditions. Indeed, when strong ground motion propagates in saturated soils, pore pressure is another important parameter to take into account when successive phases of contractive and dilatant soil behaviour are expected. Here, we model 1-D seismic wave propagation in linear and nonlinear media using the spectral element numerical method. The study uses a three-component (3C) nonlinear rheology and includes pore-pressure excess. The 1-D-3C model is used to study the 1987 Superstition Hills earthquake (ML 6.6), which was recorded at the Wildlife Refuge Liquefaction Array, USA. The data of this event present strong soil nonlinearity involving pore-pressure effects. The ground motion is numerically modelled for different assumptions on soil rheology and input motion (1C versus 3C), using the recorded borehole signals as input motion. The computed acceleration-time histories show low-frequency amplification and strong high-frequency damping due to the development of pore pressure in one of the soil layers. Furthermore, the soil is found to be more nonlinear and more dilatant under triaxial loading compared to the classical 1C analysis, and significant differences in surface displacements are observed between the 1C and 3C approaches. This study contributes to identify and understand the dominant phenomena occurring in superficial layers, depending on local soil properties and input motions, conditions relevant for site-specific studies.

Implications of climate change for evaporation from bare soils in a Mediterranean environment.

PubMed

Aydin, Mehmet; Yano, Tomohisa; Evrendilek, Fatih; Uygur, Veli

2008-05-01

The purpose of this study was to predict quantitative changes in evaporation from bare soils in the Mediterranean climate region of Turkey in response to the projections of a regional climate model developed in Japan (hereafter RCM). Daily RCM data for the estimation of reference evapotranspiration (ETr) and soil evaporation were obtained for the periods of 1994--2003 and 2070--2079. Potential evaporation (Ep) from bare soils was calculated using the Penman-Monteith equation with a surface resistance of zero. Simulation of actual soil evaporation (Ea) was carried out using Aydin model (Aydin et al., Ecological Modelling 182:91-105, 2005) combined with Aydin and Uygur (2006, A model for estimating soil water potential of bare fields. In Proceedings of the 18th International Soil Meeting (ISM) on Soils Sustaining Life on Earth, Managing Soil and Technology, Sanliurfa, 477-480pp.) model of predicting soil water potential at the top surface layer of a bare soil, after performances of Aydin model (R2 = 94.0%) and Aydin and Uygur model (R2 = 97.6) were tested. The latter model is based on the relations among potential soil evaporation, hydraulic diffusivity, and soil wetness, with some simplified assumptions. Input parameters of the model are simple and easily obtainable such as climatic parameters used to compute the potential soil evaporation, average diffusivity for the drying soil, and volumetric water content at field capacity. The combination of Aydin and Aydin and Uygur models appeared to be useful in estimating water potential of soils and Ea from bare soils, with only a few parameters. Unlike ETr and Ep projected to increase by 92 and 69 mm (equivalent to 8.0 and 7.3% increases) due to the elevated evaporative demand of the atmosphere, respectively, Ea from bare soils is projected to reduce by 50 mm (equivalent to a 16.5% decrease) in response to a decrease in rainfall by 46% in the Mediterranean region of Turkey by the 2070s predicted by RCM, and consequently, to decreased soil wetness in the future.

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.

Microwave remote sensing and radar polarization signatures of natural fields

NASA Technical Reports Server (NTRS)

Mo, Tsan

1989-01-01

Theoretical models developed for simulation of microwave remote sensing of the Earth surface from airborne/spaceborne sensors are described. Theoretical model calculations were performed and the results were compared with data of field measurements. Data studied included polarimetric images at the frequencies of P band, L band, and C band, acquired with airborne polarimeters over a agricultural field test site. Radar polarization signatures from bare soil surfaces and from tree covered fields were obtained from the data. The models developed in this report include: (1) Small perturbation model of wave scatterings from randomly rough surfaces, (2) Physical optics model, (3) Geometrical optics model, and (4) Electromagnetic wave scattering from dielectric cylinders of finite lengths, which replace the trees and branches in the modeling of tree covered field. Additionally, a three-layer emissivity model for passive sensing of a vegetation covered soil surface is also developed. The effects of surface roughness, soil moisture contents, and tree parameters on the polarization signatures were investigated.

Time series modelling of increased soil temperature anomalies during long period

NASA Astrophysics Data System (ADS)

Shirvani, Amin; Moradi, Farzad; Moosavi, Ali Akbar

2015-10-01

Soil temperature just beneath the soil surface is highly dynamic and has a direct impact on plant seed germination and is probably the most distinct and recognisable factor governing emergence. Autoregressive integrated moving average as a stochastic model was developed to predict the weekly soil temperature anomalies at 10 cm depth, one of the most important soil parameters. The weekly soil temperature anomalies for the periods of January1986-December 2011 and January 2012-December 2013 were taken into consideration to construct and test autoregressive integrated moving average models. The proposed model autoregressive integrated moving average (2,1,1) had a minimum value of Akaike information criterion and its estimated coefficients were different from zero at 5% significance level. The prediction of the weekly soil temperature anomalies during the test period using this proposed model indicated a high correlation coefficient between the observed and predicted data - that was 0.99 for lead time 1 week. Linear trend analysis indicated that the soil temperature anomalies warmed up significantly by 1.8°C during the period of 1986-2011.

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.

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.

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.

CHEMFLO-2000: INTERACTIVE SOFTWARE FOR PREDICTING AND VISUALIZING TRANSIENT WATER AND CHEMICAL MOVEMENT IN SOILS AND ASSOCIATED UNCERTAINTIES

EPA Science Inventory

An interactive Java applet and a stand-alone application program will be developed based on the CHEMFLO model developed in the mid-1980s and published as an EPA report (EPA/600/8-89/076). The model solves Richards Equation for transient water movement in unsaturated soils, and so...

Accomplishments of the NASA Johnson Space Center portion of the soil moisture project in fiscal year 1981

NASA Technical Reports Server (NTRS)

Paris, J. F.; Arya, L. M.; Davidson, S. A.; Hildreth, W. W.; Richter, J. C.; Rosenkranz, W. A.

1982-01-01

The NASA/JSC ground scatterometer system was used in a row structure and row direction effects experiment to understand these effects on radar remote sensing of soil moisture. Also, a modification of the scatterometer system was begun and is continuing, to allow cross-polarization experiments to be conducted in fiscal years 1982 and 1983. Preprocessing of the 1978 agricultural soil moisture experiment (ASME) data was completed. Preparations for analysis of the ASME data is fiscal year 1982 were completed. A radar image simulation procedure developed by the University of Kansas is being improved. Profile soil moisture model outputs were compared quantitatively for the same soil and climate conditions. A new model was developed and tested to predict the soil moisture characteristic (water tension versus volumetric soil moisture content) from particle-size distribution and bulk density data. Relationships between surface-zone soil moisture, surface flux, and subsurface moisture conditions are being studied as well as the ways in which measured soil moisture (as obtained from remote sensing) can be used for agricultural applications.

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

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.

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).

Wetting and drying of soil in response to precipitation: Data analysis, modeling, and forecasting

USGS Publications Warehouse

Basak, Aniruddha; Kulkarni, Chinmay; Schmidt, Kevin M.; Mengshoel, Ole

2016-01-01

This paper investigates methods to analyze and forecast soil moisture time series. We extend an existing Antecedent Water Index (AWI) model, which expresses soil moisture as a function of time and rainfall. Unfortunately, the existing AWI model does not forecast effectively for time periods beyond a few hours. To overcome this limitation, we develop a novel AWI-based model. Our model accumulates rainfall over a time interval and can fit a diverse range of wetting and drying curves. In addition, parameters in our model reflect hydrologic redistribution processes of gravity and suction.We validate our models using experimental soil moisture and rainfall time series data collected from steep gradient post-wildfire sites in Southern California, where rapid landscape change was observed in response to small to moderate rain storms. We found that our novel model fits the data for three distinct soil textures, occurring at different depths below the ground surface (5, 15, and 30 cm). Our model also successfully forecasts soil moisture trends, such as drying and wetting rate.

Comparison of three approaches to model grapevine organogenesis in conditions of fluctuating temperature, solar radiation and soil water content.

PubMed

Pallas, B; Loi, C; Christophe, A; Cournède, P H; Lecoeur, J

2011-04-01

There is increasing interest in the development of plant growth models representing the complex system of interactions between the different determinants of plant development. These approaches are particularly relevant for grapevine organogenesis, which is a highly plastic process dependent on temperature, solar radiation, soil water deficit and trophic competition. The extent to which three plant growth models were able to deal with the observed plasticity of axis organogenesis was assessed. In the first model, axis organogenesis was dependent solely on temperature, through thermal time. In the second model, axis organogenesis was modelled through functional relationships linking meristem activity and trophic competition. In the last model, the rate of phytomer appearence on each axis was modelled as a function of both the trophic status of the plant and the direct effect of soil water content on potential meristem activity. The model including relationships between trophic competition and meristem behaviour involved a decrease in the root mean squared error (RMSE) for the simulations of organogenesis by a factor nine compared with the thermal time-based model. Compared with the model in which axis organogenesis was driven only by trophic competition, the implementation of relationships between water deficit and meristem behaviour improved organogenesis simulation results, resulting in a three times divided RMSE. The resulting model can be seen as a first attempt to build a comprehensive complete plant growth model simulating the development of the whole plant in fluctuating conditions of temperature, solar radiation and soil water content. We propose a new hypothesis concerning the effects of the different determinants of axis organogenesis. The rate of phytomer appearance according to thermal time was strongly affected by the plant trophic status and soil water deficit. Furthermore, the decrease in meristem activity when soil water is depleted does not result from source/sink imbalances.

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.

From patterns to causal understanding: Structural equation modeling (SEM) in soil ecology

USGS Publications Warehouse

Eisenhauer, Nico; Powell, Jeff R; Grace, James B.; Bowker, Matthew A.

2015-01-01

In this perspectives paper we highlight a heretofore underused statistical method in soil ecological research, structural equation modeling (SEM). SEM is commonly used in the general ecological literature to develop causal understanding from observational data, but has been more slowly adopted by soil ecologists. We provide some basic information on the many advantages and possibilities associated with using SEM and provide some examples of how SEM can be used by soil ecologists to shift focus from describing patterns to developing causal understanding and inspiring new types of experimental tests. SEM is a promising tool to aid the growth of soil ecology as a discipline, particularly by supporting research that is increasingly hypothesis-driven and interdisciplinary, thus shining light into the black box of interactions belowground.

Near infrared spectroscopy to estimate the temperature reached on burned soils: strategies to develop robust models.

NASA Astrophysics Data System (ADS)

Guerrero, César; Pedrosa, Elisabete T.; Pérez-Bejarano, Andrea; Keizer, Jan Jacob

2014-05-01

The temperature reached on soils is an important parameter needed to describe the wildfire effects. However, the methods for measure the temperature reached on burned soils have been poorly developed. Recently, the use of the near-infrared (NIR) spectroscopy has been pointed as a valuable tool for this purpose. The NIR spectrum of a soil sample contains information of the organic matter (quantity and quality), clay (quantity and quality), minerals (such as carbonates and iron oxides) and water contents. Some of these components are modified by the heat, and each temperature causes a group of changes, leaving a typical fingerprint on the NIR spectrum. This technique needs the use of a model (or calibration) where the changes in the NIR spectra are related with the temperature reached. For the development of the model, several aliquots are heated at known temperatures, and used as standards in the calibration set. This model offers the possibility to make estimations of the temperature reached on a burned sample from its NIR spectrum. However, the estimation of the temperature reached using NIR spectroscopy is due to changes in several components, and cannot be attributed to changes in a unique soil component. Thus, we can estimate the temperature reached by the interaction between temperature and the thermo-sensible soil components. In addition, we cannot expect the uniform distribution of these components, even at small scale. Consequently, the proportion of these soil components can vary spatially across the site. This variation will be present in the samples used to construct the model and also in the samples affected by the wildfire. Therefore, the strategies followed to develop robust models should be focused to manage this expected variation. In this work we compared the prediction accuracy of models constructed with different approaches. These approaches were designed to provide insights about how to distribute the efforts needed for the development of robust models, since this step is the bottle-neck of this technique. In the first approach, a plot-scale model was used to predict the temperature reached in samples collected in other plots from the same site. In a plot-scale model, all the heated aliquots come from a unique plot-scale sample. As expected, the results obtained with this approach were deceptive, because this approach was assuming that a plot-scale model would be enough to represent the whole variability of the site. The accuracy (measured as the root mean square error of prediction, thereinafter RMSEP) was 86ºC, and the bias was also high (>30ºC). In the second approach, the temperatures predicted through several plot-scale models were averaged. The accuracy was improved (RMSEP=65ºC) respect the first approach, because the variability from several plots was considered and biased predictions were partially counterbalanced. However, this approach implies more efforts, since several plot-scale models are needed. In the third approach, the predictions were obtained with site-scale models. These models were constructed with aliquots from several plots. In this case, the results were accurate, since the RMSEP was around 40ºC, the bias was very small (<1ºC) and the R2 was 0.92. As expected, this approach clearly outperformed the second approach, in spite of the fact that the same efforts were needed. In a plot-scale model, only one interaction between temperature and soil components was modelled. However, several different interactions between temperature and soil components were present in the calibration matrix of a site-scale model. Consequently, the site-scale models were able to model the temperature reached excluding the influence of the differences in soil composition, resulting in more robust models respect that variation. Summarizing, the results were highlighting the importance of an adequate strategy to develop robust and accurate models with moderate efforts, and how a wrong strategy can result in deceptive predictions.

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.

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.

An Assessment of the Impact of Urbanization on Soil Erosion in Inner Mongolia.

PubMed

Wang, Li-Yan; Xiao, Yi; Rao, En-Ming; Jiang, Ling; Xiao, Yang; Ouyang, Zhi-Yun

2018-03-19

Inner Mongolia, an autonomous region of the People's Republic of China, has experienced severe soil erosion following a period of rapid economic development and urbanization. To investigate how urbanization has influenced the extent of soil erosion in Inner Mongolia, we used urbanization and soil erosion data from 2000 through 2010 to determine the relationship between urbanization and soil erosion patterns. Two empirical equations-the Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ)-were used to estimate the intensity of soil erosion, and we performed backward linear regression to model how it changed with greater urbanization. There was an apparent increase in the rate of urbanization and a decrease in the area affected by soil erosion in 2010 compared to the corresponding values for 2000. The urban population stood at 11.32 million in 2010, which represented a 16.47% increase over that in 2000. The area affected by soil erosion in 2000 totaled 704,817 km², yet it had decreased to 674,135 km² by 2010. However, a path of modest urban development (rural-urban mitigation) and reasonable industrial structuring (the development of GDP-2) may partially reduce urbanization's ecological pressure and thus indirectly reduce the threat of soil erosion to human security. Therefore, to better control soil erosion in Inner Mongolia during the process of urbanization, the current model of economic development should be modified to improve the eco-efficiency of urbanization, while also promoting new modes of urbanization that are environmentally sustainable, cost-effective, and conserve limited resources.

An Assessment of the Impact of Urbanization on Soil Erosion in Inner Mongolia

PubMed Central

Xiao, Yi; Rao, En-Ming; Jiang, Ling; Xiao, Yang; Ouyang, Zhi-Yun

2018-01-01

Inner Mongolia, an autonomous region of the People’s Republic of China, has experienced severe soil erosion following a period of rapid economic development and urbanization. To investigate how urbanization has influenced the extent of soil erosion in Inner Mongolia, we used urbanization and soil erosion data from 2000 through 2010 to determine the relationship between urbanization and soil erosion patterns. Two empirical equations—the Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ)—were used to estimate the intensity of soil erosion, and we performed backward linear regression to model how it changed with greater urbanization. There was an apparent increase in the rate of urbanization and a decrease in the area affected by soil erosion in 2010 compared to the corresponding values for 2000. The urban population stood at 11.32 million in 2010, which represented a 16.47% increase over that in 2000. The area affected by soil erosion in 2000 totaled 704,817 km2, yet it had decreased to 674,135 km2 by 2010. However, a path of modest urban development (rural–urban mitigation) and reasonable industrial structuring (the development of GDP-2) may partially reduce urbanization’s ecological pressure and thus indirectly reduce the threat of soil erosion to human security. Therefore, to better control soil erosion in Inner Mongolia during the process of urbanization, the current model of economic development should be modified to improve the eco-efficiency of urbanization, while also promoting new modes of urbanization that are environmentally sustainable, cost-effective, and conserve limited resources. PMID:29562707

Effect of Speed on Tire-Soil Interaction and Development of Towed Pneumatic Tire-Soil Model

DTIC Science & Technology

1974-10-01

rigid wheels were per- formed by several researchers under laboratory conditions (Refs. 20 through 22) using the flash X -ray technique. These experiments...Towed Tire-Soil Model ................................... 90 IX Conclusions and Recommendations .............. 95 X References...Velocity Fields ................................. A-1 x Section Page Appendix B - Computer Program Chart for Computation 3- of Tire Performance with

A vegetation-focused soil-plant-atmospheric continuum model to study hydrodynamic soil-plant water relations

NASA Astrophysics Data System (ADS)

Deng, Zijuan; Guan, Huade; Hutson, John; Forster, Michael A.; Wang, Yunquan; Simmons, Craig T.

2017-06-01

A novel simple soil-plant-atmospheric continuum model that emphasizes the vegetation's role in controlling water transfer (v-SPAC) has been developed in this study. The v-SPAC model aims to incorporate both plant and soil hydrological measurements into plant water transfer modeling. The model is different from previous SPAC models in which v-SPAC uses (1) a dynamic plant resistance system in the form of a vulnerability curve that can be easily obtained from sap flow and stem xylem water potential time series and (2) a plant capacitance parameter to buffer the effects of transpiration on root water uptake. The unique representation of root resistance and capacitance allows the model to embrace SPAC hydraulic pathway from bulk soil, to soil-root interface, to root xylem, and finally to stem xylem where the xylem water potential is measured. The v-SPAC model was tested on a native tree species in Australia, Eucalyptus crenulata saplings, with controlled drought treatment. To further validate the robustness of the v-SPAC model, it was compared against a soil-focused SPAC model, LEACHM. The v-SPAC model simulation results closely matched the observed sap flow and stem water potential time series, as well as the soil moisture variation of the experiment. The v-SPAC model was found to be more accurate in predicting measured data than the LEACHM model, underscoring the importance of incorporating root resistance into SPAC models and the benefit of integrating plant measurements to constrain SPAC modeling.

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.

Evaluation of liquefaction potential of soil based on standard penetration test using multi-gene genetic programming model

NASA Astrophysics Data System (ADS)

Muduli, Pradyut; Das, Sarat

2014-06-01

This paper discusses the evaluation of liquefaction potential of soil based on standard penetration test (SPT) dataset using evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). The liquefaction classification accuracy (94.19%) of the developed liquefaction index (LI) model is found to be better than that of available artificial neural network (ANN) model (88.37%) and at par with the available support vector machine (SVM) model (94.19%) on the basis of the testing data. Further, an empirical equation is presented using MGGP to approximate the unknown limit state function representing the cyclic resistance ratio (CRR) of soil based on developed LI model. Using an independent database of 227 cases, the overall rates of successful prediction of occurrence of liquefaction and non-liquefaction are found to be 87, 86, and 84% by the developed MGGP based model, available ANN and the statistical models, respectively, on the basis of calculated factor of safety (F s) against the liquefaction occurrence.

Modeling physical and biogeochemical controls over carbon accumulation in a boreal forest soil

USGS Publications Warehouse

Carrasco, J.J.; Neff, J.C.; Harden, J.W.

2006-01-01

Boreal soils are important to the global C cycle owing to large C stocks, repeated disturbance from fire, and the potential for permafrost thaw to expose previously stable, buried C. To evaluate the primary mechanisms responsible for both short- and long-term C accumulation in boreal soils, we developed a multi-isotope (12,14C) Soil C model with dynamic soil layers that develop through time as soil organic matter burns and reaccumulates. We then evaluated the mechanisms that control organic matter turnover in boreal regions including carbon input rates, substrate recalcitrance, soil moisture and temperature, and the presence of historical permafrost to assess the importance of these factors in boreal C accumulation. Results indicate that total C accumulation is controlled by the rate of carbon input, decomposition rates, and the presence of historical permafrost. However, unlike more temperate ecosystems, one of the key mechanisms involved in C preservation in boreal soils examined here is the cooling of subsurface soil layers as soil depth increases rather than increasing recalcitrance in subsurface soils. The propagation of the 14C bomb spike into soils also illustrates the importance of historical permafrost and twentieth century warming in contemporary boreal soil respiration fluxes. Both 14C and total C simulation data also strongly suggest that boreal SOM need not be recalcitrant to accumulate; the strong role of soil temperature controls on boreal C accumulation at our modeling test site in Manitoba, Canada, indicates that carbon in the deep organic soil horizons is probably relatively labile and thus subject to perturbations that result from changing climatic conditions in the future. Copyright 2006 by the American Geophysical Union.

Incorporation of satellite remote sensing pan-sharpened imagery into digital soil prediction and mapping models to characterize soil property variability in small agricultural fields

NASA Astrophysics Data System (ADS)

Xu, Yiming; Smith, Scot E.; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P.

2017-01-01

Soil prediction models based on spectral indices from some multispectral images are too coarse to characterize spatial pattern of soil properties in small and heterogeneous agricultural lands. Image pan-sharpening has seldom been utilized in Digital Soil Mapping research before. This research aimed to analyze the effects of pan-sharpened (PAN) remote sensing spectral indices on soil prediction models in smallholder farm settings. This research fused the panchromatic band and multispectral (MS) bands of WorldView-2, GeoEye-1, and Landsat 8 images in a village in Southern India by Brovey, Gram-Schmidt and Intensity-Hue-Saturation methods. Random Forest was utilized to develop soil total nitrogen (TN) and soil exchangeable potassium (Kex) prediction models by incorporating multiple spectral indices from the PAN and MS images. Overall, our results showed that PAN remote sensing spectral indices have similar spectral characteristics with soil TN and Kex as MS remote sensing spectral indices. There is no soil prediction model incorporating the specific type of pan-sharpened spectral indices always had the strongest prediction capability of soil TN and Kex. The incorporation of pan-sharpened remote sensing spectral data not only increased the spatial resolution of the soil prediction maps, but also enhanced the prediction accuracy of soil prediction models. Small farms with limited footprint, fragmented ownership and diverse crop cycle should benefit greatly from the pan-sharpened high spatial resolution imagery for soil property mapping. Our results show that multiple high and medium resolution images can be used to map soil properties suggesting the possibility of an improvement in the maps' update frequency. Additionally, the results should benefit the large agricultural community through the reduction of routine soil sampling cost and improved prediction accuracy.

Soil physics: a Moroccan perspective

NASA Astrophysics Data System (ADS)

Lahlou, Sabah; Mrabet, Rachid; Ouadia, Mohamed

2004-06-01

Research on environmental pollution and degradation of soil and water resources is now of highest priority worldwide. To address these problems, soil physics should be conceived as a central core to this research. This paper objectives are to: (1) address the role and importance of soil physics, (2) demonstrate progress in this discipline, and (3) present various uses of soil physics in research, environment and industry. The study of dynamic processes at and within the soil vadose zone (flow, dispersion, transport, sedimentation, etc.), and ephemeral phenomena (deformation, compaction, etc.), form an area of particular interest in soil physics. Soil physics has changed considerably over time. These changes are due to needed precision in data collection for accurate interpretation of space and time variation of soil properties. Soil physics interacts with other disciplines and sciences such as hydro(geo)logy, agronomy, environment, micro-meteorology, pedology, mathematics, physics, water sciences, etc. These interactions prompted the emergence of advanced theories and comprehensive mechanisms of most natural processes, development of new mathematical tools (modeling and computer simulation, fractals, geostatistics, transformations), creation of high precision instrumentation (computer assisted, less time constraint, increased number of measured parameters) and the scale sharpening of physical measurements which ranges from micro to watershed. The environment industry has contributed to an enlargement of many facets of soil physics. In other words, research demand in soil physics has increased considerably to satisfy specific and environmental problems (contamination of water resources, global warming, etc.). Soil physics research is still at an embryonic stage in Morocco. Consequently, soil physicists can take advantage of developments occurring overseas, and need to build up a database of soil static and dynamic properties and to revise developed models to meet our conditions. Large, but special, investment is required to promote research programs in soil physics, which consider developments in this discipline and respect Moroccan needs. These programs will be highlighted herein.

Effects of soil properties on copper toxicity to earthworm Eisenia fetida in 15 Chinese soils.

PubMed

Duan, Xiongwei; Xu, Meng; Zhou, Youya; Yan, Zengguang; Du, Yanli; Zhang, Lu; Zhang, Chaoyan; Bai, Liping; Nie, Jing; Chen, Guikui; Li, Fasheng

2016-02-01

The bioavailability and toxicity of metals in soil are influenced by a variety of soil properties, and this principle should be recognized in establishing soil environmental quality criteria. In the present study, the uptake and toxicity of Cu to the earthworm Eisenia fetida in 15 Chinese soils with various soil properties were investigated, and regression models for predicting Cu toxicity across soils were developed. The results showed that earthworm survival and body weight change were less sensitive to Cu than earthworm cocoon production. The soil Cu-based median effective concentrations (EC50s) for earthworm cocoon production varied from 27.7 to 383.7 mg kg(-1) among 15 Chinese soils, representing approximately 14-fold variation. Soil cation exchange capacity and organic carbon content were identified as key factors controlling Cu toxicity to earthworm cocoon production, and simple and multiple regression models were developed for predicting Cu toxicity across soils. Tissue Cu-based EC50s for earthworm cocoon production were also calculated and varied from 15.5 to 62.5 mg kg(-1) (4-fold variation). Compared to the soil Cu-based EC50s for cocoon production, the tissue Cu-based EC50s had less variation among soils, indicating that metals in tissue were more relevant to toxicity than metals in soil and hence represented better measurements of bioavailability. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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.

The relative importance of physical erosion and soil water dynamics on chemical weathering and soil formation: learning from field and model results

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Giraldez, J. V.

2015-12-01

A new model is presented that integrates the effect of landscape evolution and soil formation. This model is based on a daily spatially-explicit soil water balance. Average soil water content, temperature and deep percolation fluxes are linked to weathering and soil formation processes. Model input (temperature and precipitation) for the last 25 000 years was generated on a daily time by combining palaeoclimate data and the WXGEN weather generator. The soil-landscape model was applied to a 48 km2 semi-natural catchment in Southern Spain, with soils developed on granite. Model-generated runoff was used for a first validation against discharge observations. Next, soil formation output was contrasted against experimental data from 10 soil profiles along two catenas. Field data showed an important variation in mobile regolith thickness, between 0,44 and 1,10m, and in chemical weathering along the catena. Southern slopes were characterized by shallower, stonier and carbon-poor soils, while soils on north-facing slopes were deeper, more fine-textured and had a higher carbon content. Chemical depletion fraction was found to vary between 0,41 and 0,72. The lowest overall weathering intensity was found on plateau positions. South facing slopes revealed slightly lower weathering compared to north facing slopes. We attribute this to higher runoff generation and physical erosion rates on north facing slopes, transporting weathered material downslope. Model results corroborate these findings and show continuously wet soils on north-facing slopes with more runoff generation and a steady deep percolation flux during the wet winter season. On south-facing slopes, infiltration is higher and percolation is more erratic over time. Soils on the footslopes then were shown to be significantly impacted by deposition of sediment through lateral erosion fluxes.

Modeling soil temperature change in Seward Peninsula, Alaska

NASA Astrophysics Data System (ADS)

Debolskiy, M. V.; Nicolsky, D.; Romanovsky, V. E.; Muskett, R. R.; Panda, S. K.

2017-12-01

Increasing demand for assessment of climate change-induced permafrost degradation and its consequences promotes creation of high-resolution modeling products of soil temperature changes. This is especially relevant for areas with highly vulnerable warm discontinuous permafrost in the Western Alaska. In this study, we apply ecotype-based modeling approach to simulate high-resolution permafrost distribution and its temporal dynamics in Seward Peninsula, Alaska. To model soil temperature dynamics, we use a transient soil heat transfer model developed at the Geophysical Institute Permafrost Laboratory (GIPL-2). The model solves one dimensional nonlinear heat equation with phase change. The developed model is forced with combination of historical climate and different future scenarios for 1900-2100 with 2x2 km resolution prepared by Scenarios Network for Alaska and Arctic Planning (2017). Vegetation, snow and soil properties are calibrated by ecotype and up-scaled by using Alaska Existing Vegetation Type map for Western Alaska (Flemming, 2015) with 30x30 m resolution provided by Geographic Information Network of Alaska (UAF). The calibrated ecotypes cover over 75% of the study area. We calibrate the model using a data assimilation technique utilizing available observations of air, surface and sub-surface temperatures and snow cover collected by various agencies and research groups (USGS, Geophysical Institute, USDA). The calibration approach takes into account a natural variability between stations in the same ecotype and finds an optimal set of model parameters (snow and soil properties) within the study area. This approach allows reduction in microscale heterogeneity and aggregated soil temperature data from shallow boreholes which is highly dependent on local conditions. As a result of this study we present a series of preliminary high resolution maps for the Seward Peninsula showing changes in the active layer depth and ground temperatures for the current climate and future climate change scenarios.

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.

Nonlinear Time Domain Seismic Soil-Structure Interaction (SSI) Deep Soil Site Methodology Development

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

Spears, Robert Edward; Coleman, Justin Leigh

Currently the Department of Energy (DOE) and the nuclear industry perform seismic soil-structure interaction (SSI) analysis using equivalent linear numerical analysis tools. For lower levels of ground motion, these tools should produce reasonable in-structure response values for evaluation of existing and new facilities. For larger levels of ground motion these tools likely overestimate the in-structure response (and therefore structural demand) since they do not consider geometric nonlinearities (such as gaping and sliding between the soil and structure) and are limited in the ability to model nonlinear soil behavior. The current equivalent linear SSI (SASSI) analysis approach either joins the soilmore » and structure together in both tension and compression or releases the soil from the structure for both tension and compression. It also makes linear approximations for material nonlinearities and generalizes energy absorption with viscous damping. This produces the potential for inaccurately establishing where the structural concerns exist and/or inaccurately establishing the amplitude of the in-structure responses. Seismic hazard curves at nuclear facilities have continued to increase over the years as more information has been developed on seismic sources (i.e. faults), additional information gathered on seismic events, and additional research performed to determine local site effects. Seismic hazard curves are used to develop design basis earthquakes (DBE) that are used to evaluate nuclear facility response. As the seismic hazard curves increase, the input ground motions (DBE’s) used to numerically evaluation nuclear facility response increase causing larger in-structure response. As ground motions increase so does the importance of including nonlinear effects in numerical SSI models. To include material nonlinearity in the soil and geometric nonlinearity using contact (gaping and sliding) it is necessary to develop a nonlinear time domain methodology. This methodology will be known as, NonLinear Soil-Structure Interaction (NLSSI). In general NLSSI analysis should provide a more accurate representation of the seismic demands on nuclear facilities their systems and components. INL, in collaboration with a Nuclear Power Plant Vender (NPP-V), will develop a generic Nuclear Power Plant (NPP) structural design to be used in development of the methodology and for comparison with SASSI. This generic NPP design has been evaluated for the INL soil site because of the ease of access and quality of the site specific data. It is now being evaluated for a second site at Vogtle which is located approximately 15 miles East-Northeast of Waynesboro, Georgia and adjacent to Savanna River. The Vogtle site consists of many soil layers spanning down to a depth of 1058 feet. The reason that two soil sites are chosen is to demonstrate the methodology across multiple soil sites. The project will drive the models (soil and structure) using successively increasing acceleration time histories with amplitudes. The models will be run in time domain codes such as ABAQUS, LS-DYNA, and/or ESSI and compared with the same models run in SASSI. The project is focused on developing and documenting a method for performing time domain, non-linear seismic soil structure interaction (SSI) analysis. Development of this method will provide the Department of Energy (DOE) and industry with another tool to perform seismic SSI analysis.« less

Modelling the bioaccumulation of persistent organic pollutants in agricultural food chains for regulatory exposure assessment.

PubMed

Takaki, Koki; Wade, Andrew J; Collins, Chris D

2017-02-01

New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.

Advances in Land Data Assimilation at the NASA Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Reichle, Rolf

2009-01-01

Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.

ANZSoilML: An Australian - New Zealand standard for exchange of soil data

NASA Astrophysics Data System (ADS)

Simons, Bruce; Wilson, Peter; Ritchie, Alistair; Cox, Simon

2013-04-01

The Australian-New Zealand soil information exchange standard (ANZSoilML) is a GML-based standard designed to allow the discovery, query and delivery of soil and landscape data via standard Open Geospatial Consortium (OGC) Web Feature Services. ANZSoilML modifies the Australian soil exchange standard (OzSoilML), which is based on the Australian Soil Information Transfer and Evaluation System (SITES) database design and exchange protocols, to meet the New Zealand National Soils Database requirements. The most significant change was the removal of the lists of CodeList terms in OzSoilML, which were based on the field methods specified in the 'Australian Soil and Land Survey Field Handbook'. These were replaced with empty CodeLists as placeholders to external vocabularies to allow the use of New Zealand vocabularies without violating the data model. Testing of the use of these separately governed Australian and New Zealand vocabularies has commenced. ANZSoilML attempts to accommodate the proposed International Organization for Standardization ISO/DIS 28258 standard for soil quality. For the most part, ANZSoilML is consistent with the ISO model, although major differences arise as a result of: • The need to specify the properties appropriate for each feature type; • The inclusion of soil-related 'Landscape' features; • Allowing the mapping of soil surfaces, bodies, layers and horizons, independent of the soil profile; • Allowing specifying the relationships between the various soil features; • Specifying soil horizons as specialisations of soil layers; • Removing duplication of features provided by the ISO Observation & Measurements standard. The International Union of Soil Sciences (IUSS) Working Group on Soil Information Standards (WG-SIS) aims to develop, promote and maintain a standard to facilitate the exchange of soils data and information. Developing an international exchange standard that is compatible with existing and emerging national and regional standards is a considerable challenge. ANZSoilML is proposed as a profile of the more generalised SoilML model being progressed through the IUSS Working Group.

Growth patterns of red pine on fine-textured soils.

Treesearch

David H. Alban; Donald H. Prettyman; Gary J. Brand

1987-01-01

Compares growth of 28- to 49-year-old red pine plantations on sandy and fine-textured soils. Red pine growing on these two contrasting soils did not differ in bole form, live crown ratio, or mortality, and tree growth predicted by models (STEMS and REDPINE) developed from trees growing on sandy soils worked equally well for trees growing on fine-textured soils.

Don't soil your chances with solar energy: Experiments of natural dust accumulation on solar modules and the effect on light transmission

NASA Astrophysics Data System (ADS)

Boyle, Liza

Dust accumulation, or soiling, on solar energy harvesting systems can cause significant losses that reduce the power output of the system, increase pay-back time of the system, and reduce confidence in solar energy overall. Developing a method of estimating soiling losses could greatly improve estimates of solar energy system outputs, greatly improve operation and maintenance of solar systems, and improve siting of solar energy systems. This dissertation aims to develop a soiling model by collecting ambient soiling data as well as other environmental data and fitting a model to these data. In general a process-level approach is taken to estimating soiling. First a comparison is made between mass of deposited particulates and transmission loss. Transmission loss is the reduction in light that a solar system would see due to soiling, and mass accumulation represents the level of soiling in the system. This experiment is first conducted at two sites in the Front Range of Colorado and then expanded to three additional sites. Second mass accumulation is examined as a function of airborne particulate matter (PM) concentrations, airborne size distributions, and meteorological data. In depth analysis of this process step is done at the first two sites in Colorado, and a more general analysis is done at the three additional sites. This step is identified as less understood step, but with results still allowing for a general soiling model to be developed. Third these two process steps are combined, and spatial variability of these steps are examined. The three additional sites (an additional site in the Front Range of Colorado, a site in Albuquerque New Mexico, and a site in Cocoa Florida) represent a much more spatially and climatically diverse set of locations than the original two sites and provide a much broader sample space in which to develop the combined soiling model. Finally a few additional parameters, precipitation, micro-meteorology, and some sampling artifacts, are cursorily examined. This is to provide a broader context for these results and to help future researchers in understanding the strengths and weaknesses of this dissertation and the results presented within.

Low Velocity Earth-Penetration Test and Analysis

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Jones, Yvonne; Knight, Norman F., Jr.; Kellas, Sotiris

2001-01-01

Modeling and simulation of structural impacts into soil continue to challenge analysts to develop accurate material models and detailed analytical simulations to predict the soil penetration event. This paper discusses finite element modeling of a series of penetrometer drop tests into soft clay. Parametric studies are performed with penetrometers of varying diameters, masses, and impact speeds to a maximum of 45 m/s. Parameters influencing the simulation such as the contact penalty factor and the material model representing the soil are also studied. An empirical relationship between key parameters is developed and is shown to correlate experimental and analytical results quite well. The results provide preliminary design guidelines for Earth impact that may be useful for future space exploration sample return missions.

Development of a coupled model of a distributed hydrological model and a rice growth model for optimizing irrigation schedule

NASA Astrophysics Data System (ADS)

Tsujimoto, Kumiko; Homma, Koki; Koike, Toshio; Ohta, Tetsu

2013-04-01

A coupled model of a distributed hydrological model and a rice growth model was developed in this study. The distributed hydrological model used in this study is the Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) developed by Wang et al. (2009). This model includes a modified SiB2 (Simple Biosphere Model, Sellers et al., 1996) and the Geomorphology-Based Hydrological Model (GBHM) and thus it can physically calculate both water and energy fluxes. The rice growth model used in this study is the Simulation Model for Rice-Weather relations (SIMRIW) - rainfed developed by Homma et al. (2009). This is an updated version of the original SIMRIW (Horie et al., 1987) and can calculate rice growth by considering the yield reduction due to water stress. The purpose of the coupling is the integration of hydrology and crop science to develop a tool to support decision making 1) for determining the necessary agricultural water resources and 2) for allocating limited water resources to various sectors. The efficient water use and optimal water allocation in the agricultural sector are necessary to balance supply and demand of limited water resources. In addition, variations in available soil moisture are the main reasons of variations in rice yield. In our model, soil moisture and the Leaf Area Index (LAI) are calculated inside SIMRIW-rainfed so that these variables can be simulated dynamically and more precisely based on the rice than the more general calculations is the original WEB-DHM. At the same time by coupling SIMRIW-rainfed with WEB-DHM, lateral flow of soil water, increases in soil moisture and reduction of river discharge due to the irrigation, and its effects on the rice growth can be calculated. Agricultural information such as planting date, rice cultivar, fertilization amount are given in a fully distributed manner. The coupled model was validated using LAI and soil moisture in a small basin in western Cambodia (Sangker River Basin). This basin is mostly rainfed paddy so that irrigation scheme was firstly switched off. Several simulations with varying irrigation scheme were performed to determine the optimal irrigation schedule in this basin.

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.

Revisiting classic water erosion models in drylands: The strong impact of biological soil crusts

USGS Publications Warehouse

Bowker, M.A.; Belnap, J.; Bala, Chaudhary V.; Johnson, N.C.

2008-01-01

Soil erosion and subsequent degradation has been a contributor to societal collapse in the past and is one of the major expressions of desertification in arid regions. The revised universal soil loss equation (RUSLE) models soil lost to water erosion as a function of climate erosivity (the degree to which rainfall can result in erosion), topography, soil erodibility, and land use/management. The soil erodibility factor (K) is primarily based upon inherent soil properties (those which change slowly or not at all) such as soil texture and organic matter content, while the cover/management factor (C) is based on several parameters including biological soil crust (BSC) cover. We examined the effect of two more precise indicators of BSC development, chlorophyll a and exopolysaccharides (EPS), upon soil stability, which is closely inversely related to soil loss in an erosion event. To examine the relative influence of these elements of the C factor to the K factor, we conducted our investigation across eight strongly differing soils in the 0.8 million ha Grand Staircase-Escalante National Monument. We found that within every soil group, chlorophyll a was a moderate to excellent predictor of soil stability (R2 = 0.21-0.75), and consistently better than EPS. Using a simple structural equation model, we explained over half of the variance in soil stability and determined that the direct effect of chlorophyll a was 3?? more important than soil group in determining soil stability. Our results suggest that, holding the intensity of erosive forces constant, the acceleration or reduction of soil erosion in arid landscapes will primarily be an outcome of management practices. This is because the factor which is most influential to soil erosion, BSC development, is also among the most manageable, implying that water erosion in drylands has a solution. ?? 2008 Elsevier Ltd.

Development and deployment of a water-crop-nutrient simulation model embedded in a web application

NASA Astrophysics Data System (ADS)

Langella, Giuliano; Basile, Angelo; Coppola, Antonio; Manna, Piero; Orefice, Nadia; Terribile, Fabio

2016-04-01

It is long time by now that scientific research on environmental and agricultural issues spent large effort in the development and application of models for prediction and simulation in spatial and temporal domains. This is fulfilled by studying and observing natural processes (e.g. rainfall, water and chemicals transport in soils, crop growth) whose spatiotemporal behavior can be reproduced for instance to predict irrigation and fertilizer requirements and yield quantities/qualities. In this work a mechanistic model to simulate water flow and solute transport in the soil-plant-atmosphere continuum is presented. This desktop computer program was written according to the specific requirement of developing web applications. The model is capable to solve the following issues all together: (a) water balance and (b) solute transport; (c) crop modelling; (d) GIS-interoperability; (e) embedability in web-based geospatial Decision Support Systems (DSS); (f) adaptability at different scales of application; and (g) ease of code modification. We maintained the desktop characteristic in order to further develop (e.g. integrate novel features) and run the key program modules for testing and validation purporses, but we also developed a middleware component to allow the model run the simulations directly over the web, without software to be installed. The GIS capabilities allows the web application to make simulations in a user-defined region of interest (delimited over a geographical map) without the need to specify the proper combination of model parameters. It is possible since the geospatial database collects information on pedology, climate, crop parameters and soil hydraulic characteristics. Pedological attributes include the spatial distribution of key soil data such as soil profile horizons and texture. Further, hydrological parameters are selected according to the knowledge about the spatial distribution of soils. The availability and definition in the geospatial domain of these attributes allow the simulation outputs at a different spatial scale. Two different applications were implemented using the same framework but with different configurations of the software pieces making the physically based modelling chain: an irrigation tool simulating water requirements and their dates and a fertilization tool for optimizing in particular mineral nitrogen adds.

Use of slope, aspect, and elevation maps derived from digital elevation model data in making soil surveys

USGS Publications Warehouse

Klingebiel, A.A.; Horvath, E.H.; Moore, D.G.; Reybold, W.U.

1987-01-01

Maps showing different classes of slope, aspect, and elevation were developed from U.S. Geological Survey digital elevation model data. The classes were displayed on clear Mylar at 1:24 000-scale and registered with topographic maps and orthophotos. The maps were used with aerial photographs, topographic maps, and other resource data to determine their value in making order-three soil surveys. They were tested on over 600 000 ha in Wyoming, Idaho, and Nevada under various climatic and topographic conditions. Field evaluations showed that the maps developed from digital elevation model data were accurate, except for slope class maps where slopes were <4%. The maps were useful to soil scientists, especially where (i) class boundaries coincided with soil changes, landform delineations, land use and management separations, and vegetation changes, and (ii) rough terrain and dense vegetation made it difficult to traverse the area. In hot, arid areas of sparse vegetation, the relationship of slope classes to kinds of soil and vegetation was less significant.

Pedological memory in forest soil development

Treesearch

Jonathan D. Phillips; Daniel A. Marion

2004-01-01

Individual trees may have significant impacts on soil morphology. If these impacts are non-random such that some microsites are repeatedly preferentially affected by trees, complex local spatial variability of soils would result. A model of self-reinforcing pedologic influences of trees (SRPIT) is proposed to explain patterns of soil variability in the Ouachita...

Long-term settlement prediction at open dumping area using Hossein and Gabr method for new development

NASA Astrophysics Data System (ADS)

Pauzi, Nur Irfah Mohd; Shariffuddin, Ahmad Sulaimi; Omar, Husaini; Misran, Halina

2017-07-01

In Malaysia, the most common method of disposal is landfill/open dumping. The soil at the dumping area are mixed with waste and soil. Thus, it was called as waste soil. Due to its heterogeneity properties, waste soil has a different settlement rate because different types of waste tends to settle differently. The Hussein and Gabr model which used empirical model was proposed to compute the long-term settlement. This Hussein and Gabr model is one of the soil settlement model that can be used to predict the long-term settlement at the dumping area. The model relates between the compression index and the time factor. The time factor are t1, t2, t3 and t4. The compression index is Cα1=compression index and Cβ is biodegradation index. The duration for initial compression, the compression, the biological compression and time creep are included in the model. The sample of waste soil is taken from closed dumping area in Lukut, Negeri Sembilan with the height of waste approximately 1 to 3 meters. The sample is tested using consolidation test for determining the geotechnical parameters and compressibility index. Based on the Hossein and Gabr model, the predicted long-term settlement for 20 years (ΔH) for the waste height of 1 to 3 meters are 0.21m, 0.42m and 0.63m respectively and are below the percentages of proposed maximum settlement for waste soil which is acceptable for new development to takes place.. The types of deep or shallow foundation are proposed based on the predicted settlement. The abandoned open dumping area can now be reused for the new development after the long-term settlement are predicted and some of the precaution measures has been taken as a safety measures.

Soil fauna: key to new carbon models

NASA Astrophysics Data System (ADS)

Filser, Juliane; Faber, Jack H.; Tiunov, Alexei V.; Brussaard, Lijbert; Frouz, Jan; De Deyn, Gerlinde; Uvarov, Alexei V.; Berg, Matty P.; Lavelle, Patrick; Loreau, Michel; Wall, Diana H.; Querner, Pascal; Eijsackers, Herman; José Jiménez, Juan

2016-11-01

Soil organic matter (SOM) is key to maintaining soil fertility, mitigating climate change, combatting land degradation, and conserving above- and below-ground biodiversity and associated soil processes and ecosystem services. In order to derive management options for maintaining these essential services provided by soils, policy makers depend on robust, predictive models identifying key drivers of SOM dynamics. Existing SOM models and suggested guidelines for future SOM modelling are defined mostly in terms of plant residue quality and input and microbial decomposition, overlooking the significant regulation provided by soil fauna. The fauna controls almost any aspect of organic matter turnover, foremost by regulating the activity and functional composition of soil microorganisms and their physical-chemical connectivity with soil organic matter. We demonstrate a very strong impact of soil animals on carbon turnover, increasing or decreasing it by several dozen percent, sometimes even turning C sinks into C sources or vice versa. This is demonstrated not only for earthworms and other larger invertebrates but also for smaller fauna such as Collembola. We suggest that inclusion of soil animal activities (plant residue consumption and bioturbation altering the formation, depth, hydraulic properties and physical heterogeneity of soils) can fundamentally affect the predictive outcome of SOM models. Understanding direct and indirect impacts of soil fauna on nutrient availability, carbon sequestration, greenhouse gas emissions and plant growth is key to the understanding of SOM dynamics in the context of global carbon cycling models. We argue that explicit consideration of soil fauna is essential to make realistic modelling predictions on SOM dynamics and to detect expected non-linear responses of SOM dynamics to global change. We present a decision framework, to be further developed through the activities of KEYSOM, a European COST Action, for when mechanistic SOM models include soil fauna. The research activities of KEYSOM, such as field experiments and literature reviews, together with dialogue between empiricists and modellers, will inform how this is to be done.

Development of remote sensing techniques capable of delineating soils as an aid to soil survey

NASA Technical Reports Server (NTRS)

Coleman, T. L.; Montgomery, O. L.

1988-01-01

Eighty-one benchmark soils from Alabama, Georgia, Florida, Tennessee, and Mississippi were evaluated to determine the feasibility of spectrally differentiating among soil categories. Relationships among spectral properties that occur between soils and within soils were examined, using discriminant analysis. Soil spectral data were obtained from air-dried samples using an Exotech Model 20C field spectroradiometer (0.37 to 2.36 microns). Differentiating among the orders, suborders, great groups, and subgroups using reflectance spectra achieved varying percentages of accuracy. Six distinct reflectance curve forms were developed from the air-dried samples based on the shape and presence or absence of adsorption bands. Iron oxide and organic matter content were the dominant soil parameters affecting the spectral characteristics for differentiating among and between these soils.

Can next-generation soil data products improve soil moisture modelling at the continental scale? An assessment using a new microclimate package for the R programming environment

NASA Astrophysics Data System (ADS)

Kearney, Michael R.; Maino, James L.

2018-06-01

Accurate models of soil moisture are vital for solving core problems in meteorology, hydrology, agriculture and ecology. The capacity for soil moisture modelling is growing rapidly with the development of high-resolution, continent-scale gridded weather and soil data together with advances in modelling methods. In particular, the GlobalSoilMap.net initiative represents next-generation, depth-specific gridded soil products that may substantially increase soil moisture modelling capacity. Here we present an implementation of Campbell's infiltration and redistribution model within the NicheMapR microclimate modelling package for the R environment, and use it to assess the predictive power provided by the GlobalSoilMap.net product Soil and Landscape Grid of Australia (SLGA, ∼100 m) as well as the coarser resolution global product SoilGrids (SG, ∼250 m). Predictions were tested in detail against 3 years of root-zone (3-75 cm) soil moisture observation data from 35 monitoring sites within the OzNet project in Australia, with additional tests of the finalised modelling approach against cosmic-ray neutron (CosmOz, 0-50 cm, 9 sites from 2011 to 2017) and satellite (ASCAT, 0-2 cm, continent-wide from 2007 to 2009) observations. The model was forced by daily 0.05° (∼5 km) gridded meteorological data. The NicheMapR system predicted soil moisture to within experimental error for all data sets. Using the SLGA or the SG soil database, the OzNet soil moisture could be predicted with a root mean square error (rmse) of ∼0.075 m3 m-3 and a correlation coefficient (r) of 0.65 consistently through the soil profile without any parameter tuning. Soil moisture predictions based on the SLGA and SG datasets were ≈ 17% closer to the observations than when using a chloropleth-derived soil data set (Digital Atlas of Australian Soils), with the greatest improvements occurring for deeper layers. The CosmOz observations were predicted with similar accuracy (r = 0.76 and rmse of ∼0.085 m3 m-3). Comparisons at the continental scale to 0-2 cm satellite data (ASCAT) showed that the SLGA/SG datasets increased model fit over simulations using the DAAS soil properties (r ∼ 0.63 &rmse 15% vs. r 0.48 &rmse 18%, respectively). Overall, our results demonstrate the advantages of using GlobalSoilMap.net products in combination with gridded weather data for modelling soil moisture at fine spatial and temporal resolution at the continental scale.

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/.

Improved Assimilation of Streamflow and Satellite Soil Moisture with the Evolutionary Particle Filter and Geostatistical Modeling

NASA Astrophysics Data System (ADS)

Yan, Hongxiang; Moradkhani, Hamid; Abbaszadeh, Peyman

2017-04-01

Assimilation of satellite soil moisture and streamflow data into hydrologic models using has received increasing attention over the past few years. Currently, these observations are increasingly used to improve the model streamflow and soil moisture predictions. However, the performance of this land data assimilation (DA) system still suffers from two limitations: 1) satellite data scarcity and quality; and 2) particle weight degeneration. In order to overcome these two limitations, we propose two possible solutions in this study. First, the general Gaussian geostatistical approach is proposed to overcome the limitation in the space/time resolution of satellite soil moisture products thus improving their accuracy at uncovered/biased grid cells. Secondly, an evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC, is developed to further reduce weight degeneration and improve the robustness of the land DA system. This study provides a detailed analysis of the joint and separate assimilation of streamflow and satellite soil moisture into a distributed Sacramento Soil Moisture Accounting (SAC-SMA) model, with the use of recently developed EPF-MCMC and the general Gaussian geostatistical approach. Performance is assessed over several basins in the USA selected from Model Parameter Estimation Experiment (MOPEX) and located in different climate regions. The results indicate that: 1) the general Gaussian approach can predict the soil moisture at uncovered grid cells within the expected satellite data quality threshold; 2) assimilation of satellite soil moisture inferred from the general Gaussian model can significantly improve the soil moisture predictions; and 3) in terms of both deterministic and probabilistic measures, the EPF-MCMC can achieve better streamflow predictions. These results recommend that the geostatistical model is a helpful tool to aid the remote sensing technique and the EPF-MCMC is a reliable and effective DA approach in hydrologic applications.

Modeling the hysteretic moisture and temperature responses of soil carbon decomposition resulting from organo-mineral interactions

NASA Astrophysics Data System (ADS)

Tang, J.; Riley, W. J.

2017-12-01

Most existing soil carbon cycle models have modeled the moisture and temperature dependence of soil respiration using deterministic response functions. However, empirical data suggest abundant variability in both of these dependencies. We here use the recently developed SUPECA (Synthesizing Unit and Equilibrium Chemistry Approximation) theory and a published dynamic energy budget based microbial model to investigate how soil carbon decomposition responds to changes in soil moisture and temperature under the influence of organo-mineral interactions. We found that both the temperature and moisture responses are hysteretic and cannot be represented by deterministic functions. We then evaluate how the multi-scale variability in temperature and moisture forcing affect soil carbon decomposition. Our results indicate that when the model is run in scenarios mimicking laboratory incubation experiments, the often-observed temperature and moisture response functions can be well reproduced. However, when such response functions are used for model extrapolation involving more transient variability in temperature and moisture forcing (as found in real ecosystems), the dynamic model that explicitly accounts for hysteresis in temperature and moisture dependency produces significantly different estimations of soil carbon decomposition, suggesting there are large biases in models that do not resolve such hysteresis. We call for more studies on organo-mineral interactions to improve modeling of such hysteresis.

Mapping soil total nitrogen of cultivated land at county scale by using hyperspectral image

NASA Astrophysics Data System (ADS)

Gu, Xiaohe; Zhang, Li Yan; Shu, Meiyan; Yang, Guijun

2018-02-01

Monitoring total nitrogen content (TNC) in the soil of cultivated land quantitively and mastering its spatial distribution are helpful for crop growing, soil fertility adjustment and sustainable development of agriculture. The study aimed to develop a universal method to map total nitrogen content in soil of cultivated land by HSI image at county scale. Several mathematical transformations were used to improve the expression ability of HSI image. The correlations between soil TNC and the reflectivity and its mathematical transformations were analyzed. Then the susceptible bands and its transformations were screened to develop the optimizing model of map soil TNC in the Anping County based on the method of multiple linear regression. Results showed that the bands of 14th, 16th, 19th, 37th and 60th with different mathematical transformations were screened as susceptible bands. Differential transformation was helpful for reducing the noise interference to the diagnosis ability of the target spectrum. The determination coefficient of the first order differential of logarithmic transformation was biggest (0.505), while the RMSE was lowest. The study confirmed the first order differential of logarithm transformation as the optimal inversion model for soil TNC, which was used to map soil TNC of cultivated land in the study area.

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.

Evaluation of scour potential of cohesive soils : final report, August 2009.

DOT National Transportation Integrated Search

2009-08-01

Prediction of scour at bridge river crossings is an evolving process. Hydraulic models to estimate water velocity and, therefore, the shear stresses that erode soil are reasonably well developed. The weak link remains methods for estimating soil erod...

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.

Meta-modeling soil organic carbon sequestration potential and its application at regional scale.

PubMed

Luo, Zhongkui; Wang, Enli; Bryan, Brett A; King, Darran; Zhao, Gang; Pan, Xubin; Bende-Michl, Ulrike

2013-03-01

Upscaling the results from process-based soil-plant models to assess regional soil organic carbon (SOC) change and sequestration potential is a great challenge due to the lack of detailed spatial information, particularly soil properties. Meta-modeling can be used to simplify and summarize process-based models and significantly reduce the demand for input data and thus could be easily applied on regional scales. We used the pre-validated Agricultural Production Systems sIMulator (APSIM) to simulate the impact of climate, soil, and management on SOC at 613 reference sites across Australia's cereal-growing regions under a continuous wheat system. We then developed a simple meta-model to link the APSIM-modeled SOC change to primary drivers, i.e., the amount of recalcitrant SOC, plant available water capacity of soil, soil pH, and solar radiation, temperature, and rainfall in the growing season. Based on high-resolution soil texture data and 8165 climate data points across the study area, we used the meta-model to assess SOC sequestration potential and the uncertainty associated with the variability of soil characteristics. The meta-model explained 74% of the variation of final SOC content as simulated by APSIM. Applying the meta-model to Australia's cereal-growing regions reveals regional patterns in SOC, with higher SOC stock in cool, wet regions. Overall, the potential SOC stock ranged from 21.14 to 152.71 Mg/ha with a mean of 52.18 Mg/ha. Variation of soil properties induced uncertainty ranging from 12% to 117% with higher uncertainty in warm, wet regions. In general, soils in Australia's cereal-growing regions under continuous wheat production were simulated as a sink of atmospheric carbon dioxide with a mean sequestration potential of 8.17 Mg/ha.

Representing life in the Earth system with soil microbial functional traits in the MIMICS model

NASA Astrophysics Data System (ADS)

Wieder, W. R.; Grandy, A. S.; Kallenbach, C. M.; Taylor, P. G.; Bonan, G. B.

2015-06-01

Projecting biogeochemical responses to global environmental change requires multi-scaled perspectives that consider organismal diversity, ecosystem processes, and global fluxes. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon (C) cycle-climate feedbacks. We used a microbial trait-based soil C model with two physiologically distinct microbial communities, and evaluate how this model represents soil C storage and response to perturbations. Drawing from the application of functional traits used to model other ecosystems, we incorporate copiotrophic and oligotrophic microbial functional groups in the MIcrobial-MIneral Carbon Stabilization (MIMICS) model; these functional groups are akin to "gleaner" vs. "opportunist" plankton in the ocean, or r- vs. K-strategists in plant and animal communities. Here we compare MIMICS to a conventional soil C model, DAYCENT (the daily time-step version of the CENTURY model), in cross-site comparisons of nitrogen (N) enrichment effects on soil C dynamics. MIMICS more accurately simulates C responses to N enrichment; moreover, it raises important hypotheses involving the roles of substrate availability, community-level enzyme induction, and microbial physiological responses in explaining various soil biogeochemical responses to N enrichment. In global-scale analyses, we show that MIMICS projects much slower rates of soil C accumulation than a conventional soil biogeochemistry in response to increasing C inputs with elevated carbon dioxide (CO2) - a finding that would reduce the size of the land C sink estimated by the Earth system. Our findings illustrate that tradeoffs between theory and utility can be overcome to develop soil biogeochemistry models that evaluate and advance our theoretical understanding of microbial dynamics and soil biogeochemical responses to environmental change.

Quantification of the impact of hydrology on agricultural production as a result of too dry, too wet or too saline conditions

NASA Astrophysics Data System (ADS)

Hack-ten Broeke, Mirjam J. D.; Kroes, Joop G.; Bartholomeus, Ruud P.; van Dam, Jos C.; de Wit, Allard J. W.; Supit, Iwan; Walvoort, Dennis J. J.; van Bakel, P. Jan T.; Ruijtenberg, Rob

2016-08-01

For calculating the effects of hydrological measures on agricultural production in the Netherlands a new comprehensive and climate proof method is being developed: WaterVision Agriculture (in Dutch: Waterwijzer Landbouw). End users have asked for a method that considers current and future climate, that can quantify the differences between years and also the effects of extreme weather events. Furthermore they would like a method that considers current farm management and that can distinguish three different causes of crop yield reduction: drought, saline conditions or too wet conditions causing oxygen shortage in the root zone. WaterVision Agriculture is based on the hydrological simulation model SWAP and the crop growth model WOFOST. SWAP simulates water transport in the unsaturated zone using meteorological data, boundary conditions (like groundwater level or drainage) and soil parameters. WOFOST simulates crop growth as a function of meteorological conditions and crop parameters. Using the combination of these process-based models we have derived a meta-model, i.e. a set of easily applicable simplified relations for assessing crop growth as a function of soil type and groundwater level. These relations are based on multiple model runs for at least 72 soil units and the possible groundwater regimes in the Netherlands. So far, we parameterized the model for the crops silage maize and grassland. For the assessment, the soil characteristics (soil water retention and hydraulic conductivity) are very important input parameters for all soil layers of these 72 soil units. These 72 soil units cover all soils in the Netherlands. This paper describes (i) the setup and examples of application of the process-based model SWAP-WOFOST, (ii) the development of the simplified relations based on this model and (iii) how WaterVision Agriculture can be used by farmers, regional government, water boards and others to assess crop yield reduction as a function of groundwater characteristics or as a function of the salt concentration in the root zone for the various soil types.

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

Physical root-soil interactions

NASA Astrophysics Data System (ADS)

Kolb, Evelyne; Legué, Valérie; Bogeat-Triboulot, Marie-Béatrice

2017-12-01

Plant root system development is highly modulated by the physical properties of the soil and especially by its mechanical resistance to penetration. The interplay between the mechanical stresses exerted by the soil and root growth is of particular interest for many communities, in agronomy and soil science as well as in biomechanics and plant morphogenesis. In contrast to aerial organs, roots apices must exert a growth pressure to penetrate strong soils and reorient their growth trajectory to cope with obstacles like stones or hardpans or to follow the tortuous paths of the soil porosity. In this review, we present the main macroscopic investigations of soil-root physical interactions in the field and combine them with simple mechanistic modeling derived from model experiments at the scale of the individual root apex.

Physical root-soil interactions.

PubMed

Kolb, Evelyne; Legué, Valérie; Bogeat-Triboulot, Marie-Béatrice

2017-11-16

Plant root system development is highly modulated by the physical properties of the soil and especially by its mechanical resistance to penetration. The interplay between the mechanical stresses exerted by the soil and root growth is of particular interest for many communities, in agronomy and soil science as well as in biomechanics and plant morphogenesis. In contrast to aerial organs, roots apices must exert a growth pressure to penetrate strong soils and reorient their growth trajectory to cope with obstacles like stones or hardpans or to follow the tortuous paths of the soil porosity. In this review, we present the main macroscopic investigations of soil-root physical interactions in the field and combine them with simple mechanistic modeling derived from model experiments at the scale of the individual root apex.

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.

Spatially distributed modelling of pesticide leaching at European scale with the PyCatch modelling framework

NASA Astrophysics Data System (ADS)

Schmitz, Oliver; van der Perk, Marcel; Karssenberg, Derek; Häring, Tim; Jene, Bernhard

2017-04-01

The modelling of pesticide transport through the soil and estimating its leaching to groundwater is essential for an appropriate environmental risk assessment. Pesticide leaching models commonly used in regulatory processes often lack the capability of providing a comprehensive spatial view, as they are implemented as non-spatial point models or only use a few combinations of representative soils to simulate specific plots. Furthermore, their handling of spatial input and output data and interaction with available Geographical Information Systems tools is limited. Therefore, executing several scenarios simulating and assessing the potential leaching on national or continental scale at high resolution is rather inefficient and prohibits the straightforward identification of areas prone to leaching. We present a new pesticide leaching model component of the PyCatch framework developed in PCRaster Python, an environmental modelling framework tailored to the development of spatio-temporal models (http://www.pcraster.eu). To ensure a feasible computational runtime of large scale models, we implemented an elementary field capacity approach to model soil water. Currently implemented processes are evapotranspiration, advection, dispersion, sorption, degradation and metabolite transformation. Not yet implemented relevant additional processes such as surface runoff, snowmelt, erosion or other lateral flows can be integrated with components already implemented in PyCatch. A preliminary version of the model executes a 20-year simulation of soil water processes for Germany (20 soil layers, 1 km2 spatial resolution, and daily timestep) within half a day using a single CPU. A comparison of the soil moisture and outflow obtained from the PCRaster implementation and PELMO, a commonly used pesticide leaching model, resulted in an R2 of 0.98 for the FOCUS Hamburg scenario. We will further discuss the validation of the pesticide transport processes and show case studies applied to European countries.

From Process Understanding Via Soil Functions to Sustainable Soil Management - A Systemic Approach

NASA Astrophysics Data System (ADS)

Wollschlaeger, U.; Bartke, S.; Bartkowski, B.; Daedlow, K.; Helming, K.; Kogel-Knabner, I.; Lang, B.; Rabot, E.; Russell, D.; Stößel, B.; Weller, U.; Wiesmeier, M.; Rabot, E.; Vogel, H. J.

2017-12-01

Fertile soils are central resources for the production of biomass and the 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 requires 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: 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 that are not yet sufficiently 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. Hence, a solid and integrated assessment of soil quality requires the consideration of the ensemble of soil functions and its relation to soil management to finally be able to develop site-specific options for sustainable soil management. We present an integrated modeling approach that investigates the influence of soil management on the ensemble of soil functions. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. As the evidence base required for feeding the model is for the most part stored in the existing scientific literature, another central component of our work is to set up a public "knowledge-portal" providing the infrastructure for a community effort towards a comprehensive knowledge base on soil processes as a basis for model developments. The connection to the socio-economic system is established using the Drivers-Pressures-Impacts-States-Responses (DPSIR) framework where our improved understanding about soil ecosystem processes is linked to ecosystem services and resource efficiency via the soil functions.

The activation energy of stabilised/solidified contaminated soils.

PubMed

Chitambira, B; Al-Tabbaa, A; Perera, A S R; Yu, X D

2007-03-15

Developing an understanding of the time-related performance of cement-treated materials is essential in understanding their durability and long-term effectiveness. A number of models have been developed to predict this time-related performance. One such model is the maturity concept which involves use of the 'global' activation energy which derives from the Arrhenius equation. The accurate assessment of the activation energy is essential in the realistic modelling of the accelerated ageing of cement-treated soils. Experimentally, this model is applied to a series of tests performed at different elevated temperatures. Experimental work, related to the results of a time-related performance on a contaminated site in the UK treated with in situ stabilisation/solidification was carried out. Three different cement-based grouts were used on two model site soils which were both contaminated with a number of heavy metals and a hydrocarbon. Uncontaminated soils were also tested. Elevated temperatures up to 60 degrees C and curing periods up to 90 days were used. The resulting global activation energies for the uncontaminated and contaminated soils were compared. Lower values were obtained for the contaminated soils reflecting the effect of the contaminants. The resulting equivalent ages for the uncontaminated and contaminated mixes tested were 5.1-7.4 and 0.8-4.1 years, respectively. This work shows how a specific set of contaminants affect the E(a) values for particular cementitious systems and how the maturity concept can be applied to cement-treated contaminated soils.

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.

Assessing soil fluxes using meteoric 10Be: development and application of the Be2D model

NASA Astrophysics Data System (ADS)

Campforts, Benjamin; Govers, Gerard; Vanacker, Veerle; Baken, Stijn; Smolders, Erik; Vanderborght, Jan

2015-04-01

Meteoric 10Be is a promising and increasingly popular tool to better understand soil fluxes at different timescales. Unlike other, more classical, methods such as the study of sedimentary archives it enables a direct coupling between eroding and deposition sites. However, meteoric 10Be can be mobilized within the soil. Therefore, spatial variations in meteoric 10Be inventories cannot directly be translated into spatial variations in erosion and sedimentation rates: a correct interpretation of measured 10Be inventories requires that both lateral and vertical movement of meteoric 10Be are accounted for. Here, we present a spatially explicit 2D model that allows to simulate the behaviour of meteoric 10Be in the soil system over timescales of up to 1 million year and use the model to investigate the impact of accelerated erosion on meteoric 10Be inventories. The model consists of two parts. A first component deals with advective and diffusive mobility within the soil profile, whereas a second component describes lateral soil (and meteoric 10Be) fluxes over the hillslope. Soil depth is calculated dynamically, accounting for soil production through weathering and lateral soil fluxes. Different types of erosion such as creep, water and tillage erosion are supported. Model runs show that natural soil fluxes can be well reconstructed based on meteoric 10Be inventories, and this for a wide range of geomorphological and pedological conditions. However, extracting signals of human impact and distinguishing them from natural soil fluxes is only feasible when the soil has a rather high retention capacity so that meteoric 10Be is retained in the top soil layer. Application of the Be2D model to an existing data set in the Appalachian Mountains [West et al.,2013] using realistic parameter values for the soil retention capacity as well as for vertical advection resulted in a good agreement between simulated and observed 10Be inventories. This confirms the robustness of the model. We therefore conclude that the Be2D model is a useful tool to develop more solid and quantitative interpretations of the spatial variation of meteoric 10Be inventories in eroding landscapes. West, N., E. Kirby, P. Bierman, R. Slingerland, L. Ma, D. Rood, and S. Brantley (2013), Regolith production and transport at the Susquehanna Shale Hills Critical Zone Observatory, Part 2: Insights from meteoric 10 Be, J. Geophys. Res. Earth Surf., 118(3), 1877-1896.

Use of midlatitude soil moisture and meteorological observations to validate soil moisture simulations with biosphere and bucket models

NASA Technical Reports Server (NTRS)

Robock, Alan; Vinnikov, Konstantin YA.; Schlosser, C. Adam; Speranskaya, Nina A.; Xue, Yongkang

1995-01-01

Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally 'ground truth,' snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring -- SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible heat fluxes, which would have large effects on GCM simulations.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model

NASA Astrophysics Data System (ADS)

Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo

2017-04-01

Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).

Critical Zone Experimental Design to Assess Soil Processes and Function

NASA Astrophysics Data System (ADS)

Banwart, Steve

2010-05-01

Through unsustainable land use practices, mining, deforestation, urbanisation and degradation by industrial pollution, soil losses are now hypothesized to be much faster (100 times or more) than soil formation - with the consequence that soil has become a finite resource. The crucial challenge for the international research community is to understand the rates of processes that dictate soil mass stocks and their function within Earth's Critical Zone (CZ). The CZ is the environment where soils are formed, degrade and provide their essential ecosystem services. Key among these ecosystem services are food and fibre production, filtering, buffering and transformation of water, nutrients and contaminants, storage of carbon and maintaining biological habitat and genetic diversity. We have initiated a new research project to address the priority research areas identified in the European Union Soil Thematic Strategy and to contribute to the development of a global network of Critical Zone Observatories (CZO) committed to soil research. Our hypothesis is that the combined physical-chemical-biological structure of soil can be assessed from first-principles and the resulting soil functions can be quantified in process models that couple the formation and loss of soil stocks with descriptions of biodiversity and nutrient dynamics. The objectives of this research are to 1. Describe from 1st principles how soil structure influences processes and functions of soils, 2. Establish 4 European Critical Zone Observatories to link with established CZOs, 3. Develop a CZ Integrated Model of soil processes and function, 4. Create a GIS-based modelling framework to assess soil threats and mitigation at EU scale, 5. Quantify impacts of changing land use, climate and biodiversity on soil function and its value and 6. Form with international partners a global network of CZOs for soil research and deliver a programme of public outreach and research transfer on soil sustainability. The experimental design studies soil processes across the temporal evolution of the soil profile, from its formation on bare bedrock, through managed use as productive land to its degradation under longstanding pressures from intensive land use. To understand this conceptual life cycle of soil, we have selected 4 European field sites as Critical Zone Observatories. These are to provide data sets of soil parameters, processes and functions which will be incorporated into the mathematical models. The field sites are 1) the BigLink field station which is located in the chronosequence of the Damma Glacier forefield in alpine Switzerland and is established to study the initial stages of soil development on bedrock; 2) the Lysina Catchment in the Czech Republic which is representative of productive soils managed for intensive forestry, 3) the Fuchsenbigl Field Station in Austria which is an agricultural research site that is representative of productive soils managed as arable land and 4) the Koiliaris Catchment in Crete, Greece which represents degraded Mediterranean region soils, heavily impacted by centuries of intensive grazing and farming, under severe risk of desertification.

Using causal loop diagrams for the initialization of stakeholder engagement in soil salinity management in agricultural watersheds in developing countries: a case study in the Rechna Doab watershed, Pakistan.

PubMed

Inam, Azhar; Adamowski, Jan; Halbe, Johannes; Prasher, Shiv

2015-04-01

Over the course of the last twenty years, participatory modeling has increasingly been advocated as an integral component of integrated, adaptive, and collaborative water resources management. However, issues of high cost, time, and expertise are significant hurdles to the widespread adoption of participatory modeling in many developing countries. In this study, a step-wise method to initialize the involvement of key stakeholders in the development of qualitative system dynamics models (i.e. causal loop diagrams) is presented. The proposed approach is designed to overcome the challenges of low expertise, time and financial resources that have hampered previous participatory modeling efforts in developing countries. The methodological framework was applied in a case study of soil salinity management in the Rechna Doab region of Pakistan, with a focus on the application of qualitative modeling through stakeholder-built causal loop diagrams to address soil salinity problems in the basin. Individual causal loop diagrams were developed by key stakeholder groups, following which an overall group causal loop diagram of the entire system was built based on the individual causal loop diagrams to form a holistic qualitative model of the whole system. The case study demonstrates the usefulness of the proposed approach, based on using causal loop diagrams in initiating stakeholder involvement in the participatory model building process. In addition, the results point to social-economic aspects of soil salinity that have not been considered by other modeling studies to date. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

NASA Technical Reports Server (NTRS)

Entekhabi, D.; Eagleson, P. S.

1989-01-01

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

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.

Comparison of two methods for calculating the P sorption capacity parameter in soils

USDA-ARS?s Scientific Manuscript database

Phosphorus (P) cycling in soils is an important process affecting P movement through the landscape. The P cycling routines in many computer models are based on the relationships developed for the EPIC model. An important parameter required for this model is the P sorption capacity parameter (PSP). I...

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.

Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX-GHG

DOE PAGES

Wang, Kefeng; Peng, Changhui; Zhu, Qiuan; ...

2017-09-28

Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process-based model TRIPLEX-GHG was developed by coupling it with the new MEND (Microbial-ENzyme-mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX-MICROBE) shows considerable improvement over the previous version (TRIPLEX-GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195more » Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well-regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated. We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC) and mineral-associated organic carbon (MOC). Furthermore, our work represents the first step towards a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles.« less

Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX-GHG

NASA Astrophysics Data System (ADS)

Wang, Kefeng; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Wang, Meng; Zhang, Kerou; Wang, Gangsheng

2017-10-01

Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process-based model TRIPLEX-GHG was developed by coupling it with the new MEND (Microbial-ENzyme-mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX-MICROBE) shows considerable improvement over the previous version (TRIPLEX-GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195 Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well-regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated by Xu et al. (2014). We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC), and mineral-associated organic carbon (MOC). However, our work represents the first step toward a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles.

Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX-GHG

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

Wang, Kefeng; Peng, Changhui; Zhu, Qiuan

Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process-based model TRIPLEX-GHG was developed by coupling it with the new MEND (Microbial-ENzyme-mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX-MICROBE) shows considerable improvement over the previous version (TRIPLEX-GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195more » Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well-regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated. We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC) and mineral-associated organic carbon (MOC). Furthermore, our work represents the first step towards a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles.« less

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.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.

PubMed

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert

PubMed Central

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203

Modeling the Impact of Soil Conditions on Global Water Balance

NASA Astrophysics Data System (ADS)

Wang, P. L.; Feddema, J. J.

2016-12-01

The amount of water the soil can hold for plant use, defined as soil water-holding capacity (WHC), has a large influence on the water cycle and climatic variables. Although soil properties vary widely worldwide, many climate modeling applications assume WHC to be spatially invariant. This study explores how a more realistic soil WHC estimate affects the global water balance relative to commonly assumed soil properties. We use a modified Thornthwaite water balance model combined with a newly developed soil WHC and soil thickness data at a 30 arc second resolution. The soil WHC data was obtained by integrating WHCs to a depth of 2 m and modified by the soil thickness data on a grid-by-grid basis, and then resampling to the 0.5 degree climatology data. We observed that down scaling soils data before modifying soil depths greatly increases global soil WHCs. This new dataset is compared to WHC information with a fixed 2-m soil depth, and a constant 150-mm soil WHC. Results indicate higher soil WHC results in increased soil moisture, decreased moisture surplus and deficits, and increased actual evapotranspiration (AE), and vice-versa. However, due to high variability in soil characteristics across climate gradients, this generalization does not hold true for regionally averaged outcomes. Compared to using a constant 150-mm WHC, more realistic soil WHC increases global averaged AE 1%, and decreases deficit 2% and surplus 3%. Most change is observed in areas with pronounced wet and dry seasons; using a constant 2-m soil depth doubles the differences. Regionally, Europe was most affected: AE increases 4%, and the deficit and surplus decrease 20% and 12%. Australia shows that regionally averaged results are not equivocal for moisture surplus and deficit; deficit decreases 0.4%, while surplus decreases 9%. This research highlights the importance of soil condition for climate modeling and how a better representation of soil moisture conditions affects global water balance modeling.

Quantification of the inevitable: the influence of soil macrofauna on soil water movement in rehabilitated open-cut mine land

NASA Astrophysics Data System (ADS)

Arnold, S.; Williams, E. R.

2015-08-01

Recolonisation of soil by macrofauna (especially ants and termites) in rehabilitated open-cut mine sites is inevitable. In these highly disturbed landscapes, soil invertebrates play a major role in soil development (macropore configuration, nutrient cycling, bioturbation, etc.) and can influence hydrological processes such as infiltration and seepage. Understanding and quantifying these ecosystem processes is important in rehabilitation design, establishment and subsequent management to ensure progress to the desired end-goal, especially in waste cover systems designed to prevent water reaching and transporting underlying hazardous waste materials. However, soil macrofauna are typically overlooked during hydrological modelling, possibly due to uncertainties on the extent of their influence, which can lead to failure of waste cover systems or rehabilitation activities. We propose that scientific experiments under controlled conditions are required to quantify (i) macrofauna - soil structure interactions, (ii) functional dynamics of macrofauna taxa, and (iii) their effects on macrofauna and soil development over time. Such knowledge would provide crucial information for soil water models, which would increase confidence in mine waste cover design recommendations and eventually lead to higher likelihood of rehabilitation success of open-cut mining land.

Modeling Anaerobic Soil Organic Carbon Decomposition in Arctic Polygon Tundra: Insights into Soil Geochemical Influences on Carbon Mineralization: Modeling Archive

DOE Data Explorer

Zheng, Jianqiu; Thornton, Peter; Painter, Scott; Gu, Baohua; Wullschleger, Stan; Graham, David

2018-06-13

This anaerobic carbon decomposition model is developed with explicit representation of fermentation, methanogenesis and iron reduction by combining three well-known modeling approaches developed in different disciplines. A pool-based model to represent upstream carbon transformations and replenishment of DOC pool, a thermodynamically-based model to calculate rate kinetics and biomass growth for methanogenesis and Fe(III) reduction, and a humic ion-binding model for aqueous phase speciation and pH calculation are implemented into the open source geochemical model PHREEQC (V3.0). Installation of PHREEQC is required to run this model.

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.

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

NASA Technical Reports Server (NTRS)

Salvucci, Guido D.

2000-01-01

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

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

NASA Technical Reports Server (NTRS)

Salvucci, Guido D.

1997-01-01

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

An approach for modeling the influence of wheel tractor loads and vibration frequencies on soil compaction

NASA Astrophysics Data System (ADS)

Verotti, M.; Servadio, P.; Belfiore, N. P.; Bergonzoli, S.

2012-04-01

Both soil compaction and ground vibration are forms of environmental degradation that may be understood in the context of the vehicle-soil interaction process considered (Hildebrand et al., 2008). The transit of tractors on agricultural soil is often the main cause of soil compaction increasing. As known, this can be a serious problems for tillage and sowing and therefore the influence of all the affecting factors have been extensively studied in the last decades in order to understand their impact on the biosystem. There are factors related to the climate, namely to the rainfalls and temperature, and many others. Hence, it is not simple to figure out a complete model for predicting an index of compaction, for a given situation. Soil compaction models are important tools for controlling soil compaction due to agricultural field traffic and they are potentially useful technique to provide information concerning correct soil management. By means of such models, strategies and recommendations for prevention of soil compaction may be developed and specific advice may be given to farmers and advisers. In order to predict field wheeled and tracked vehicle performance, some empirical methods, used for off-road vehicle, were applied by Servadio (2010) on agricultural soil. The empirical indexes included, besides the soil strength, the load carried by the tire or track, some technical characteristics of the tire or track of the vehicle (tire or track width, tire or track wheel diameter, unloaded tire section height, number of wheel station in one track, tire deflection, total length of the belt track, the track pitch) as well as the vehicle passes. They have been validated with the tests results of agricultural vehicles over a range of soil in central Italy. Among the parameters which affect soil compaction, the water content of the soil, the axle load and number of vehicle passes proved to be the most important ones. The present paper concerns mainly vehicle-soil-man interaction. In particular, a model based on elasto-visco-plastic concentrated parameters, with multiple degrees of freedom, will be used in order to build a method for detecting a soil damage index, especially expressed in terms of increasing of soil compaction. Besides the axle load, the model will take into account the frequency of the vibrations that the vehicle is transmitting to the soil. Such model expresses a numerical value for the transmissibility coefficient and also allows evaluating the damage at the surface and on the bulk medium where the agricultural crops initially develop. Key words: vehicle-soil interaction, vibration, compaction, models. Acknowledgements This work was carried out under the auspices of the special project "Sceneries of adaptation of the Italian agriculture to the climatic changes" (AGROSCENARI) of the Agricultural Research Council, and Italian Ministry of the Agricultural and Forestry Politics.

STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

NASA Astrophysics Data System (ADS)

Or, D.; von Ruette, J.; Lehmann, P.

2017-12-01

Landslides and subsequent debris-flows initiated by rainfall represent a common natural hazard in mountainous regions. We integrated a landslide hydro-mechanical triggering model with a simple model for debris flow runout pathways and developed a graphical user interface (GUI) to represent these natural hazards at catchment scale at any location. The STEP-TRAMM GUI provides process-based estimates of the initiation locations and sizes of landslides patterns based on digital elevation models (SRTM) linked with high resolution global soil maps (SoilGrids 250 m resolution) and satellite based information on rainfall statistics for the selected region. In the preprocessing phase the STEP-TRAMM model estimates soil depth distribution to supplement other soil information for delineating key hydrological and mechanical properties relevant to representing local soil failure. We will illustrate this publicly available GUI and modeling platform to simulate effects of deforestation on landslide hazards in several regions and compare model outcome with satellite based information.

Predicting Ascospore Release of Monilinia vaccinii-corymbosi of Blueberry with Machine Learning.

PubMed

Harteveld, Dalphy O C; Grant, Michael R; Pscheidt, Jay W; Peever, Tobin L

2017-11-01

Mummy berry, caused by Monilinia vaccinii-corymbosi, causes economic losses of highbush blueberry in the U.S. Pacific Northwest (PNW). Apothecia develop from mummified berries overwintering on soil surfaces and produce ascospores that infect tissue emerging from floral and vegetative buds. Disease control currently relies on fungicides applied on a calendar basis rather than inoculum availability. To establish a prediction model for ascospore release, apothecial development was tracked in three fields, one in western Oregon and two in northwestern Washington in 2015 and 2016. Air and soil temperature, precipitation, soil moisture, leaf wetness, relative humidity and solar radiation were monitored using in-field weather stations and Washington State University's AgWeatherNet stations. Four modeling approaches were compared: logistic regression, multivariate adaptive regression splines, artificial neural networks, and random forest. A supervised learning approach was used to train the models on two data sets: training (70%) and testing (30%). The importance of environmental factors was calculated for each model separately. Soil temperature, soil moisture, and solar radiation were identified as the most important factors influencing ascospore release. Random forest models, with 78% accuracy, showed the best performance compared with the other models. Results of this research helps PNW blueberry growers to optimize fungicide use and reduce production costs.

A Geochemical Reaction Model for Titration of Contaminated Soil and Groundwater at the Oak Ridge Reservation

NASA Astrophysics Data System (ADS)

Zhang, F.; Parker, J. C.; Gu, B.; Luo, W.; Brooks, S. C.; Spalding, B. P.; Jardine, P. M.; Watson, D. B.

2007-12-01

This study investigates geochemical reactions during titration of contaminated soil and groundwater at the Oak Ridge Reservation in eastern Tennessee. The soils and groundwater exhibits low pH and high concentrations of aluminum, calcium, magnesium, manganese, various trace metals such as nickel and cobalt, and radionuclides such as uranium and technetium. The mobility of many of the contaminant species diminishes with increasing pH. However, base additions to increase pH are strongly buffered by various precipitation/dissolution and adsorption/desorption reactions. The ability to predict acid-base behavior and associated geochemical effects is thus critical to evaluate remediation performance of pH manipulation strategies. This study was undertaken to develop a practical but generally applicable geochemical model to predict aqueous and solid-phase speciation during soil and groundwater titration. To model titration in the presence of aquifer solids, an approach proposed by Spalding and Spalding (2001) was utilized, which treats aquifer solids as a polyprotic acid. Previous studies have shown that Fe and Al-oxyhydroxides strongly sorb dissolved Ni, U and Tc species. In this study, since the total Fe concentration is much smaller than that of Al, only ion exchange reactions associated with Al hydroxides are considered. An equilibrium reaction model that includes aqueous complexation, precipitation, ion exchange, and soil buffering reactions was developed and implemented in the code HydroGeoChem 5.0 (HGC5). Comparison of model results with experimental titration curves for contaminated groundwater alone and for soil- water systems indicated close agreement. This study is expected to facilitate field-scale modeling of geochemical processes under conditions with highly variable pH to develop practical methods to control contaminant mobility at geochemically complex sites.

SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems

NASA Astrophysics Data System (ADS)

Bradley, J. A.; Anesio, A. M.; Singarayer, J. S.; Heath, M. R.; Arndt, S.

2015-08-01

SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework which is developed as part of an interdisciplinary, iterative, model-data based approach fully integrating fieldwork and laboratory experiments with model development, testing, and application. SHIMMER is designed to simulate the establishment of microbial biomass and associated biogeochemical cycling during the initial stages of ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The model mechanistically describes and predicts transformations in carbon, nitrogen and phosphorus through aggregated components of the microbial community as a set of coupled ordinary differential equations. The rationale for development of the model arises from decades of empirical observation on the initial stages of soil development in glacier forefields. SHIMMER enables a quantitative and process focussed approach to synthesising the existing empirical data and advancing understanding of microbial and biogeochemical dynamics. Here, we provide a detailed description of SHIMMER. The performance of SHIMMER is then tested in two case studies using published data from the Damma Glacier forefield in Switzerland and the Athabasca Glacier in Canada. In addition, a sensitivity analysis helps identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass, and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Simulation results indicate that primary production is responsible for the initial build-up of substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter are identified as important in sustaining this productivity. Microbial production in young soils is supported by labile organic matter, whereas carbon stocks in older soils are more refractory. Nitrogen fixing bacteria are responsible for the initial accumulation of available nitrates in the soil. Biogeochemical rates are highly seasonal, as observed in experimental data. The development and application of SHIMMER not only provides important new insights into forefield dynamics, but also highlights aspects of these systems that require further field and laboratory research. The most pressing advances need to come in quantifying nutrient budgets and biogeochemical rates, in exploring seasonality, the fate of allochthonous deposition in relation to autochthonous production, and empirical studies of microbial growth and cell death, to increase understanding of how glacier forefield development contributes to the global biogeochemical cycling and climate in the future.

Modeling soil heating and moisture transport under extreme conditions: Forest fires and slash pile burns

NASA Astrophysics Data System (ADS)

Massman, W. J.

2012-10-01

Heating any soil during a sufficiently intense wildfire or prescribed burn can alter it irreversibly, causing many significant, long-term biological, chemical, and hydrological effects. Given the climate-change-driven increasing probability of wildfires and the increasing use of prescribed burns by land managers, it is important to better understand the dynamics of the coupled heat and moisture transport in soil during these extreme heating events. Furthermore, improved understanding and modeling of heat and mass transport during extreme conditions should provide insights into the associated transport mechanisms under more normal conditions. The present study describes a numerical model developed to simulate soil heat and moisture transport during fires where the surface heating often ranges between 10,000 and 100,000 W m-2 for several minutes to several hours. Basically, the model extends methods commonly used to model coupled heat flow and moisture evaporation at ambient conditions into regions of extreme dryness and heat. But it also incorporates some infrequently used formulations for temperature dependencies of the soil specific heat, thermal conductivity, and the water retention curve, as well as advective effects due to the large changes in volume that occur when liquid water is rapidly volatilized. Model performance is tested against laboratory measurements of soil temperature and moisture changes at several depths during controlled heating events. Qualitatively, the model agrees with the laboratory observations, namely, it simulates an increase in soil moisture ahead of the drying front (due to the condensation of evaporated soil water at the front) and a hiatus in the soil temperature rise during the strongly evaporative stage of the soil drying. Nevertheless, it is shown that the model is incapable of producing a physically realistic solution because it does not (and, in fact, cannot) represent the relationship between soil water potential and soil moisture at extremely low soil moisture contents (i.e., residual or bound water: θ < 0.01 m3 m-3, for example). Diagnosing the model's performance yields important insights into how to make progress on modeling soil evaporation and heating under conditions of high temperatures and very low soil moisture content.

Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint

NASA Technical Reports Server (NTRS)

Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian

2011-01-01

Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

The implications of microbial and substrate limitation for the fates of carbon in different organic soil horizon types of boreal forest ecosystems: a mechanistically based model analysis

USGS Publications Warehouse

He, Y.; Zhuang, Q.; Harden, Jennifer W.; McGuire, A. David; Fan, Z.; Liu, Y.; Wickland, Kimberly P.

2014-01-01

The large amount of soil carbon in boreal forest ecosystems has the potential to influence the climate system if released in large quantities in response to warming. Thus, there is a need to better understand and represent the environmental sensitivity of soil carbon decomposition. Most soil carbon decomposition models rely on empirical relationships omitting key biogeochemical mechanisms and their response to climate change is highly uncertain. In this study, we developed a multi-layer microbial explicit soil decomposition model framework for boreal forest ecosystems. A thorough sensitivity analysis was conducted to identify dominating biogeochemical processes and to highlight structural limitations. Our results indicate that substrate availability (limited by soil water diffusion and substrate quality) is likely to be a major constraint on soil decomposition in the fibrous horizon (40–60% of soil organic carbon (SOC) pool size variation), while energy limited microbial activity in the amorphous horizon exerts a predominant control on soil decomposition (>70% of SOC pool size variation). Elevated temperature alleviated the energy constraint of microbial activity most notably in amorphous soils, whereas moisture only exhibited a marginal effect on dissolved substrate supply and microbial activity. Our study highlights the different decomposition properties and underlying mechanisms of soil dynamics between fibrous and amorphous soil horizons. Soil decomposition models should consider explicitly representing different boreal soil horizons and soil–microbial interactions to better characterize biogeochemical processes in boreal forest ecosystems. A more comprehensive representation of critical biogeochemical mechanisms of soil moisture effects may be required to improve the performance of the soil model we analyzed in this study.

Implementation and Validation of an Anisotropic Plasticity Model for Clay and a Two-Scale Micropolar Constitutive Model for Sand

NASA Astrophysics Data System (ADS)

Yonten, Karma

As a multi-phase material, soil exhibits highly nonlinear, anisotropic, and inelastic behavior. While it may be impractical for one constitutive model to address all features of the soil behavior, one can identify the essential aspects of the soil's stress-strainstrength response for a particular class of problems and develop a suitable constitutive model that captures those aspects. Here, attention is given to two important features of the soil stress-strain-strength behavior: anisotropy and post-failure response. An anisotropic soil plasticity model is implemented to investigate the significance of initial and induced anisotropy on the response of geo-structures founded on cohesive soils. The model is shown to produce realistic responses for a variety of over-consolidation ratios. Moreover, the performance of the model is assessed in a boundary value problem in which a cohesive soil is subjected to the weight of a newly constructed soil embankment. Significance of incorporating anisotropy is clearly demonstrated by comparing the results of the simulation using the model with those obtained by using an isotropic plasticity model. To investigate post-failure response of soils, the issue of strain localization in geostructures is considered. Post-failure analysis of geo-structures using numerical techniques such as mesh-based or mesh-free methods is often faced with convergence issues which may, at times, lead to incorrect failure mechanisms. This is due to the fact that majority of existing constitutive models are formulated within the framework of classical continuum mechanics that leads to ill-posed governing equations at the onset of localization. To overcome this challenge, a critical state two-surface plasticity model is extended to incorporate the micro-structural mechanisms that become significant within the shear band. The extended model is implemented to study the strain localization of granular soils in drained and undrained conditions. It is demonstrated that the extended model is capable of capturing salient features of soil behavior in pre- and post-failure regimes. The effects of soil particle size, initial density and confining pressure on the thickness and orientation of shear band are investigated and compared with the observed behavior of soils.

The desorptivity model of bulk soil-water evaporation

NASA Technical Reports Server (NTRS)

Clapp, R. B.

1983-01-01

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

Nitrogen dynamics in flooded soil systems: an overview on concepts and performance of models

PubMed Central

Nurulhuda, Khairudin; Gaydon, Donald S; Jing, Qi; Zakaria, Mohamad P; Struik, Paul C

2017-01-01

Abstract Extensive modelling studies on nitrogen (N) dynamics in flooded soil systems have been published. Consequently, many N dynamics models are available for users to select from. With the current research trend, inclined towards multidisciplinary research, and with substantial progress in understanding of N dynamics in flooded soil systems, the objective of this paper is to provide an overview of the modelling concepts and performance of 14 models developed to simulate N dynamics in flooded soil systems. This overview provides breadth of knowledge on the models, and, therefore, is valuable as a first step in the selection of an appropriate model for a specific application. © 2017 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. PMID:28940491

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

NASA Astrophysics Data System (ADS)

Gupta, Manika; Bolten, John; Lakshmi, Venkat

2015-04-01

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

Historical Perspectives and Future Needs in the Development of the Soil Series Concept

NASA Astrophysics Data System (ADS)

Beaudette, Dylan E.; Brevik, Eric C.; Indorante, Samuel J.

2016-04-01

The soil series concept is an ever-evolving understanding of soil profile observations, their connection to the landscape, and functional limits on the range in characteristics that affect management. Historically, the soil series has played a pivotal role in the development of soil-landscape theory, modern soil survey methods, and concise delivery of soils information to the end-user-- in other words, soil series is the palette from which soil survey reports are crafted. Over the last 20 years the soil series has received considerable criticism as a means of soil information organization (soil survey development) and delivery (end-user application of soil survey data), with increasing pressure (internal and external) to retire the soil series. We propose that a modern re-examination of soil series information could help address several of the long-standing critiques of soil survey: consistency across survey vintage and political divisions and more robust estimates of soil properties and associated uncertainty. A new library of soil series data would include classic narratives describing morphology and management, quantitative descriptions of soil properties and their ranges, graphical depiction of the relationships between associated soil series, block diagrams illustrating soil-landscape models, maps of series distribution, and a probabilistic representation of a "typical" soil profile. These data would be derived from re-correlation of existing morphologic and characterization data informed by modern statistical methods and regional expertise.

Extension of coupled multispecies metal transport and speciation (TRANSPEC) model to soil.

PubMed

Bhavsar, Satyendra P; Gandhi, Nilima; Diamond, Miriam L

2008-01-01

Atmospheric deposition of metals emitted from mining operations has raised metal concentrations in the surrounding soils. This repository may be remobilized and act as a source of metals to nearby surface aquatic systems. It is important to understand metal dynamics and the impact of various chemistry and fate parameters on metal movement in the soil environment in order to evaluate risk associated with metals in terrestrial ecosystems and accurately establish critical discharge limits that are protective of aquatic biota. Here we extend our previously developed coupled multispecies metal fate-TRANsport and SPECiation/complexation (TRANSPEC) model, which was applicable to surface aquatic systems. The extended TRANSPEC, termed TRANSPEC-II, estimates the partition coefficient, K(d), between the soil-solid and -soluble phases using site-specific data and a semi-empirical regression model obtained from literature. A geochemical model calculates metal and species fractions in the dissolved and colloidal phases of the soil solution. The multispecies fugacity/aquivalence based fate-transport model then estimates inter-media transport rates such as leaching from soil, soil runoff, and water-sediment exchanges of each metal species. The model is illustratively applied to Ni in the Kelly Lake watershed (Sudbury, Ontario, Canada), where several mining operations are located. The model results suggest that the current atmospheric fallout supplies only 4% of Ni removed from soil through soil runoff and leaching. Soil runoff contributes about 20% of Ni entering into Kelly Lake with the rest coming from other sources. Leaching to groundwater, apart from runoff, is also a major loss process for Ni in the soil. A sensitivity analysis indicates that raising soil pH to above 6 may substantially reduce metal runoff and improve water quality of nearby water bodies that are impacted by runoff.

Predicting forest dieback in Maine, USA: a simple model based on soil frost and drought

Treesearch

Allan N.D. Auclair; Warren E. Heilman; Blondel Brinkman

2010-01-01

Tree roots of northern hardwoods are shallow rooted, winter active, and minimally frost hardened; dieback is a winter freezing injury to roots incited by frost penetration in the absence of adequate snow cover and exacerbated by drought in summer. High soil water content greatly increases conductivity of frost. We develop a model based on the sum of z-scores of soil...

The Role of Priming in the Development of Stable and Radioactive Carbon Isotope Profiles of Soil Organic Matter

NASA Astrophysics Data System (ADS)

Serach, L.; Breecker, D.

2017-12-01

The stability of soil carbon (C) is one of the largest sources of uncertainty in global C cycle models and is central to identifying potential feedbacks to a warming climate. The role that more stable soil organic matter (SOM) pools could have in these feedbacks is highly uncertain. Stable C isotope (δ13C) and radiocarbon (14C) SOM profiles are used to understand the processes involved in soil C stabilization. In this study, we use a 1-dimensional, 3 pool soil C model to simulate the development of SOM δ13C and 14C profiles in a well-drained forest soil. Under the simplest model scenario where decomposition rate constants for each SOM pool remain fixed, model runs exhibit a buildup of slowly degrading C in the shallow subsurface (0-5cm) where fresh, labile C typically dominates in natural soils. Additionally, magnitudes of trends in SOM δ13C and 14C profiles were inconsistent with those observed in natural profiles, suggesting a deficiency in this version of the model. We hypothesize that the observed disparity between modeled and natural profiles is due to the absence of priming in the model. Priming effects presume a change in decomposition rate constants for recalcitrant C pools upon the addition of labile C to the soil. As such, priming effects were simulated in the model by making decomposition rate constants a function of labile C input (e.g., root C and leaf litter). The incorporation of priming into the model yields larger, more realistic shifts in SOM δ13C profiles and trends in 14C profiles that vary based on the sensitivity of recalcitrant pools to labile C addition. So far, the results from this study support the hypothesis that SOM δ13C and 14C profiles cannot be explained without priming. These results highlight the importance of priming to our understanding of the persistence of stable C in the soil and our ability to use SOM δ13C and 14C trends as a means to quantify C stability.

DRAINMOD-FOREST: Integrated modeling of hydrology, soil carbon and nitrogen dynamics, and plant growth for drained forests

Treesearch

Shiying Tian; Mohamed A. Youssef; R. Wayne Skaggs; Devendra M. Amatya; G.M. Chescheir

2012-01-01

We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model,...

The importance of magnetic methods for soil mapping and process modelling. Case study in Ukraine

NASA Astrophysics Data System (ADS)

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

2016-04-01

The correct planning of agriculture areas is fundamental for a sustainable future in Ukraine. After the recent political problems in Ukraine, new challenges emerged regarding sustainability questions. At the same time the soil mapping and modelling are intensively developing all over the world (Pereira et al., 2015; Brevik et al., in press). Magnetic susceptibility (MS) methods are low cost and accurate for the developing maps of agricultural areas, fundamental for Ukrain's economy.This allow to colleact a great amount of soil data, usefull for a better understading of the spatial distribution of soil properties. Recently, this method have been applied in other works in Ukraine and elsewhere (Jordanova et al., 2011; Menshov et al., 2015). The objective of this work is to study the spatial distribution of MS and humus content on the topsoils (0-5 cm) in two different areas. The first is located in Poltava region and the second in Kharkiv region. The results showed that MS depends of soil type, topography and anthropogenic influence. For the interpretation of MS spatial distribution in top soil we consider the frequency and time after the last tillage, tilth depth, fertilizing, and the puddling regarding the vehicle model. On average the soil MS of the top soil of these two cases is about 30-70×10-8 m3/kg. In Poltava region not disturbed soil has on average MS values of 40-50×10-8 m3/kg, for Kharkiv region 50-60×10-8 m3/kg. The tilled soil of Poltava region has on average an MS of 60×10-8 m3/kg, and 70×10-8 m3/kg in Kharkiv region. MS is higher in non-tilled soils than in the tilled ones. The correlation between MS and soil humus content is very high ( up to 0.90) in both cases. Breivik, E., Baumgarten, A., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Jordán, A. Soil mapping, classification, and modelling: history and future directions. Geoderma (in press), doi:10.1016/j.geoderma.2015.05.017 Jordanova D., Jordanova N., Atanasova A., Tsacheva T., Petrov P., (2011). Soil tillage erosion by using magnetism of soils - a case study from Bulgaria. Environ. Monit. Assess, 183, 381-394. Menshov O. Pereira P., Kruglov O., (2015). Spatial variability of soil magnetic susceptibility in an agricultural field located in Eastern Ukraine. Geophysical Research Abstracts, 17, EGU2015-578-2. Pereira, P., Cerdà, A., Úbeda, X., Mataix-Solera, J. Arcenegui, V., Zavala, L. (2015) Modelling the impacts of wildfire on ash thickness in a short-term period, Land Degradation and Development, 26, 180-192. DOI: 10.1002/ldr.2195

Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Trease, Brian

2011-01-01

To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting system, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction System), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using Adams dynamic modeling software. The external library was built in Fortran and called by Adams to model the wheel-soil interactions include the rut-formation effect of deformable soils, lateral and longitudinal forces, bull-dozing effects, and applied wheel torque. The paper presents the details and implementation of the system. To validate the developed system, one study case is presented from a realistic drive on Mars of the Opportunity rover. The simulation results match well from the measurement of on-board telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.

Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra.

PubMed

Peng, Yi; Xiong, Xiong; Adhikari, Kabindra; Knadel, Maria; Grunwald, Sabine; Greve, Mogens Humlekrog

2015-01-01

There is a great challenge in combining soil proximal spectra and remote sensing spectra to improve the accuracy of soil organic carbon (SOC) models. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The first objective of this study was to integrate information of SOC derived from visible near-infrared reflectance (Vis-NIR) spectra in the laboratory with remote sensing (RS) images to improve predictions of topsoil SOC in the Skjern river catchment, Denmark. The second objective was to improve SOC prediction results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l'Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain parameters and soil maps were compiled to predict topsoil SOC using Cubist regression and Bayesian kriging. The results showed that the model developed from RS data, ancillary environmental data and laboratory spectral data yielded a lower root mean square error (RMSE) (2.8%) and higher R2 (0.59) than the model developed from only RS data and ancillary environmental data (RMSE: 3.6%, R2: 0.46). Plant-available water (PAW) was the most important predictor for all the models because of its close relationship with soil organic matter content. Moreover, vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were very important predictors in SOC spatial models. Furthermore, the 'upland model' was able to more accurately predict SOC compared with the 'upland & wetland model'. However, the separately calibrated 'upland and wetland model' did not improve the prediction accuracy for wetland sites, since it was not possible to adequately discriminate the vegetation in the RS summer images. We conclude that laboratory Vis-NIR spectroscopy adds critical information that significantly improves the prediction accuracy of SOC compared to using RS data alone. We recommend the incorporation of laboratory spectra with RS data and other environmental data to improve soil spatial modeling and digital soil mapping (DSM).

Modeling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

On the role of soil fauna in providing soil functions - a meta study

NASA Astrophysics Data System (ADS)

Lang, Birgit; Russell, David J.; Vogel, Hans-Jörg; Wollschläger, Ute

2017-04-01

Fertile soils are fundamental for the production of biomass and therefore for the provision of goods such as food or fuel. However, soils are threatened by e.g. land degradation, but once lost their functionality cannot simply be replaced as soils are complex systems developed over long time periods. Thus, to develop strategies for sustainable soil use and management, we need a comprehensive functional understanding of soil systems. To this end, the interdisciplinary research program "Soil as a Natural Resource for the Bio-Economy - BonaRes" was launched by the German Federal Government in 2015. One part of this program is the development of a Knowledge Centre for soil functions and services. As part of the Knowledge Centre, we focus on the identification and quantification of biological drivers of soil functions. Based on a systematic review of existing literature, we assess the importance of different soil faunal groups for the soil functions and processes most relevant to agricultural production (i.e. decomposition, mineralization, soil structuring. Additionally, we investigate direct impacts of soil fauna on soil properties (e.g. aggregation, pore volume). As site specific conditions such as climate, soil type or management practices affect soil fauna and their performance, these responses must also be taken into account. In the end, our findings will be used in the development of modeling tools aiming to predict the impacts of different management measures on soil ecosystem services and functions.

MODELS FOR LEACHING OF PESTICIDES IN SOILS AND GROUNDWATER

EPA Science Inventory

Models are developed which describe leaching of pesticides in the root zone and the intermediate vadose zone, and flushing of residual solute mass in the aquifer. Pollutants' loss pathways in the soil, such as volatilization, crop uptake, and biochemical decay, are emphasized, a...

Soil process modelling in CZO research: gains in data harmonisation and model validation

NASA Astrophysics Data System (ADS)

van Gaans, Pauline; Andrianaki, Maria; Kobierska, Florian; Kram, Pavel; Lamacova, Anna; Lair, Georg; Nikolaidis, Nikos; Duffy, Chris; Regelink, Inge; van Leeuwen, Jeroen P.; de Ruiter, Peter

2014-05-01

Various soil process models were applied to four European Critical Zone observatories (CZOs), the core research sites of the FP7 project SoilTrEC: the Damma glacier forefield (CH), a set of three forested catchments on geochemically contrasing bedrocks in the Slavkov Forest (CZ), a chronosequence of soils in the former floodplain of the Danube of Fuchsenbigl/Marchfeld (AT), and the Koiliaris catchments in the north-western part of Crete, (GR). The aim of the modelling exercises was to apply and test soil process models with data from the CZOs for calibration/validation, identify potential limits to the application scope of the models, interpret soil state and soil functions at key stages of the soil life cycle, represented by the four SoilTrEC CZOs, contribute towards harmonisation of data and data acquisition. The models identified as specifically relevant were: The Penn State Integrated Hydrologic Model (PIHM), a fully coupled, multiprocess, multi-scale hydrologic model, to get a better understanding of water flow and pathways, The Soil and Water Assessment Tool (SWAT), a deterministic, continuous time (daily time step) basin scale model, to evaluate the impact of soil management practices, The Rothamsted Carbon model (Roth-C) to simulate organic carbon turnover and the Carbon, Aggregation, and Structure Turnover (CAST) model to include the role of soil aggregates in carbon dynamics, The Ligand Charge Distribution (LCD) model, to understand the interaction between organic matter and oxide surfaces in soil aggregate formation, and The Terrestrial Ecology Model (TEM) to obtain insight into the link between foodweb structure and carbon and nutrient turnover. With some exceptions all models were applied to all four CZOs. The need for specific model input contributed largely to data harmonisation. The comparisons between the CZOs turned out to be of great value for understanding the strength and limitations of the models, as well as the differences in soil conditions between the CZOs. The CZO modelling led to further developments of the PIHM, with incorporation of functionality for karstic fracture flow (Koiliaris) and fracture flow anisotropy (Damma). The Damma case also provided experience on how to use results from geophysical investigations in model refinement. The SWAT modelling showed variability among the CZOs in hydraulic conductivity, the curve number that determines how fast rainfall results in runoff, and soil moisture capacity. Roth-C and CAST showed carbon sequestration fluxes to be low for old cultivated soils (Koiliaris) and high for new soils (Damma), where the latter site also had very high turnover rates. The LCD modelling, so far limited to the calcareous floodplain soils in Austria, explains differences in C-sequestration capacity between forest and agricultural soils from competition between phosphate and soil organic matter for adsorption sites on Fe-(hydr)oxides. The wide variety of soil (eco)system conditions challenged the TEM model and showed important directions for refinement: 1) differentiating between various fractions of organic matter and concomitant microbial decomposition pathways, and 2) the need to better define the physiological traits of the organisms in relation to local environmental conditions.

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 Logistic Regression to Predict the Probability of Debris Flows in Areas Burned by Wildfires, Southern California, 2003-2006

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.; Michael, John A.; Helsel, Dennis R.

2008-01-01

Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

2015-12-01

Forest carbon processes are affected by soil moisture, soil temperature and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore they can neither resolve topographically driven hill-slope soil moisture patterns, nor simulate the nonlinear effects of soil moisture on carbon processes. A spatially-distributed biogeochemistry model, Flux-PIHM-BGC, has been developed by coupling the Biome-BGC (BBGC) model with a coupled physically-based land surface hydrologic model, Flux-PIHM. Flux-PIHM incorporates a land-surface scheme (adapted from the Noah land surface model) into the Penn State Integrated Hydrologic Model (PIHM). Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. Flux-PIHM-BGC model was tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations at the SSHCZO, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, aboveground carbon stock, and soil carbon efflux, provided an ideal test bed for the coupled model. Model results show that when uniform solar radiation is used, vegetation carbon and soil carbon are positively correlated with soil moisture in space, which agrees with the observations within the watershed. When topographically-driven solar radiation is used, however, the wetter valley floor becomes radiation limited, and produces less vegetation and soil carbon than the drier hillslope due to the assumption that canopy height is uniform in the watershed. This contradicts with the observations, and suggests that a tree height model with dynamic allocation model are needed to reproduce the spatial variation of carbon processes within a watershed.

Developing an integration tool for soil contamination assessment

NASA Astrophysics Data System (ADS)

Anaya-Romero, Maria; Zingg, Felix; Pérez-Álvarez, José Miguel; Madejón, Paula; Kotb Abd-Elmabod, Sameh

2015-04-01

In the last decades, huge soil areas have been negatively influenced or altered in multiples forms. Soils and, consequently, underground water, have been contaminated by accumulation of contaminants from agricultural activities (fertilizers and pesticides) industrial activities (harmful material dumping, sludge, flying ashes) and urban activities (hydrocarbon, metals from vehicle traffic, urban waste dumping). In the framework of the RECARE project, local partners across Europe are focusing on a wide range of soil threats, as soil contamination, and aiming to develop effective prevention, remediation and restoration measures by designing and applying targeted land management strategies (van Lynden et al., 2013). In this context, the Guadiamar Green Corridor (Southern Spain) was used as a case study, aiming to obtain soil data and new information in order to assess soil contamination. The main threat in the Guadiamar valley is soil contamination after a mine spill occurred on April 1998. About four hm3 of acid waters and two hm3 of mud, rich in heavy metals, were released into the Agrio and Guadiamar rivers affecting more than 4,600 ha of agricultural and pasture land. Main trace elements contaminating soil and water were As, Cd, Cu, Pb, Tl and Zn. The objective of the present research is to develop informatics tools that integrate soil database, models and interactive platforms for soil contamination assessment. Preliminary results were obtained related to the compilation of harmonized databases including geographical, hydro-meteorological, soil and socio-economic variables based on spatial analysis and stakeholder's consultation. Further research will be modellization and upscaling at the European level, in order to obtain a scientifically-technical predictive tool for the assessment of soil contamination.

The role of organic soil layer on the fate of Siberian larch forest and near-surface permafrost under changing climate: A simulation study

NASA Astrophysics Data System (ADS)

SATO, H.; Iwahana, G.; Ohta, T.

2013-12-01

Siberian larch forest is the largest coniferous forest region in the world. In this vast region, larch often forms nearly pure stands, regenerated by recurrent fire. This region is characterized by a short and dry growing season; the annual mean precipitation for Yakutsk was only about 240 mm. To maintain forest ecosystem under such small precipitation, underlying permafrost and seasonal soil freezing-thawing-cycle have been supposed to play important roles; (1) frozen ground inhibits percolation of soil water into deep soil layers, and (2) excess soil water at the end of growing season can be carried over until the next growing season as ice, and larch trees can use the melt water. As a proof for this explanation, geographical distribution of Siberian larch region highly coincides with continuous and discontinuous permafrost zone. Recent observations and simulation studies suggests that existences of larch forest and permafrost in subsurface layer are co-dependent; permafrost maintains the larch forest by enhancing water use efficiency of trees, while larch forest maintains permafrost by inhibiting solar radiation and preventing heat exchanges between soil and atmosphere. Owing to such complexity and absence of enough ecosystem data available, current-generation Earth System Models significantly diverse in their prediction of structure and key ecosystem functions in Siberian larch forest under changing climate. Such uncertainty should in turn expand uncertainty over predictions of climate, because Siberian larch forest should have major role in the global carbon balance with its huge area and vast potential carbon pool within the biomass and soil, and changes in boreal forest albedo can have a considerable effect on Northern Hemisphere climate. In this study, we developed an integrated ecosystem model, which treats interactions between plant-dynamics and freeze-thaw cycles. This integrated model contains a dynamic global vegetation model SEIB-DGVM, which simulates plant and carbon dynamics. It also contains a one-dimensional land surface model NOAH 2.7.1, which simulates soil moisture (both liquid and frozen), soil temperature, snowpack depth and density, canopy water content, and the energy and water fluxes. This integrated model quantitatively reconstructs post-fire development of forest structure (i.e. LAI and biomass) and organic soil layer, which dampens heat exchanges between soil and atmosphere. With the post-fire development of LAI and the soil organic layer, the integrated model also quantitatively reconstructs changes in seasonal maximum of active layer depth. The integrated model is then driven by the IPCC A1B scenario of rising atmospheric CO2, and by climate changes during the twenty-first century resulting from the change in CO2. This simulation suggests that forecasted global warming would causes decay of Siberian larch ecosystem, but such responses could be delayed by "memory effect" of the soil organic layer for hundreds of years.

Evaporation from soils subjected to natural boundary conditions at the land-atmospheric interface

NASA Astrophysics Data System (ADS)

Smits, K.; Illngasekare, T.; Ngo, V.; Cihan, A.

2012-04-01

Bare soil evaporation is a key process for water exchange between the land and the atmosphere and an important component of the water balance in semiarid and arid regions. However, there is no agreement on the best methodology to determine evaporation under different boundary conditions at the land surface. This becomes critical in developing models that couples land to the atmosphere. Because it is difficult to measure evaporation from soil, with the exception of using lysimeters, numerous formulations have been proposed to establish a relationship between the rate of evaporation and soil moisture and/or soil temperature and thermal properties. Different formulations vary in how they partition available energy. A need exists to systematically compare existing methods to experimental data under highly controlled conditions not achievable in the field. The goal of this work is to perform controlled experiments under transient conditions of soil moisture, temperature and wind at the land/atmospheric interface to test different conceptual and mathematical formulations for the soil surface boundary conditions to develop appropriate numerical models to be used in simulations. In this study, to better understand the coupled water-vapor-heat flow processes in the shallow subsurface near the land surface, we modified a previously developed theory by Smits et al. [2011] that allows non-equilibrium liquid/gas phase change with gas phase vapor diffusion to better account for dry soil conditions. The model did not implement fitting parameters such as a vapor enhancement factor that is commonly introduced into the vapor diffusion coefficient as an arbitrary multiplication factor. In order to experimentally test the numerical formulations/code, we performed a two-dimensional physical model experiment under varying boundary conditions using test sand for which the hydraulic and thermal properties were well characterized. Precision data under well-controlled transient heat and wind boundary conditions was generated and results from numerical simulations were compared with experimental data. Results demonstrate that the boundary condition approaches varied in their ability to capture stage 1- and stage 2- evaporation. Results also demonstrated the importance of properly characterizing soil thermal properties and accounting for dry soil conditions. The contribution of film flow to hydraulic conductivity for the layer above the drying front is dominant compared to that of capillary flow, demonstrating the importance of including film flow in modeling efforts for dry soils, especially for fine grained soils. Comparisons of different formulations of the surface boundary condition validate the need for joint evaluation of heat and mass transfer for better modeling accuracy. This knowledge is applicable to many current hydrologic and environmental problems to include climate modeling and the simulation of contaminant transport and volatilization in the shallow subsurface. Smits, K. M., A. Cihan, T. Sakaki, and T. H. Illangasekare (2011). Evaporation from soils under thermal boundary conditions: Experimental and modeling investigation to compare equilibrium- and nonequilibrium-based approaches, Water Resour. Res., 47, W05540, doi:10.1029/2010WR009533.

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.

Eawag-Soil in enviPath: a new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data.

PubMed

Latino, Diogo A R S; Wicker, Jörg; Gütlein, Martin; Schmid, Emanuel; Kramer, Stefan; Fenner, Kathrin

2017-03-22

Developing models for the prediction of microbial biotransformation pathways and half-lives of trace organic contaminants in different environments requires as training data easily accessible and sufficiently large collections of respective biotransformation data that are annotated with metadata on study conditions. Here, we present the Eawag-Soil package, a public database that has been developed to contain all freely accessible regulatory data on pesticide degradation in laboratory soil simulation studies for pesticides registered in the EU (282 degradation pathways, 1535 reactions, 1619 compounds and 4716 biotransformation half-life values with corresponding metadata on study conditions). We provide a thorough description of this novel data resource, and discuss important features of the pesticide soil degradation data that are relevant for model development. Most notably, the variability of half-life values for individual compounds is large and only about one order of magnitude lower than the entire range of median half-life values spanned by all compounds, demonstrating the need to consider study conditions in the development of more accurate models for biotransformation prediction. We further show how the data can be used to find missing rules relevant for predicting soil biotransformation pathways. From this analysis, eight examples of reaction types were presented that should trigger the formulation of new biotransformation rules, e.g., Ar-OH methylation, or the extension of existing rules, e.g., hydroxylation in aliphatic rings. The data were also used to exemplarily explore the dependence of half-lives of different amide pesticides on chemical class and experimental parameters. This analysis highlighted the value of considering initial transformation reactions for the development of meaningful quantitative-structure biotransformation relationships (QSBR), which is a novel opportunity offered by the simultaneous encoding of transformation reactions and corresponding half-lives in Eawag-Soil. Overall, Eawag-Soil provides an unprecedentedly rich collection of manually extracted and curated biotransformation data, which should be useful in a great variety of applications.

State of the Art in Large-Scale Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;

Estimating root-zone soil moisture in the West Africa Sahel using remotely sensed rainfall and vegetation

NASA Astrophysics Data System (ADS)

McNally, Amy L.

Agricultural drought is characterized by shortages in precipitation, large differences between actual and potential evapotranspiration, and soil water deficits that impact crop growth and pasture productivity. Rainfall and other agrometeorological gauge networks in Sub-Saharan Africa are inadequate for drought early warning systems and hence, satellite-based estimates of rainfall and vegetation greenness provide the main sources of information. While a number of studies have described the empirical relationship between rainfall and vegetation greenness, these studies lack a process based approach that includes soil moisture storage. In Chapters I and II, I modeled soil moisture using satellite rainfall inputs and developed a new method for estimating soil moisture with NDVI calibrated to in situ and microwave soil moisture observations. By transforming both NDVI and rainfall into estimates of soil moisture I was able to easily compare these two datasets in a physically meaningful way. In Chapter II, I also show how the new NDVI derived soil moisture can be assimilated into a water balance model that calculates an index of crop water stress. Compared to the analogous rainfall derived estimates of soil moisture and crop stress the NDVI derived estimates were better correlated with millet yields. In Chapter III, I developed a metric for defining growing season drought events that negatively impact millet yields. This metric is based on the data and models used in the Chapters I and II. I then use this metric to evaluate the ability of a sophisticated land surface model to detect drought events. The analysis showed that this particular land surface model's soil moisture estimates do have the potential to benefit the food security and drought early warning communities. With a focus on soil moisture, this dissertation introduced new methods that utilized a variety of data and models for agricultural drought monitoring applications. These new methods facilitate a more quantitative, transparent `convergence of evidence' approach to identifying agricultural drought events that lead to food insecurity. Ideally, these new methods will contribute to better famine early warning and the timely delivery of food aid to reduce the human suffering caused by drought.

GEMAS: prediction of solid-solution phase partitioning coefficients (Kd) for oxoanions and boric acid in soils using mid-infrared diffuse reflectance spectroscopy.

PubMed

Janik, Leslie J; Forrester, Sean T; Soriano-Disla, José M; Kirby, Jason K; McLaughlin, Michael J; Reimann, Clemens

2015-02-01

The authors' aim was to develop rapid and inexpensive regression models for the prediction of partitioning coefficients (Kd), defined as the ratio of the total or surface-bound metal/metalloid concentration of the solid phase to the total concentration in the solution phase. Values of Kd were measured for boric acid (B[OH]3(0)) and selected added soluble oxoanions: molybdate (MoO4(2-)), antimonate (Sb[OH](6-)), selenate (SeO4(2-)), tellurate (TeO4(2-)) and vanadate (VO4(3-)). Models were developed using approximately 500 spectrally representative soils of the Geochemical Mapping of Agricultural Soils of Europe (GEMAS) program. These calibration soils represented the major properties of the entire 4813 soils of the GEMAS project. Multiple linear regression (MLR) from soil properties, partial least-squares regression (PLSR) using mid-infrared diffuse reflectance Fourier-transformed (DRIFT) spectra, and models using DRIFT spectra plus analytical pH values (DRIFT + pH), were compared with predicted log K(d + 1) values. Apart from selenate (R(2)  = 0.43), the DRIFT + pH calibrations resulted in marginally better models to predict log K(d + 1) values (R(2)  = 0.62-0.79), compared with those from PSLR-DRIFT (R(2)  = 0.61-0.72) and MLR (R(2)  = 0.54-0.79). The DRIFT + pH calibrations were applied to the prediction of log K(d + 1) values in the remaining 4313 soils. An example map of predicted log K(d + 1) values for added soluble MoO4(2-) in soils across Europe is presented. The DRIFT + pH PLSR models provided a rapid and inexpensive tool to assess the risk of mobility and potential availability of boric acid and selected oxoanions in European soils. For these models to be used in the prediction of log K(d + 1) values in soils globally, additional research will be needed to determine if soil variability is accounted on the calibration. © 2014 SETAC.

Development of an earth pressure model for design of earth retaining structures in piedmont soil.

DOT National Transportation Integrated Search

2008-10-01

Anecdotal evidence suggests that earth pressure in Piedmont residual soils is typically over estimated. Such estimates of earth pressure impact the design of earth retaining structures used on highway projects. Thus, the development of an appropriate...

Soil Carbon and Nitrogen Cycle Modeling

NASA Astrophysics Data System (ADS)

Woo, D.; Chaoka, S.; Kumar, P.; Quijano, J. C.

2012-12-01

Second generation bioenergy crops, such as miscanthus (Miscantus × giganteus) and switchgrass (Panicum virgatum), are regarded as clean energy sources, and are an attractive option to mitigate the human-induced climate change. However, the global climate change and the expansion of perennial grass bioenergy crops have the power to alter the biogeochemical cycles in soil, especially, soil carbon storages, over long time scales. In order to develop a predictive understanding, this study develops a coupled hydrological-soil nutrient model to simulate soil carbon responses under different climate scenarios such as: (i) current weather condition, (ii) decreased precipitation by -15%, and (iii) increased temperature up to +3C for four different crops, namely miscanthus, switchgrass, maize, and natural prairie. We use Precision Agricultural Landscape Modeling System (PALMS), version 5.4.0, to capture biophysical and hydrological components coupled with a multilayer carbon and ¬nitrogen cycle model. We apply the model at daily time scale to the Energy Biosciences Institute study site, located in the University of Illinois Research Farms, in Urbana, Illinois. The atmospheric forcing used to run the model was generated stochastically from parameters obtained using available data recorded in Bondville Ameriflux Site. The model simulations are validated with observations of drainage and nitrate and ammonium concentrations recorded in drain tiles during 2011. The results of this study show (1) total soil carbon storage of miscanthus accumulates most noticeably due to the significant amount of aboveground plant carbon, and a relatively high carbon to nitrogen ratio and lignin content, which reduce the litter decomposition rate. Also, (2) the decreased precipitation contributes to the enhancement of total soil carbon storage and soil nitrogen concentration because of the reduced microbial biomass pool. However, (3) an opposite effect on the cycle is introduced by the increased temperature. The simulation results obtained in this study show differences in the soil biogeochemistry induced by the different crops analyzed. Considering the spatial scale at which this crops are cultivated this results suggest there could be important implications in the carbon and nitrogen cycle and indirect feedbacks on climate change. This study also helps us understand the future soil mineral cycle, and ensure a sustainable transition to bioenergy crops.

Modeling critical zone processes in intensively managed environments

NASA Astrophysics Data System (ADS)

Kumar, Praveen; Le, Phong; Woo, Dong; Yan, Qina

2017-04-01

Processes in the Critical Zone (CZ), which sustain terrestrial life, are tightly coupled across hydrological, physical, biochemical, and many other domains over both short and long timescales. In addition, vegetation acclimation resulting from elevated atmospheric CO2 concentration, along with response to increased temperature and altered rainfall pattern, is expected to result in emergent behaviors in ecologic and hydrologic functions, subsequently controlling CZ processes. We hypothesize that the interplay between micro-topographic variability and these emergent behaviors will shape complex responses of a range of ecosystem dynamics within the CZ. Here, we develop a modeling framework ('Dhara') that explicitly incorporates micro-topographic variability based on lidar topographic data with coupling of multi-layer modeling of the soil-vegetation continuum and 3-D surface-subsurface transport processes to study ecological and biogeochemical dynamics. We further couple a C-N model with a physically based hydro-geomorphologic model to quantify (i) how topographic variability controls the spatial distribution of soil moisture, temperature, and biogeochemical processes, and (ii) how farming activities modify the interaction between soil erosion and soil organic carbon (SOC) dynamics. To address the intensive computational demand from high-resolution modeling at lidar data scale, we use a hybrid CPU-GPU parallel computing architecture run over large supercomputing systems for simulations. Our findings indicate that rising CO2 concentration and air temperature have opposing effects on soil moisture, surface water and ponding in topographic depressions. Further, the relatively higher soil moisture and lower soil temperature contribute to decreased soil microbial activities in the low-lying areas due to anaerobic conditions and reduced temperatures. The decreased microbial relevant processes cause the reduction of nitrification rates, resulting in relatively lower nitrate concentration. Results from geomorphologic model also suggest that soil erosion and deposition plays a dominant role in SOC both above- and below-ground. In addition, tillage can change the amplitude and frequency of C-N oscillation. This work sheds light in developing practical means for reducing soil erosion and carbon loss when the landscape is affected by human activities.

Soil Organic Carbon and Nutrient Dynamics in Reclaimed Appalachian Mine Soil

NASA Astrophysics Data System (ADS)

Acton, P.; Fox, J.; Campbell, J. E.; Rowe, H. D.; Jones, A.

2011-12-01

Past research has shown that drastically disturbed and degraded soils can offer a high potential for soil organic carbon and aboveground carbon sequestration. Little work has been done on both the functioning of soil carbon accumulation and turnover in reclaimed surface mining soils. Reclamation practices of surface coal mine soils in the Southern Appalachian forest region of the United States emphasizes heavy compaction of surface material to provide slope stability and reduce surface erosion, and topsoil is not typically added. An analysis of the previously collected data has provided a 14 year chronosequence of SOC uptake and development in the soil column and revealed that these soils are sequestering carbon at a rate of 1.3 MgC ha-1 yr-1, which is 1.6 to 3 times less than mining soils reported for other regions. Results of bulk density analysis indicate a contrast between 0 - 10 cm (1.51 g cm-3) and 10 - 50 cm (2.04 g cm-3) depth intervals. Aggregate stability was also quantified as well as dynamic soil texture measurements. With this analysis, it has been established that these soils are well below their potential in terms of the ability to store and cycle carbon and other nutrients as well their ability to sustain a fully-functioning forested ecosystem typical for the region. We are taking an integrated approach that relies on ecological observations for present conditions combined with computational modeling to understand long-term soil organic carbon (SOC) accumulation and turnover in regards to SOC sequestration potential and quantification of specific processes by which these soils develop. A dual-isotope end-member model, utilizing the carbon 13 and nitrogen 15 stable isotopes, is being developed to provide greater input into the mathematical separation of organic carbon derived from new soil inputs and existing coal carbon. Soils from the study sites have been isolated into three distinct size pools, and elemental and isotopic analysis of these samples was performed. These results are being used to calibrate an isotope fractionation model to quantify decomposition rates of various conceptual organic matter pools. The hydrology of the mine soils is being modeled using the SCS curve number method to quantify infiltration rates. An assessment of above and belowground biomass was performed to provide estimates for annual plant production. Soil samples will be analyzed for micronutrient content. The CENTURY soil organic matter model will be utilized to provide a biogeochemical analysis of the plant and soil ecosystem. Simulations will be made under varying climatic and land-use changes. Surface coal mine extraction can act as a disturbance and greatly impacts the terrestrial carbon reservoir through initial removal of aboveground biomass and soil carbon and thereafter mineland reclamation. This research will provide a better understanding of the net impact of surface coal mining on terrestrial carbon, thus accounting for long term C sequestration in the soils and aboveground biomass that might offset drastic carbon disturbance in the initial stage of surface mining.

EFFECTS OF ELECTROOSMOSIS ON SOIL TEMPERATURE AND HYDRAULIC HEAD: II. NUMERICAL SIMULATION

EPA Science Inventory

A numerical model to simulate the distributions of voltage, soil temperature, and hydraulic head during the field test of electroosmosis was developed. The two-dimensional governing equations for the distributions of voltage, soil temperature, and hydraulic head within a cylindri...

Gaining insights into interrill soil erosion processes using rare earth element tracers

USDA-ARS?s Scientific Manuscript database

Increasing interest in developing process-based erosion models requires better understanding of the relationships among soil detachment, transportation, and deposition. The objectives are to 1) identify the limiting process between soil detachment and sediment transport for interrill erosion, 2) und...

Highly spatially- and seasonally-resolved predictive contamination maps for persistent organic pollutants: development and validation.

PubMed

Ballabio, Cristiano; Guazzoni, Niccoló; Comolli, Roberto; Tremolada, Paolo

2013-08-01

A reliable spatial assessment of the POPs contamination in soils is essential for burden studies and flux evaluations. Soil characteristics and properties vary enormously even within small spatial scale and over time; therefore soil capacity of accumulating POPs varies greatly. In order to include this very high spatial and temporal variability, models can be used for assessing soil accumulation capacity in a specific time and space and, from it, the spatial distribution and temporal trends of POPs concentrations. In this work, predictive contamination maps of the accumulation capacity of soils were developed at a space resolution of 1×1m with a time frame of one day, in a study area located in the central Alps. Physical algorithms for temperature and organic carbon estimation along the soil profile and across the year were fitted to estimate the horizontal, vertical and seasonal distribution of the contamination potential for PCBs in soil (Ksa maps). The resulting maps were cross-validated with an independent set of PCB contamination data, showing very good agreement (e.g. for CB-153, R(2)=0.80, p-value≤2.2·10(-06)). Slopes of the regression between predicted Ksa and experimental concentrations were used to map the soil contamination for the whole area, taking into account soil characteristics and temperature conditions. These maps offer the opportunity to evaluate burden (concentration maps) and fluxes (emission maps) with highly resolved temporal and spatial detail. In addition, in order to explain the observed low autumn PCB concentrations in soil related to the high Ksa values of this period, a dynamic model of seasonal variation of soil concentrations was developed basing on rate parameters fitted on measured concentrations. The model was able to describe, at least partially, the observed different behavior between the quite rapid discharge phase in summer and the slow recharge phase in autumn. Copyright © 2013 Elsevier B.V. All rights reserved.

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

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Holmes, Thomas

2007-01-01

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

Quantification of the inevitable: the influence of soil macrofauna on soil water movement in rehabilitated open-cut mined lands

NASA Astrophysics Data System (ADS)

Arnold, S.; Williams, E. R.

2016-01-01

Recolonisation of soil by macrofauna (especially ants, termites and earthworms) in rehabilitated open-cut mine sites is inevitable and, in terms of habitat restoration and function, typically of great value. In these highly disturbed landscapes, soil invertebrates play a major role in soil development (macropore configuration, nutrient cycling, bioturbation, etc.) and can influence hydrological processes such as infiltration, seepage, runoff generation and soil erosion. Understanding and quantifying these ecosystem processes is important in rehabilitation design, establishment and subsequent management to ensure progress to the desired end goal, especially in waste cover systems designed to prevent water reaching and transporting underlying hazardous waste materials. However, the soil macrofauna is typically overlooked during hydrological modelling, possibly due to uncertainties on the extent of their influence, which can lead to failure of waste cover systems or rehabilitation activities. We propose that scientific experiments under controlled conditions and field trials on post-mining lands are required to quantify (i) macrofauna-soil structure interactions, (ii) functional dynamics of macrofauna taxa, and (iii) their effects on macrofauna and soil development over time. Such knowledge would provide crucial information for soil water models, which would increase confidence in mine waste cover design recommendations and eventually lead to higher likelihood of rehabilitation success of open-cut mining land.

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.

Model-Based Analysis of the Long-Term Effects of Fertilization Management on Cropland Soil Acidification.

PubMed

Zeng, Mufan; de Vries, Wim; Bonten, Luc T C; Zhu, Qichao; Hao, Tianxiang; Liu, Xuejun; Xu, Minggang; Shi, Xiaojun; Zhang, Fusuo; Shen, Jianbo

2017-04-04

Agricultural soil acidification in China is known to be caused by the over-application of nitrogen (N) fertilizers, but the long-term impacts of different fertilization practices on intensive cropland soil acidification are largely unknown. Here, we further developed the soil acidification model VSD+ for intensive agricultural systems and validated it against observed data from three long-term fertilization experiments in China. The model simulated well the changes in soil pH and base saturation over the last 20 years. The validated model was adopted to quantify the contribution of N and base cation (BC) fluxes to soil acidification. The net NO 3 - leaching and NO 4 + input accounted for 80% of the proton production under N application, whereas one-third of acid was produced by BC uptake when N was not applied. The simulated long-term (1990-2050) effects of different fertilizations on soil acidification showed that balanced N application combined with manure application avoids reduction of both soil pH and base saturation, while application of calcium nitrate and liming increases these two soil properties. Reducing NH 4 + input and NO 3 - leaching by optimizing N management and increasing BC inputs by manure application thus already seem to be effective approaches to mitigating soil acidification in intensive cropland systems.

Approach To Development of Guidelines For Determination of Natural Attenuation Capacity and Resilience of Soils

NASA Astrophysics Data System (ADS)

Putters, B.

The natural attenuation capacity of the soil is often used to help remove contaminants from the soil and groundwater. However, the definition of natural attenuation capac- ity in terms of soil properties, and how it should be measured are still a matter of discussion. Moreover, due to the interaction between soil and pollutant during the attenuation processes, changes in soil properties may occur. The resilience of the soil determines the rate of recovery of the soil, and to what extent it regains its original capacity for attenuation. This resilience, too, is not yet defined or measureable. The objective of the research is to develop guidelines to determine the natural attenu- ation capacity and the resilience of soils. The approach comprises five steps: 1. Experimental data on degradation and adsorp- tion are collected from literature. Missing data are filled by means of regression tech- niques. 2. Based upon existing knowledge on fate and behaviour of pollutants in soil environment, data are analysed on expected relations between soil parameters: which parameters determine the processes. 3. The most important parameters are analysed in a sensitivity analysis, performed by means of a mechanistic model. The testing vari- ables in the sensitivity analysis are an expression of the natural attenuation capacity and the resilience, respectively, and will be related to time. 4. The sensitivity analy- sis is extended by development of an artificial neural network and by use of genetic algorithms. 5. Data from the realisations (model calculations with different input) are classified into guidelines.

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

PubMed

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

2014-10-01

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

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

PubMed Central

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

2014-01-01

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

High resolution change estimation of soil moisture and its assimilation into a land surface model

NASA Astrophysics Data System (ADS)

Narayan, Ujjwal

Near surface soil moisture plays an important role in hydrological processes including infiltration, evapotranspiration and runoff. These processes depend non-linearly on soil moisture and hence sub-pixel scale soil moisture variability characterization is important for accurate modeling of water and energy fluxes at the pixel scale. Microwave remote sensing has evolved as an attractive technique for global monitoring of near surface soil moisture. A radiative transfer model has been tested and validated for soil moisture retrieval from passive microwave remote sensing data under a full range of vegetation water content conditions. It was demonstrated that soil moisture retrieval errors of approximately 0.04 g/g gravimetric soil moisture are attainable with vegetation water content as high as 5 kg/m2. Recognizing the limitation of low spatial resolution associated with passive sensors, an algorithm that uses low resolution passive microwave (radiometer) and high resolution active microwave (radar) data to estimate soil moisture change at the spatial resolution of radar operation has been developed and applied to coincident Passive and Active L and S band (PALS) and Airborne Synthetic Aperture Radar (AIRSAR) datasets acquired during the Soil Moisture Experiments in 2002 (SMEX02) campaign with root mean square error of 10% and a 4 times enhancement in spatial resolution. The change estimation algorithm has also been used to estimate soil moisture change at 5 km resolution using AMSR-E soil moisture product (50 km) in conjunction with the TRMM-PR data (5 km) for a 3 month period demonstrating the possibility of high resolution soil moisture change estimation using satellite based data. Soil moisture change is closely related to precipitation and soil hydraulic properties. A simple assimilation framework has been implemented to investigate whether assimilation of surface layer soil moisture change observations into a hydrologic model will potentially improve it performance. Results indicate an improvement in model prediction of near surface and deep layer soil moisture content when the update is performed to the model state as compared to free model runs. It is also seen that soil moisture change assimilation is able to mitigate the effect of erroneous precipitation input data.

Modeling the Dynamics of Soil Structure and Water in Agricultural Soil

NASA Astrophysics Data System (ADS)

Weller, U.; Lang, B.; Rabot, E.; Stössel, B.; Urbanski, L.; Vogel, H. J.; Wiesmeier, M.; Wollschlaeger, U.

2017-12-01

The impact of agricultural management on soil functions is manifold and severe. It has both positive and adverse influence. Our goal is to develop model tools quantifying the agricultural impact on soil functions based on a mechanistic understanding of soil processes to support farmers and decision makers. The modeling approach is based on defining relevant soil components, i.e. soil matrix, macropores, organisms, roots and organic matter. They interact and form the soil's macroscopic properties and functions including water and gas dynamics, and biochemical cycles. Based on existing literature information we derive functional interaction processes and combine them in a network of dynamic soil components. In agricultural soils, a major issue is linked to changes in soil structure and their influence on water dynamics. Compaction processes are well studied in literature, but for the resilience due to root growth and activity of soil organisms the information is scarcer. We implement structural dynamics into soil water and gas simulations using a lumped model that is both coarse enough to allow extensive model runs while still preserving some important, yet rarely modeled phenomenons like preferential flow, hysteretic and dynamic behavior. For simulating water dynamics, at each depth, the model assumes water at different binding energies depending on soil structure, i.e. the pore size distribution. Non-equilibrium is postulated, meaning that free water may occur even if the soil is not fully saturated. All energy levels are interconnected allowing water to move, both within a spatial node, and between neighboring nodes (adding gravity). Structure dynamics alters the capacity of this water compartments, and the conductance of its connections. Connections are switched on and off depending on whether their sources contain water or their targets have free capacity. This leads to piecewise linear system behavior that allows fast calculation for extended time steps. Based on this concept, the dynamics of soil structure can be directly linked to soil water dynamics as a main driver for other soil processes. Further steps will include integration of temperature and solute leaching as well as defining the feedback of the water regime on the structure forming processes.

Coupling System Dynamics and Physically-based Models for Participatory Water Management - A Methodological Framework, with Two Case Studies: Water Quality in Quebec, and Soil Salinity in Pakistan

NASA Astrophysics Data System (ADS)

Boisvert-Chouinard, J.; Halbe, J.; Baig, A. I.; Adamowski, J. F.

2014-12-01

The principles of Integrated Water Resource Management outline the importance of stakeholder participation in water management processes, but in practice, there is a lack of meaningful engagement in water planning and implementation, and participation is often limited to public consultation and education. When models are used to support water planning, stakeholders are usually not involved in their development and use, and the models commonly fail to represent important feedbacks between socio-economic and physical processes. This paper presents the development of holistic models of the Du Chêne basin in Quebec, and the Rechna Doab basin in Pakistan, that simulate socio-economic and physical processes related to, respectively, water quality management, and soil salinity management. The models each consists of two sub-components: a System Dynamics (SD) model, and a physically based model. The SD component was developed in collaboration with key stakeholders in the basins. The Du Chêne SD model was coupled with a Soil and Water Assessment Tool (SWAT) model, while the Rechna Doab SD model was coupled with SahysMod, a soil salinity model. The coupled models were used to assess the environmental and socio-economic impacts of different management scenarios proposed by stakeholders. Results indicate that coupled SD - physically-based models can be used as effective tools for participatory water planning and implementation. The participatory modeling process provides a structure for meaningful stakeholder engagement, and the models themselves can be used to transparently and coherently assess and compare different management options.

Analysis of Infiltration-Suction Response in Unsaturated Residual Soil Slope in Gelugor, Penang

NASA Astrophysics Data System (ADS)

Ashraf Mohamad Ismail, Mohd; Hasliza Hamzah, Nur; Min, Ng Soon; Hazreek Zainal Abidin, Mohd; Tajudin, Saiful Azhar Ahmad; Madun, Aziman

2018-04-01

Rainfall infiltration on residual soil slope may impair slope stability by altering the pore-water pressure in the soil. A study has been carried out on unsaturated residual soil slope in Gelugor, Penang to determine the changes in matric suction of residual soils at different depth due to rainwater infiltration. The sequence of this study includes the site investigation, field instrumentation, laboratory experiment and numerical modeling. Void ratio and porosity of soil were found to be decreasing with depth while the bulk density and dry density of soil increased due to lower porosity of soil at greater depth. Soil infiltration rate and matric suction of all depths decrease with the increase of volumetric water content as well as the degree of saturation. Numerical modeling was used to verify and predict the relationship between infiltration-suction response and degree of saturation. Numerical models can be used to integrate the rainfall scenarios into quantitative landslide hazard assessments. Thus, development plans and mitigation measures can be designed for estimated impacts from hazard assessments based on collected data.

Insights from intercomparison of microbial and conventional soil models

NASA Astrophysics Data System (ADS)

Allison, S. D.; Li, J.; Luo, Y.; Mayes, M. A.; Wang, G.

2014-12-01

Changing the structure of soil biogeochemical models to represent coupling between microbial biomass and carbon substrate pools could improve predictions of carbon-climate feedbacks. So-called "microbial models" with this structure make very different predictions from conventional models based on first-order decay of carbon substrate pools. Still, the value of microbial models is uncertain because microbial physiological parameters are poorly constrained and model behaviors have not been fully explored. To address these issues, we developed an approach for inter-comparing microbial and conventional models. We initially focused on soil carbon responses to microbial carbon use efficiency (CUE) and temperature. Three scenarios were implemented in all models at a common reference temperature (20°C): constant CUE (held at 0.31), varied CUE (-0.016°C-1), and 50% acclimated CUE (-0.008°C-1). Whereas the conventional model always showed soil carbon losses with increasing temperature, the microbial models each predicted a temperature threshold above which warming led to soil carbon gain. The location of this threshold depended on CUE scenario, with higher temperature thresholds under the acclimated and constant scenarios. This result suggests that the temperature sensitivity of CUE and the structure of the soil carbon model together regulate the long-term soil carbon response to warming. Compared to the conventional model, all microbial models showed oscillatory behavior in response to perturbations and were much less sensitive to changing inputs. Oscillations were weakest in the most complex model with explicit enzyme pools, suggesting that multi-pool coupling might be a more realistic representation of the soil system. This study suggests that model structure and CUE parameterization should be carefully evaluated when scaling up microbial models to ecosystems and the globe.

Proximal Soil Sensing – A Contribution for Species Habitat Distribution Modelling of Earthworms in Agricultural Soils?

PubMed Central

Schirrmann, Michael; Joschko, Monika; Gebbers, Robin; Kramer, Eckart; Zörner, Mirjam; Barkusky, Dietmar; Timmer, Jens

2016-01-01

Background Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils. Methodology/Principal Findings Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species. Conclusions/Significance Our findings suggest that PSS contributes to the spatial modelling of earthworm abundances at field scale and that it will support species distribution modelling in the attempt to understand the soil-earthworm relationships in agroecosystems. PMID:27355340

Proximal Soil Sensing - A Contribution for Species Habitat Distribution Modelling of Earthworms in Agricultural Soils?

PubMed

Schirrmann, Michael; Joschko, Monika; Gebbers, Robin; Kramer, Eckart; Zörner, Mirjam; Barkusky, Dietmar; Timmer, Jens

2016-01-01

Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils. Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species. Our findings suggest that PSS contributes to the spatial modelling of earthworm abundances at field scale and that it will support species distribution modelling in the attempt to understand the soil-earthworm relationships in agroecosystems.

[Study on the polarized reflectance hyperspectral characteristics and models of typical saline soil in the west of Jilin Province, China].

PubMed

Han, Yang; Qin, Wei-chao; Wang, Ye-qiao

2014-06-01

In recent years, the area of saline soil in the west of Jilin Province expands increasingly, and soil quality is becoming more and more worsening, which not only caused great damage to the land resources, but also posed a huge threat to agricultural production and ecological environment. We combined with polarized and hyperspectral information to establish the general model and scientifically validated it. The results show that there is a strong relationship between the saline soil hyperspectral polarized information and its physicochemical property parameters, and with regularity. This paper has important theoretical significance for the mechanism of saline soil surface reflection, recognition and classification of saline soil and background, the utilization of soil polarization sensor and the development of quantitative remote sensing.

Testing of DRAINMOD for Forested Watersheds with Non-Pattern Drainage

Treesearch

Devendra M. Amatya; Ge Sun; R. Wayne Skaggs; Carl C. Trettin

2003-01-01

Models like DRAINMOD and its forestry version, DRAINLOB, have been specifically developed as a field scale model for evaluating hydrologic effects of crops (trees), soil, and water management practices for lands with pattern drainage (i.e. with parallel ditches) on relatively flat, high water table soils. These models conduct a water balance between the ditches to...

Potential soil organic carbon stocks in semi arid areas under climate change scenarios: an application of CarboSOIL model in northern Egypt

NASA Astrophysics Data System (ADS)

Muñoz-Rojas, Miriam; Abd-Elmabod, Sameh K.; Jordán, Antonio; Zavala, Lorena M.; Anaya-Romero, Maria; De la Rosa, Diego

2014-05-01

1. INTRODUCTION Climate change is predicted to have a large impact on semi arid areas which are often degraded and vulnerable to environmental changes (Muñoz-Rojas et al., 2012a; 2012b; 2013). However, these areas might play a key role in mitigation of climate change effects through sequestration of carbon in soils (United Nations, 2011). At the same time, increasing organic carbon in these environments could be beneficial for soil erosion control, soil fertility and, ultimately, food production (Lal, 2004). Several approaches have been carried out to evaluate climate change impacts on soil organic carbon (SOC) stocks, but soil carbon models are amongst the most effective tools to assess C stocks, dynamics and distribution and to predict trends under climate change scenarios (Jones et al., 2005 ). CarboSOIL is an empirical model based on regression techniques and developed to predict SOC contents at standard soil depths of 0 to 25, 25 to 50 and 50-75 cm (Muñoz-Rojas et al., 2013). CarboSOIL model has been designed as a GIS-integrated tool and is a new component of the agroecological decision support system for land evaluation MicroLEIS DSS (De la Rosa et al., 2004). 2. GENERAL METHODS In this research, CarboSOIL was applied in El-Fayoum depression, a semi arid region located in northern Egypt with a large potential for agriculture (Abd-Elmabod et al, 2012). The model was applied in a total of six soil-units classified according the USDA Soil Taxonomy system within the orders Entisols and Aridisols under different climate climate change scenarios. Global climate models based on the Organisation for Economic Co-operation and Development (Agrawala at al., 2004) and the Intergovernmental Panel on Climate Change (IPCC, 2007) were applied to predict short-, medium- and long-term trends (2030, 2050 and 2100) of SOC dynamics and sequestration at different soil depths (0-25, 25-50 and 50-75) and land use types (irrigated areas, olive groves, wheat, cotton and other annual crops, and fruit trees and berries). 3. RESULTS AND CONCLUSIONS According to results, considerable decreases of SOC stocks are expected in the 25-50 cm soil section under all considered land use types and all projected scenarios, in particular in Vertic Torrifluvents and Typic Torrifluvents under wheat, cotton and other annual crops. Oppositely, SOC stocks tend to increase in the deeper soil section (50-75 cm), mostly in Typic Haplocalcids under permanently irrigated areas and olive groves in the 2100 scenario. In the upper layer (0-25 cm), slight increases have been predicted under all considered land use types. The methodology used in this research could be applied to other semi arid areas with available soil, land use and climate data. Moreover, the information developed in this study might support decision-making for land use planning, agricultural management and climate adaptation strategies in semi arid regions. REFERENCES Abd-Elmabod, S.K., Ali, R.R., Anaya-Romero, M., Jordán, A., Muñoz-Rojas, M., Abdelmageed, T.A., Zavala, L.M., De la Rosa, D. 2012. Evaluating soil degradation under different scenarios of agricultural land management in Mediterranean region. Nature and Science 10, 103-116. Agrawala, S., A. Moehner, M. El Raey, D. Conway, M. van Aalst, M. Hagenstad and J. Smith. 2004. Development and Climate Change In Egypt: Focus on Coastal Resources and the Nile. Organisation for Economic Co-operation and Development. De la Rosa, D., Mayol, F., Moreno, F., Cabrera, F., Díaz-Pereira, E., Antoine, J. 2002. A multilingual soil profile database (SDBm Plus) as an essential part of land resources information systems. Environmental Modelling & Software 17, 721-730. DOI: 10.1016/S1364-8152(02)00031-2. IPCC. 2007. Climate Change 2007: The Physical Science Basis. Cambridge/New York: Cambridge University Press Jones, C., McConnell, C., Coleman, K., Cox, P., Falloon, P., Jenkinson, D. and Powlson, D. 2005. Global climate change and soil carbon stocks; predictions from two contrasting models for the turnover of organic carbon in soil. Global Change Biology 11: 154-166 Lal, R. 2004. Soil carbon sequestration to mitigate climate change. Geoderma 123, 1-22. DOI: 10.1016/j.geoderma.2004.01.032. Muñoz-Rojas, M., Jordán, A., Zavala, L.M., De la Rosa, D., Abd-Elmabod, S.K., Anaya-Romero, M. 2012a. Impact of land use and land cover changes on organic carbon stocks in Mediterranean soils (1956-2007). Land Degradation & Development. In press. DOI: 10.1002/ldr.2194. Muñoz-Rojas, M., Jordán, A., Zavala, L.M., De la Rosa, D., Abd-Elmabod, S.K., Anaya-Romero, M. 2012b. Organic carbon stocks in Mediterranean soil types under different land uses (Southern Spain). Solid Earth 3, 375-386. DOI: 10.5194/se-3-375-2012. Muñoz-Rojas, M., Jordán, A., Zavala, L.M., González-Peñaloza, F.A., De la Rosa, D., Anaya-Romero, M. 2013. Modelling soil organic carbon stocks in global change scenarios: a CarboSOIL application. Biogeosciences Discussions 10, 10997-11035. DOI: 10.5194/bgd-10-10997-2013. United Nations. 2011. Global Drylands: A UN system-wide response. Full Report. United Nations Environment Management Group.

Rates of soil development from four soil chronosequences in the southern Great Basin

USGS Publications Warehouse

Harden, J.W.; Taylor, E.M.; Hill, C.; Mark, R.K.; McFadden, L.D.; Reheis, M.C.; Sowers, J.M.; Wells, S.G.

1991-01-01

Four soil chronosequences in the southern Great Basin were examined in order to study and quantify soil development during the Quaternary. Soils of all four areas are developed in gravelly alluvial fans in semiarid climates with 8 to 40 cm mean annual precipitation. Lithologies of alluvium are granite-gneiss at Silver Lake, granite and basalt at Cima Volcanic Field, limestone at Kyle Canyon, and siliceous volcanic rocks at Fortymile Wash. Ages of the soils are approximated from several radiometric and experimental techniques, and rates are assessed using a conservative mathematical approach. Average rates for Holocene soils at Silver Lake are about 10 times higher than for Pleistocene soils at Kyle Canyon and Fortymile Wash, based on limited age control. Holocene soils in all four areas appear to develop at similar rates, and Pleistocene soils at Kyle Canyon and Fortymile Wash may differ by only a factor of 2 to 4. Over time spans of several millennia, a preferred model for the age curves is not linear but may be exponential or parabolic, in which rates decrease with increasing age. These preliminary results imply that the geographical variation in rates within the southern Great Basin-Mojave region may be much less significant than temporal variation in rates of soil development. The reasons for temporal variation in rates and processes of soil development are complexly linked to climatic change and related changes in water and dust, erosional history, and internally driven chemical and physical processes. ?? 1991.

Mechanistic modeling of microbial interactions at pore to profile scale resolve methane emission dynamics from permafrost soil

NASA Astrophysics Data System (ADS)

Ebrahimi, Ali; Or, Dani

2017-05-01

The sensitivity of polar regions to raising global temperatures is reflected in rapidly changing hydrological processes associated with pronounced seasonal thawing of permafrost soil and increased biological activity. Of particular concern is the potential release of large amounts of soil carbon and stimulation of other soil-borne greenhouse gas emissions such as methane. Soil methanotrophic and methanogenic microbial communities rapidly adjust their activity and spatial organization in response to permafrost thawing and other environmental factors. Soil structural elements such as aggregates and layering affect oxygen and nutrient diffusion processes thereby contributing to methanogenic activity within temporal anoxic niches (hot spots). We developed a mechanistic individual-based model to quantify microbial activity dynamics in soil pore networks considering transport processes and enzymatic activity associated with methane production in soil. The model was upscaled from single aggregates to the soil profile where freezing/thawing provides macroscopic boundary conditions for microbial activity at different soil depths. The model distinguishes microbial activity in aerate bulk soil from aggregates (or submerged profile) for resolving methane production and oxidation rates. Methane transport pathways by diffusion and ebullition of bubbles vary with hydration dynamics. The model links seasonal thermal and hydrologic dynamics with evolution of microbial community composition and function affecting net methane emissions in good agreement with experimental data. The mechanistic model enables systematic evaluation of key controlling factors in thawing permafrost and microbial response (e.g., nutrient availability and enzyme activity) on long-term methane emissions and carbon decomposition rates in the rapidly changing polar regions.

Modeling runoff generation in a small snow-dominated mountainous catchment

USDA-ARS?s Scientific Manuscript database

Snowmelt in mountainous areas is an important contributor to river water flows in the western United States. We developed a distributed model that calculates solar radiation, canopy energy balance, surface energy balance, snow pack dynamics, soil water flow, snow–soil–bedrock heat exchange, soil wat...

Predicting soil quality indices with near infrared analysis in a wildfire chronosequence.

PubMed

Cécillon, Lauric; Cassagne, Nathalie; Czarnes, Sonia; Gros, Raphaël; Vennetier, Michel; Brun, Jean-Jacques

2009-01-15

We investigated the power of near infrared (NIR) analysis for the quantitative assessment of soil quality in a wildfire chronosequence. The effect of wildfire disturbance and soil engineering activity of earthworms on soil organic matter quality was first assessed with principal component analysis of NIR spectra. Three soil quality indices were further calculated using an adaptation of the method proposed by Velasquez et al. [Velasquez, E., Lavelle, P., Andrade, M. GISQ, a multifunctional indicator of soil quality. Soil Biol Biochem 2007; 39: 3066-3080.], each one addressing an ecosystem service provided by soils: organic matter storage, nutrient supply and biological activity. Partial least squares regression models were developed to test the predicting ability of NIR analysis for these soil quality indices. All models reached coefficients of determination above 0.90 and ratios of performance to deviation above 2.8. This finding provides new opportunities for the monitoring of soil quality, using NIR scanning of soil samples.

A novel and simple model of the uptake of organic chemicals by vegetation from air and soil.

PubMed

Hung, H; Mackay, D

1997-09-01

A novel and simple three-compartment fugacity model has been developed to predict the kinetics and equilibria of the uptake of organic chemicals in herbaceous agricultural plants at various times, including the time of harvest using only readily available input data. The chemical concentration in each of the three plant compartments leaf, stem which includes fruits and seeds, and root) is expressed as a function of both time and chemical concentrations in soil and air. The model was developed using the fugacity concept; however, the final expressions are presented in terms of concentrations in soil and air, equilibrium partition coefficients and a set of transport and transformation half-lives. An illustrative application of the model is presented which describes the uptake of bromacil by a soybean plant under hydroponic conditions. The model, which is believed to give acceptably accurate prediction of the distribution of chemicals among plant tissues, air and soil, may be used for the assessment of exposure to, and risk from contaminants consumed either directly from vegetation or indirectly in natural and agricultural food chains.

Development and application of a hillslope hydrologic model

USGS Publications Warehouse

Blain, C.A.; Milly, P.C.D.

1991-01-01

A vertically integrated two-dimensional lateral flow model of soil moisture has been developed. Derivation of the governing equation is based on a physical interpretation of hillslope processes. The lateral subsurface-flow model permits variability of precipitation and evapotranspiration, and allows arbitrary specification of soil-moisture retention properties. Variable slope, soil thickness, and saturation are all accommodated. The numerical solution method, a Crank-Nicolson, finite-difference, upstream-weighted scheme, is simple and robust. A small catchment in northeastern Kansas is the subject of an application of the lateral subsurface-flow model. Calibration of the model using observed discharge provides estimates of the active porosity (0.1 cm3/cm3) and of the saturated horizontal hydraulic conductivity (40 cm/hr). The latter figure is at least an order of magnitude greater than the vertical hydraulic conductivity associated with the silty clay loam soil matrix. The large value of hydraulic conductivity derived from the calibration is suggestive of macropore-dominated hillslope drainage. The corresponding value of active porosity agrees well with a published average value of the difference between total porosity and field capacity for a silty clay loam. ?? 1991.

Predicting Soil Organic Carbon and Total Nitrogen in the Russian Chernozem from Depth and Wireless Color Sensor Measurements

NASA Astrophysics Data System (ADS)

Mikhailova, E. A.; Stiglitz, R. Y.; Post, C. J.; Schlautman, M. A.; Sharp, J. L.; Gerard, P. D.

2017-12-01

Color sensor technologies offer opportunities for affordable and rapid assessment of soil organic carbon (SOC) and total nitrogen (TN) in the field, but the applicability of these technologies may vary by soil type. The objective of this study was to use an inexpensive color sensor to develop SOC and TN prediction models for the Russian Chernozem (Haplic Chernozem) in the Kursk region of Russia. Twenty-one dried soil samples were analyzed using a Nix Pro™ color sensor that is controlled through a mobile application and Bluetooth to collect CIEL*a*b* (darkness to lightness, green to red, and blue to yellow) color data. Eleven samples were randomly selected to be used to construct prediction models and the remaining ten samples were set aside for cross validation. The root mean squared error (RMSE) was calculated to determine each model's prediction error. The data from the eleven soil samples were used to develop the natural log of SOC (lnSOC) and TN (lnTN) prediction models using depth, L*, a*, and b* for each sample as predictor variables in regression analyses. Resulting residual plots, root mean square errors (RMSE), mean squared prediction error (MSPE) and coefficients of determination ( R 2, adjusted R 2) were used to assess model fit for each of the SOC and total N prediction models. Final models were fit using all soil samples, which included depth and color variables, for lnSOC ( R 2 = 0.987, Adj. R 2 = 0.981, RMSE = 0.003, p-value < 0.001, MSPE = 0.182) and lnTN ( R 2 = 0.980 Adj. R 2 = 0.972, RMSE = 0.004, p-value < 0.001, MSPE = 0.001). Additionally, final models were fit for all soil samples, which included only color variables, for lnSOC ( R 2 = 0.959 Adj. R 2 = 0.949, RMSE = 0.007, p-value < 0.001, MSPE = 0.536) and lnTN ( R 2 = 0.912 Adj. R 2 = 0.890, RMSE = 0.015, p-value < 0.001, MSPE = 0.001). The results suggest that soil color may be used for rapid assessment of SOC and TN in these agriculturally important soils.

Modelling soil carbon flows and stocks following a carbon balance approach at regional scale for the EU-27

NASA Astrophysics Data System (ADS)

Lesschen, Jan Peter; Sikirica, Natasa; Bonten, Luc; Dibari, Camilla; Sanchez, Berta; Kuikman, Peter

2014-05-01

Soil Organic Carbon (SOC) is a key parameter to many soil functions and services. SOC is essential to support water retention and nutrient buffering and mineralization in the soil as well as to enhance soil biodiversity. Consequently, loss of SOC or low SOC levels might threaten soil productivity or even lead to a collapse of a farming system. Identification of areas in Europe with critically low SOC levels or with a negative carbon balance is a challenge in order to apply the appropriate strategies to restore these areas or prevent further SOC losses. The objective of this study is to assess current soil carbon flows and stocks at a regional scale; we follow a carbon balance approach which we developed within the MITERRA-Europe model. MITERRA-Europe is an environmental impact assessment model and calculates nitrogen and greenhouse emission on a deterministic and annual basis using emission and leaching factors at regional level (NUTS2, comparable to province level) in the EU27. The model already contained a soil carbon module based on the IPCC stock change approach. Within the EU FP7 SmartSoil project we developed a SOC balance approach, for which we quantified the input of carbon (manure, crop residues, other organic inputs) and the losses of carbon (decomposition, leaching and erosion). The calculations rules from the Roth-C model were used to estimate SOC decomposition. For the actual soil carbon stocks we used the data from the LUCAS soil sample survey. LUCAS collected soil samples in 2009 at about 22000 locations across the EU, which were analysed for a range of soil properties. Land management practices are accounted for, based on data from the EU wide Survey on Agricultural Production Methods in the 2010 Farm Structure Survey. The survey comprises data on the application of soil tillage, soil cover, crop rotation and irrigation. Based on the simulated soil carbon balance and the actual carbon stocks from LUCAS we now can identify regions within the EU that are at risk. We further present results of the potential soil carbon sequestration by land management practices, such as cover crops, zero and reduced tillage, crop residue management and additional input of organic carbon. These results will be relevant for defining region specific strategies to reach the policy target on preventing loss of soil organic matter as stipulated in the Roadmap to a Resource Efficient Europe.

Soil Moisture Estimate under Forest using a Semi-empirical Model at P-Band

NASA Astrophysics Data System (ADS)

Truong-Loi, M.; Saatchi, S.; Jaruwatanadilok, S.

2013-12-01

In this paper we show the potential of a semi-empirical algorithm to retrieve soil moisture under forests using P-band polarimetric SAR data. In past decades, several remote sensing techniques have been developed to estimate the surface soil moisture. In most studies associated with radar sensing of soil moisture, the proposed algorithms are focused on bare or sparsely vegetated surfaces where the effect of vegetation can be ignored. At long wavelengths such as L-band, empirical or physical models such as the Small Perturbation Model (SPM) provide reasonable estimates of surface soil moisture at depths of 0-5cm. However for densely covered vegetated surfaces such as forests, the problem becomes more challenging because the vegetation canopy is a complex scattering environment. For this reason there have been only few studies focusing on retrieving soil moisture under vegetation canopy in the literature. Moghaddam et al. developed an algorithm to estimate soil moisture under a boreal forest using L- and P-band SAR data. For their studied area, double-bounce between trunks and ground appear to be the most important scattering mechanism. Thereby, they implemented parametric models of radar backscatter for double-bounce using simulations of a numerical forest scattering model. Hajnsek et al. showed the potential of estimating the soil moisture under agricultural vegetation using L-band polarimetric SAR data and using polarimetric-decomposition techniques to remove the vegetation layer. Here we use an approach based on physical formulation of dominant scattering mechanisms and three parameters that integrates the vegetation and soil effects at long wavelengths. The algorithm is a simplification of a 3-D coherent model of forest canopy based on the Distorted Born Approximation (DBA). The simplified model has three equations and three unknowns, preserving the three dominant scattering mechanisms of volume, double-bounce and surface for three polarized backscattering coefficients: σHH, σVV and σHV. The inversion process, which is not an ill-posed problem, uses the non-linear optimization method of Levenberg-Marquardt and estimates the three model parameters: vegetation aboveground biomass, average soil moisture and surface roughness. The model analytical formulation will be first recalled and sensitivity analyses will be shown. Then some results obtained with real SAR data will be presented and compared to ground estimates.

Modelling spatiotemporal distribution patterns of earthworms in order to indicate hydrological soil processes

NASA Astrophysics Data System (ADS)

Palm, Juliane; Klaus, Julian; van Schaik, Loes; Zehe, Erwin; Schröder, Boris

2010-05-01

Soils provide central ecosystem functions in recycling nutrients, detoxifying harmful chemicals as well as regulating microclimate and local hydrological processes. The internal regulation of these functions and therefore the development of healthy and fertile soils mainly depend on the functional diversity of plants and animals. Soil organisms drive essential processes such as litter decomposition, nutrient cycling, water dynamics, and soil structure formation. Disturbances by different soil management practices (e.g., soil tillage, fertilization, pesticide application) affect the distribution and abundance of soil organisms and hence influence regulating processes. The strong relationship between environmental conditions and soil organisms gives us the opportunity to link spatiotemporal distribution patterns of indicator species with the potential provision of essential soil processes on different scales. Earthworms are key organisms for soil function and affect, among other things, water dynamics and solute transport in soils. Through their burrowing activity, earthworms increase the number of macropores by building semi-permanent burrow systems. In the unsaturated zone, earthworm burrows act as preferential flow pathways and affect water infiltration, surface-, subsurface- and matrix flow as well as the transport of water and solutes into deeper soil layers. Thereby different ecological earthworm types have different importance. Deep burrowing anecic earthworm species (e.g., Lumbricus terrestris) affect the vertical flow and thus increase the risk of potential contamination of ground water with agrochemicals. In contrast, horizontal burrowing endogeic (e.g., Aporrectodea caliginosa) and epigeic species (e.g., Lumbricus rubellus) increase water conductivity and the diffuse distribution of water and solutes in the upper soil layers. The question which processes are more relevant is pivotal for soil management and risk assessment. Thus, finding relevant environmental predictors which explain the distribution and dynamics of different ecological earthworm types can help us to understand where or when these processes are relevant in the landscape. Therefore, we develop species distribution models which are a useful tool to predict spatiotemporal distributions of earthworm occurrence and abundance under changing environmental conditions. On field scale, geostatistical distribution maps have shown that the spatial distribution of earthworms depends on soil parameters such as food supply, soil moisture, bulk density but with different patterns for earthworm stages (adult, juvenile) and ecological types (anecic, endogeic, epigeic). On landscape scales, earthworm distribution seems to be strongly controlled by management/disturbance-related factors. Our study shows different modelling approaches for predicting distribution patterns of earthworms in the Weiherbach area, an agricultural site in Kraichtal (Baden-Württemberg, Germany). We carried out field studies on arable fields differing in soil management practices (conventional, conservational), soil properties (organic matter content, texture, soil moisture), and topography (slope, elevation) in order to identify predictors for earthworm occurrence, abundance and biomass. Our earthworm distribution models consider all ecological groups as well as different life stages, accounting for the fact that the activity of juveniles is sometimes different from those of adults. Within our BIOPORE-project it is our final goal to couple our distribution models with population dynamic models and a preferential flow model to an integrated ecohydrological model to analyse feedbacks between earthworm engineering and transport characteristics affecting the functioning of (agro-) ecosystems.

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.

Off-Road Soft Soil Tire Model Development and Experimental Testing

DTIC Science & Technology

2011-06-29

Eduardo Pinto 2 , Mr. Scott Naranjo 3 , Dr. Paramsothy Jayakumar 4 , Dr. Archie Andonian 5 , Dr. Dave Hubbell 6 , Dr. Brant Ross 7 1Virginia...The effect of soil charac- teristics on the tire dynamics will be studied. Validation against data collected from full vehicle testing is included in...the proposed future work. Keywords: tire model, soft soil, terramechanics, vehicle dynamics , indoor testing 1 Introduction The goal of this paper is

Hungarian contribution to the Global Soil Organic Carbon Map (GSOC17) using advanced machine learning algorithms and geostatistics

NASA Astrophysics Data System (ADS)

Szatmári, Gábor; Laborczi, Annamária; Takács, Katalin; Pásztor, László

2017-04-01

The knowledge about soil organic carbon (SOC) baselines and changes, and the detection of vulnerable hot spots for SOC losses and gains under climate change and changed land management is still fairly limited. Thus Global Soil Partnership (GSP) has been requested to develop a global SOC mapping campaign by 2017. GSPs concept builds on official national data sets, therefore, a bottom-up (country-driven) approach is pursued. The elaborated Hungarian methodology suits the general specifications of GSOC17 provided by GSP. The input data for GSOC17@HU mapping approach has involved legacy soil data bases, as well as proper environmental covariates related to the main soil forming factors, such as climate, organisms, relief and parent material. Nowadays, digital soil mapping (DSM) highly relies on the assumption that soil properties of interest can be modelled as a sum of a deterministic and stochastic component, which can be treated and modelled separately. We also adopted this assumption in our methodology. In practice, multiple regression techniques are commonly used to model the deterministic part. However, this global (and usually linear) models commonly oversimplify the often complex and non-linear relationship, which has a crucial effect on the resulted soil maps. Thus, we integrated machine learning algorithms (namely random forest and quantile regression forest) in the elaborated methodology, supposing then to be more suitable for the problem in hand. This approach has enable us to model the GSOC17 soil properties in that complex and non-linear forms as the soil itself. Furthermore, it has enable us to model and assess the uncertainty of the results, which is highly relevant in decision making. The applied methodology has used geostatistical approach to model the stochastic part of the spatial variability of the soil properties of interest. We created GSOC17@HU map with 1 km grid resolution according to the GSPs specifications. The map contributes to the GSPs GSOC17 proposals, as well as to the development of global soil information system under GSP Pillar 4 on soil data and information. However, we elaborated our adherent code (created in R software environment) in such a way that it can be improved, specified and applied for further uses. Hence, it opens the door to create countrywide map(s) with higher grid resolution for SOC (or other soil related properties) using the advanced methodology, as well as to contribute and support the SOC (or other soil) related country level decision making. Our paper will present the soil mapping methodology itself, the resulted GSOC17@HU map, some of our conclusions drawn from the experiences and their effects on the further uses. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Aspects of spatial and temporal aggregation in estimating regional carbon dioxide fluxes from temperate forest soils

NASA Technical Reports Server (NTRS)

Kicklighter, David W.; Melillo, Jerry M.; Peterjohn, William T.; Rastetter, Edward B.; Mcguire, A. David; Steudler, Paul A.; Aber, John D.

1994-01-01

We examine the influence of aggregation errors on developing estimates of regional soil-CO2 flux from temperate forests. We find daily soil-CO2 fluxes to be more sensitive to changes in soil temperatures (Q(sub 10) = 3.08) than air temperatures (Q(sub 10) = 1.99). The direct use of mean monthly air temperatures with a daily flux model underestimates regional fluxes by approximately 4%. Temporal aggregation error varies with spatial resolution. Overall, our calibrated modeling approach reduces spatial aggregation error by 9.3% and temporal aggregation error by 15.5%. After minimizing spatial and temporal aggregation errors, mature temperate forest soils are estimated to contribute 12.9 Pg C/yr to the atmosphere as carbon dioxide. Georeferenced model estimates agree well with annual soil-CO2 fluxes measured during chamber studies in mature temperate forest stands around the globe.

Simulation of salinity effects on past, present, and future soil organic carbon stocks.

PubMed

Setia, Raj; Smith, Pete; Marschner, Petra; Gottschalk, Pia; Baldock, Jeff; Verma, Vipan; Setia, Deepika; Smith, Jo

2012-02-07

Soil organic carbon (SOC) models are used to predict changes in SOC stocks and carbon dioxide (CO(2)) emissions from soils, and have been successfully validated for non-saline soils. However, SOC models have not been developed to simulate SOC turnover in saline soils. Due to the large extent of salt-affected areas in the world, it is important to correctly predict SOC dynamics in salt-affected soils. To close this knowledge gap, we modified the Rothamsted Carbon Model (RothC) to simulate SOC turnover in salt-affected soils, using data from non-salt-affected and salt-affected soils in two agricultural regions in India (120 soils) and in Australia (160 soils). Recently we developed a decomposition rate modifier based on an incubation study of a subset of these soils. In the present study, we introduce a new method to estimate the past losses of SOC due to salinity and show how salinity affects future SOC stocks on a regional scale. Because salinity decreases decomposition rates, simulations using the decomposition rate modifier for salinity suggest an accumulation of SOC. However, if the plant inputs are also adjusted to reflect reduced plant growth under saline conditions, the simulations show a significant loss of soil carbon in the past due to salinization, with a higher average loss of SOC in Australian soils (55 t C ha(-1)) than in Indian soils (31 t C ha(-1)). There was a significant negative correlation (p < 0.05) between SOC loss and osmotic potential. Simulations of future SOC stocks with the decomposition rate modifier and the plant input modifier indicate a greater decrease in SOC in saline than in non-saline soils under future climate. The simulations of past losses of SOC due to salinity were repeated using either measured charcoal-C or the inert organic matter predicted by the Falloon et al. equation to determine how much deviation from the Falloon et al. equation affects the amount of plant inputs generated by the model for the soils used in this study. Both sets of results suggest that saline soils have lost carbon and will continue to lose carbon under future climate. This demonstrates the importance of both reduced decomposition and reduced plant input in simulations of future changes in SOC stocks in saline soils.

Influence of landscape position and transient water table on soil development and carbon distribution in a steep, headwater catchment

Treesearch

Scott W. Bailey; Patricia A. Brousseau; Kevin J. McGuire; Donald S. Ross

2014-01-01

Upland headwater catchments, such as those in the AppalachianMountain region, are typified by coarse textured soils, flashy hydrologic response, and low baseflow of streams, suggesting well drained soils and minimal groundwater storage. Model formulations of soil genesis, nutrient cycling, critical loads and rainfall/runoff response are typically based on vertical...

The evolution of concepts for soil erosion modelling

NASA Astrophysics Data System (ADS)

Kirkby, Mike

2013-04-01

From the earliest models for soil erosion, based on power laws relating sediment discharge or yield to slope length and gradient, the development of the Universal Soil Loss Equation was a natural step, although one that has long continued to hinder the development of better perceptual models for erosion processes. Key stumbling blocks have been: 1. The failure to go through runoff generation as a key intermediary 2. The failure to separate hydrological and strength parameters of the soil 3. The failure to treat sediment transport along a slope as a routing problem 4. The failure to analyse the nature of the dependence on vegetation Key advances have been in these directions (among others) 1. Improved understanding of the hydrological processes (e.g. infiltration and runoff, sediment entrainment) leading to KINEROS, LISEM,WEPP, PESERA 2. Recognition of selective sediment transport (e.g. transport- or supply-limited removal, grain travel distances) leading e.g. to MAHLERAN 3. Development of models adapted to particular time/space scales Some major remaining problems 1. Failure to integrate geomorphological and agronomic approaches 2. Tillage erosion - Is erosion loss of sediment or lowering of centre of mass? 3. Dynamic change during an event, as rills etc form.

A loess-paleosol record of climate and glacial history over the past two glacial-interglacial cycles (~140 ka), southern Jackson Hole, Wyoming

USGS Publications Warehouse

Pierce, Kenneth L.; Muhs, Daniel R.; Fosberg, Maynard A.; Mahan, Shannon; Rosenbaum, Joseph G.; Licciardi, Joseph M.; Pavich, Milan J.

2011-01-01

Loess accumulated on a Bull Lake outwash terrace of Marine Oxygen Isotope Stage 6 (MIS 6) age in southern Jackson Hole, Wyoming. The 9 m section displays eight intervals of loess deposition (Loess 1 to Loess 8, oldest), each followed by soil development. Our age-depth model is constrained by thermoluminescence, meteoric Be-10 accumulation in soils, and cosmogenic Be-10 surface exposure ages. We use particle size, geochemical, mineral-magnetic, and clay mineralogical data to interpret loess sources and pedogenesis. Deposition of MIS 6 loess was followed by a tripartite soil/thin loess complex (Soils 8,7, and 6) apparently reflecting the large climatic oscillations of MIS 5. Soil 8 (MIS 5e) shows the strongest development. Loess 5 accumulated during a glacial interval (similar to 76-69 ka; MIS 4) followed by soil development under conditions wetter and probably colder than present. Deposition of thick Loess 3 (similar to 43-51 ka, MIS 3) was followed by soil development comparable with that observed in Soil 1. Loess 1 (MIS 2) accumulated during the Pinedale glaciation and was followed by development of Soil 1 under a semiarid climate. This record of alternating loess deposition and soil development is compatible with the history of Yellowstone vegetation and the glacial flour record from the Sierra Nevada. Published by Elsevier Inc. on behalf of University of Washington.

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.

Mechanistic modeling of thermo-hydrological processes and microbial interactions at pore to profile scales resolve methane emission dynamics from permafrost soil

NASA Astrophysics Data System (ADS)

Ebrahimi, Ali; Or, Dani

2017-04-01

The sensitivity of the Earth's polar regions to raising global temperatures is reflected in rapidly changing hydrological processes with pronounced seasonal thawing of permafrost soil and increased biological activity. Of particular concern is the potential release of large amounts of soil carbon and the stimulation of other soil-borne GHG emissions such as methane. Soil methanotrophic and methanogenic microbial communities rapidly adjust their activity and spatial organization in response to permafrost thawing and a host of other environmental factors. Soil structural elements such as aggregates and layering and hydration status affect oxygen and nutrient diffusion processes thereby contributing to methanogenic activity within temporal anoxic niches (hotspots or hot-layers). We developed a mechanistic individual based model to quantify microbial activity dynamics within soil pore networks considering, hydration, temperature, transport processes and enzymatic activity associated with methane production in soil. The model was the upscaled from single aggregates (or hotspots) to quantifying emissions from soil profiles in which freezing/thawing processes provide macroscopic boundary conditions for microbial activity at different soil depths. The model distinguishes microbial activity in aerate bulk soil from aggregates (or submerged parts of the profile) for resolving methane production and oxidation rates. Methane transport pathways through soil by diffusion and ebullition of bubbles vary with hydration dynamics and affect emission patterns. The model links seasonal thermal and hydrologic dynamics with evolution of microbial community composition and function affecting net methane emissions in good agreement with experimental data. The mechanistic model enables systematic evaluation of key controlling factors in thawing permafrost and microbial response (e.g., nutrient availability, enzyme activity, PH) on long term methane emissions and carbon decomposition rates in the rapidly changing polar regions.

Representing life in the Earth system with soil microbial functional traits in the MIMICS model

NASA Astrophysics Data System (ADS)

Wieder, W. R.; Grandy, A. S.; Kallenbach, C. M.; Taylor, P. G.; Bonan, G. B.

2015-02-01

Projecting biogeochemical responses to global environmental change requires multi-scaled perspectives that consider organismal diversity, ecosystem processes and global fluxes. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon cycle-climate feedbacks. We used a microbial trait-based soil carbon (C) model, with two physiologically distinct microbial communities to improve current estimates of soil C storage and their likely response to perturbations. Drawing from the application of functional traits used to model other ecosystems, we incorporate copiotrophic and oligotrophic microbial functional groups in the MIcrobial-MIneral Carbon Stabilization (MIMICS) model, which incorporates oligotrophic and copiotrophic functional groups, akin to "gleaner" vs. "opportunist" plankton in the ocean, or r vs. K strategists in plant and animals communities. Here we compare MIMICS to a conventional soil C model, DAYCENT, in cross-site comparisons of nitrogen (N) enrichment effects on soil C dynamics. MIMICS more accurately simulates C responses to N enrichment; moreover, it raises important hypotheses involving the roles of substrate availability, community-level enzyme induction, and microbial physiological responses in explaining various soil biogeochemical responses to N enrichment. In global-scale analyses, we show that current projections from Earth system models likely overestimate the strength of the land C sink in response to increasing C inputs with elevated carbon dioxide (CO2). Our findings illustrate that tradeoffs between theory and utility can be overcome to develop soil biogeochemistry models that evaluate and advance our theoretical understanding of microbial dynamics and soil biogeochemical responses to environmental change.

A mechanistic, globally-applicable model of plant nitrogen uptake, retranslocation and fixation

NASA Astrophysics Data System (ADS)

Fisher, J. B.; Tan, S.; Malhi, Y.; Fisher, R. A.; Sitch, S.; Huntingford, C.

2008-12-01

Nitrogen is one of the nutrients that can most limit plant growth, and nitrogen availability may be a controlling factor on biosphere responses to climate change. We developed a plant nitrogen assimilation model based on a) advective transport through the transpiration stream, b) retranslocation whereby carbon is expended to resorb nitrogen from leaves, c) active uptake whereby carbon is expended to acquire soil nitrogen, and d) biological nitrogen fixation whereby carbon is expended for symbiotic nitrogen fixers. The model relies on 9 inputs: 1) net primary productivity (NPP), 2) plant C:N ratio, 3) available soil nitrogen, 4) root biomass, 5) transpiration rate, 6) saturated soil depth,7) leaf nitrogen before senescence, 8) soil temperature, and 9) ability to fix nitrogen. A carbon cost of retranslocation is estimated based on leaf nitrogen and compared to an active uptake carbon cost based on root biomass and available soil nitrogen; for nitrogen fixers both costs are compared to a carbon cost of fixation dependent on soil temperature. The NPP is then allocated to optimize growth while maintaining the C:N ratio. The model outputs are total plant nitrogen uptake, remaining NPP available for growth, carbon respired to the soil and updated available soil nitrogen content. We test and validate the model (called FUN: Fixation and Uptake of Nitrogen) against data from the UK, Germany and Peru, and run the model under simplified scenarios of primary succession and climate change. FUN is suitable for incorporation into a land surface scheme of a General Circulation Model and will be coupled with a soil model and dynamic global vegetation model as part of a land surface model (JULES).

Impacts of climate variability and extreme events on soil hydrological processes

NASA Astrophysics Data System (ADS)

Ramos, M. C.; Mulligan, M.

2003-04-01

The Mediterranean climate (dry subhumid), characterised by a high variability, produces in many situations an insufficient water supply to support stable agriculture. Not only is there insufficient rainfall, but its occurrence is also highly variable between years, during the year, and spatially, during a single rainfall event. One of the main climatic characteristics affecting the vulnerability of the Mediterranean region is the high intensity rainfalls which fall after a very dry summer and the high degree of climatic fluctuation in the short and long term, especially in rainfall quantity. In addition, the rainwater penetration and storage of water in the soil are conditioned by the soil characteristics, in some cases modified by changes in land use and with new management practices. The aim of this study was to evaluate the impact of this high variability, from year to year and through the year, on soil hydrological processes, in fields resulted of the mechanisation works in vineyards in a Mediterranean environment. The PATTERNlight model, a simplified two-dimensional version of the hydrological and growth PATTERN model (Mulligan, 1996) is used here to simulate the water balance for three situations: normal, wet and dry years. Ssignificant differences in soil moisture and recharge were observed under vine culture from year to year, giving rise very often, to critical situations for the development of the crops. The distribution of the rainfall through the year together with the intensity of the recorded rainfalls is much very significant for soil hydrology than the total annual rainfall. Very low soil moisture conditions are raised when spring rainfall is scarce, which contribute to exhaustion of profile soil water over the summer, especially if the antecedent soil moisture is low. This low soil moisture has a significant effect on the development of the vine crop. The simulations of leaf and root biomass carried out with the PATTERNLIGHT model indicate the differences in the development of the leaf biomass between wet and dry conditions, especially with dry springs. Wet conditions favour the development of root and leaf biomass in a significant way. Mulligan, M., 1996. Modelling the hydrology of vegetation competition in a degrade semiarid environment. PhD Theses. Department of Geography, King's College London, University of London.

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

Comparative analysis of tree classification models for detecting fusarium oxysporum f. sp cubense (TR4) based on multi soil sensor parameters

NASA Astrophysics Data System (ADS)

Estuar, Maria Regina Justina; Victorino, John Noel; Coronel, Andrei; Co, Jerelyn; Tiausas, Francis; Señires, Chiara Veronica

2017-09-01

Use of wireless sensor networks and smartphone integration design to monitor environmental parameters surrounding plantations is made possible because of readily available and affordable sensors. Providing low cost monitoring devices would be beneficial, especially to small farm owners, in a developing country like the Philippines, where agriculture covers a significant amount of the labor market. This study discusses the integration of wireless soil sensor devices and smartphones to create an application that will use multidimensional analysis to detect the presence or absence of plant disease. Specifically, soil sensors are designed to collect soil quality parameters in a sink node from which the smartphone collects data from via Bluetooth. Given these, there is a need to develop a classification model on the mobile phone that will report infection status of a soil. Though tree classification is the most appropriate approach for continuous parameter-based datasets, there is a need to determine whether tree models will result to coherent results or not. Soil sensor data that resides on the phone is modeled using several variations of decision tree, namely: decision tree (DT), best-fit (BF) decision tree, functional tree (FT), Naive Bayes (NB) decision tree, J48, J48graft and LAD tree, where decision tree approaches the problem by considering all sensor nodes as one. Results show that there are significant differences among soil sensor parameters indicating that there are variances in scores between the infected and uninfected sites. Furthermore, analysis of variance in accuracy, recall, precision and F1 measure scores from tree classification models homogeneity among NBTree, J48graft and J48 tree classification models.

Constraining the 2012-2014 growing season Alaskan methane budget using CARVE aircraft measurements

NASA Astrophysics Data System (ADS)

Hartery, S.; Chang, R. Y. W.; Commane, R.; Lindaas, J.; Miller, S. M.; Wofsy, S. C.; Karion, A.; Sweeney, C.; Miller, C. E.; Dinardo, S. J.; Steiner, N.; McDonald, K. C.; Watts, J. D.; Zona, D.; Oechel, W. C.; Kimball, J. S.; Henderson, J.; Mountain, M. E.

2015-12-01

Soil in northen latitudes contains rich carbon stores which have been historically preserved via permafrost within the soil bed; however, recent surface warming in these regions is allowing deeper soil layers to thaw, influencing the net carbon exchange from these areas. Due to the extreme nature of its climate, these eco-regions remain poorly understood by most global models. In this study we analyze methane fluxes from Alaska using in situ aircraft observations from the 2012-2014 Carbon in Arctic Reservoir Vulnerability Experiment (CARVE). These observations are coupled with an atmospheric particle transport model which quantitatively links surface emissions to atmospheric observations to make regional methane emission estimates. The results of this study are two-fold. First, the inter-annual variability of the methane emissions was found to be <1 Tg over the area of interest and is largely influenced by the length of time the deep soil remains unfrozen. Second, the resulting methane flux estimates and mean soil parameters were used to develop an empirical emissions model to help spatially and temporally constrain the methane exchange at the Alaskan soil surface. The empirical emissions model will provide a basis for exploring the sensitivity of methane emissions to subsurface soil temperature, soil moisture, organic carbon content, and other parameters commonly used in process-based models.

Plant, soil, and shadow reflectance components of row crops

NASA Technical Reports Server (NTRS)

Richardson, A. J.; Wiegand, C. L.; Gausman, H. W.; Cuellar, J. A.; Gerbermann, A. H.

1975-01-01

Data from the first Earth Resource Technology Satellite (LANDSAT-1) multispectral scanner (MSS) were used to develop three plant canopy models (Kubelka-Munk (K-M), regression, and combined K-M and regression models) for extracting plant, soil, and shadow reflectance components of cropped fields. The combined model gave the best correlation between MSS data and ground truth, by accounting for essentially all of the reflectance of plants, soil, and shadow between crop rows. The principles presented can be used to better forecast crop yield and to estimate acreage.

Pedotransfer Functions in Earth System Science: Challenges and Perspectives

NASA Astrophysics Data System (ADS)

Van Looy, Kris; Bouma, Johan; Herbst, Michael; Koestel, John; Minasny, Budiman; Mishra, Umakant; Montzka, Carsten; Nemes, Attila; Pachepsky, Yakov A.; Padarian, José; Schaap, Marcel G.; Tóth, Brigitta; Verhoef, Anne; Vanderborght, Jan; van der Ploeg, Martine J.; Weihermüller, Lutz; Zacharias, Steffen; Zhang, Yonggen; Vereecken, Harry

2017-12-01

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.

Using a System Model for Irrigation Management

NASA Astrophysics Data System (ADS)

de Souza, Leonardo; de Miranda, Eu; Sánchez-Román, Rodrigo; Orellana-González, Alba

2014-05-01

When using Systems Thinking variables involved in any process have a dynamic behavior, according to nonstatic relationships with the environment. In this paper it is presented a system dynamics model developed to be used as an irrigation management tool. The model involves several parameters related to irrigation such as: soil characteristics, climate data and culture's physiological parameters. The water availability for plants in the soil is defined as a stock in the model, and this soil water content will define the right moment to irrigate and the water depth required to be applied. The crop water consumption will reduce soil water content; it is defined by the potential evapotranspiration (ET) that acts as an outflow from the stock (soil water content). ET can be estimated by three methods: a) FAO Penman-Monteith (ETPM), b) Hargreaves-Samani (ETHS) method, based on air temperature data and c) Class A pan (ETTCA) method. To validate the model were used data from the States of Ceará and Minas Gerais, Brazil, and the culture was bean. Keyword: System Dynamics, soil moisture content, agricultural water balance, irrigation scheduling.

Modeling the plant-soil interaction in presence of heavy metal pollution and acidity variations.

PubMed

Guala, Sebastián; Vega, Flora A; Covelo, Emma F

2013-01-01

On a mathematical interaction model, developed to model metal uptake by plants and the effects on their growth, we introduce a modification which considers also effects on variations of acidity in soil. The model relates the dynamics of the uptake of metals from soil to plants and also variations of uptake according to the acidity level. Two types of relationships are considered: total and available metal content. We suppose simple mathematical assumptions in order to get as simple as possible expressions with the aim of being easily tested in experimental problems. This work introduces modifications to two versions of the model: on the one hand, the expression of the relationship between the metal in soil and the concentration of the metal in plants and, on the other hand, the relationship between the metal in the soil and total amount of the metal in plants. The fine difference of both versions is fundamental at the moment to consider the tolerance and capacity of accumulation of pollutants in the biomass from the soil.

An Efficient Approach to Modeling the Topographic Control of Surface Hydrology for Regional and Global Climate Modeling.

NASA Astrophysics Data System (ADS)

Stieglitz, Marc; Rind, David; Famiglietti, James; Rosenzweig, Cynthia

1997-01-01

The current generation of land-surface models used in GCMs view the soil column as the fundamental hydrologic unit. While this may be effective in simulating such processes as the evolution of ground temperatures and the growth/ablation of a snowpack at the soil plot scale, it effectively ignores the role topography plays in the development of soil moisture heterogeneity and the subsequent impacts of this soil moisture heterogeneity on watershed evapotranspiration and the partitioning of surface fluxes. This view also ignores the role topography plays in the timing of discharge and the partitioning of discharge into surface runoff and baseflow. In this paper an approach to land-surface modeling is presented that allows us to view the watershed as the fundamental hydrologic unit. The analytic form of TOPMODEL equations are incorporated into the soil column framework and the resulting model is used to predict the saturated fraction of the watershed and baseflow in a consistent fashion. Soil moisture heterogeneity represented by saturated lowlands subsequently impacts the partitioning of surface fluxes, including evapotranspiration and runoff. The approach is computationally efficient, allows for a greatly improved simulation of the hydrologic cycle, and is easily coupled into the existing framework of the current generation of single column land-surface models. Because this approach uses the statistics of the topography rather than the details of the topography, it is compatible with the large spatial scales of today's regional and global climate models. Five years of meteorological and hydrological data from the Sleepers River watershed located in the northeastern United States where winter snow cover is significant were used to drive the new model. Site validation data were sufficient to evaluate model performance with regard to various aspects of the watershed water balance, including snowpack growth/ablation, the spring snowmelt hydrograph, storm hydrographs, and the seasonal development of watershed evapotranspiration and soil moisture.

Soils as Sediment database: closing a gap between soil science and geomorphology

NASA Astrophysics Data System (ADS)

Kuhn, Nikolaus J.

2016-04-01

Soils are an interface between the Earth's spheres and shaped by the nature of the interaction between them. The relevance of soil properties for the nature of the interaction between atmosphere, hydrosphere and biosphere is well-studied and accepted, on point- or ecotone-scale. However, this understanding of the largely vertical connections between spheres is not matched by a similar recognition of soil properties affecting processes acting largely in a lateral way across the land surface, such as erosion, transport and deposition of soil. Key areas where such an understanding is essential are all issues related to the lateral movement of soil-bound substances that affect the nature of soils itself, as well as water or vegetation downslope from the source area. The redistribution of eroded soil falls several disciplines, most notably soil science, agronomy, hydrology and geomorphology. Accordingly, the way sediment is described differs: in soil science, aggregation and structure are essential properties, while most process-based soil erosion models treat soil as a mixture of individual mineral grains, based on concepts derived in fluvial geomorphology or civil engineering. The actual behavior of aggregated sediment is not reflected by either approach and difficult to capture due to the dynamic nature of aggregation, especially in an environment such as running water. Still, a proxy to assess the uncertainties introduced by aggregation on the behavior of soil as sediment would represent a step forward. To develop such a proxy, a database collating relevant soil and sediment properties could serve as an initial step to identify which soil types and erosion scenarios are prone to generate a high uncertainty compared to the use of soil texture in erosion models. Furthermore, it could serve to develop standardized analytical procedures for appropriate description of soil as sediment.

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...

Projected irrigation requirements for upland crops using soil moisture model under climate change in South Korea

USDA-ARS?s Scientific Manuscript database

An increase in abnormal climate change patterns and unsustainable irrigation in uplands cause drought and affect agricultural water security, crop productivity, and price fluctuations. In this study, we developed a soil moisture model to project irrigation requirements (IR) for upland crops under cl...

WEPP model implementation project with the USDA-Natural Resources Conservation Service

USDA-ARS?s Scientific Manuscript database

The Water Erosion Prediction Project (WEPP) is a physical process-based soil erosion model that can be used to estimate runoff, soil loss, and sediment yield from hillslope profiles, fields, and small watersheds. Initially developed from 1985-1995, WEPP has been applied and validated across a wide r...

MODELING MICROBIAL TRANSPORT IN SOIL AND GROUNDWATER: MICROBIOLOGISTS CAN ASSIST IN THE DEVELOPMENT OF MODELS OF CONTAMINANT TRANSPORT

EPA Science Inventory

A large body of literature describes the processes affecting the fate of microorganisms in the subsurface environment (i.e., soil and groundwater). The fate of microorganisms depends on two main components: survival and transport. other components must be considered when determin...

Constitutive and numerical modeling of soil and soil-pile interaction for 3D applications and Kealakaha stream bridge case study.

DOT National Transportation Integrated Search

2011-12-01

This study is concerned with developing new modeling tools for predicting the response of the new Kealakaha : Stream Bridge to static and dynamic loads, including seismic shaking. The bridge will span 220 meters, with the : deck structure being curve...

Towards a better understanding of the cracking behavior in soils

USDA-ARS?s Scientific Manuscript database

Understanding and modeling shrinkage-induced cracks helps bridge the gap between flow problem in the laboratory and at the field. Modeling flow at the field scale with Darcian fluxes developed at the laboratory scales is challenged with preferential flows attributed to the cracking behavior of soils...

Effects of soil moisture on the diurnal pattern of pesticide emission: Numerical simulation and sensitivity analysis

USDA-ARS?s Scientific Manuscript database

Accurate prediction of pesticide volatilization is important for the protection of human and environmental health. Due to the complexity of the volatilization process, sophisticated predictive models are needed, especially for dry soil conditions. A mathematical model was developed to allow simulati...

Development of cropland management dataset to support U.S. SWAT assessments

USDA-ARS?s Scientific Manuscript database

The Soil and Water Assessment Tool (SWAT) is a widely used hydrologic/water quality simulation model in the U.S. Process-based models like SWAT require a great deal of data to accurately represent the natural world, including topography, landuse, soils, weather, and management. With the exception ...

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.

Modeling daily soil salinity dynamics in response to agricultural and environmental changes in coastal Bangladesh

NASA Astrophysics Data System (ADS)

Payo, Andrés.; Lázár, Attila N.; Clarke, Derek; Nicholls, Robert J.; Bricheno, Lucy; Mashfiqus, Salehin; Haque, Anisul

2017-05-01

Understanding the dynamics of salt movement in the soil is a prerequisite for devising appropriate management strategies for land productivity of coastal regions, especially low-lying delta regions, which support many millions of farmers around the world. At present, there are no numerical models able to resolve soil salinity at regional scale and at daily time steps. In this research, we develop a novel holistic approach to simulate soil salinization comprising an emulator-based soil salt and water balance calculated at daily time steps. The method is demonstrated for the agriculture areas of coastal Bangladesh (˜20,000 km2). This shows that we can reproduce the dynamics of soil salinity under multiple land uses, including rice crops, combined shrimp and rice farming, as well as non-rice crops. The model also reproduced well the observed spatial soil salinity for the year 2009. Using this approach, we have projected the soil salinity for three different climate ensembles, including relative sea-level rise for the year 2050. Projected soil salinity changes are significantly smaller than other reported projections. The results suggest that inter-season weather variability is a key driver of salinization of agriculture soils at coastal Bangladesh.

Study of the effect of wind speed on evaporation from soil through integrated modeling of the atmospheric boundary layer and shallow subsurface.

PubMed

Davarzani, Hossein; Smits, Kathleen; Tolene, Ryan M; Illangasekare, Tissa

2014-01-01

In an effort to develop methods based on integrating the subsurface to the atmospheric boundary layer to estimate evaporation, we developed a model based on the coupling of Navier-Stokes free flow and Darcy flow in porous medium. The model was tested using experimental data to study the effect of wind speed on evaporation. The model consists of the coupled equations of mass conservation for two-phase flow in porous medium with single-phase flow in the free-flow domain under nonisothermal, nonequilibrium phase change conditions. In this model, the evaporation rate and soil surface temperature and relative humidity at the interface come directly from the integrated model output. To experimentally validate numerical results, we developed a unique test system consisting of a wind tunnel interfaced with a soil tank instrumented with a network of sensors to measure soil-water variables. Results demonstrated that, by using this coupling approach, it is possible to predict the different stages of the drying process with good accuracy. Increasing the wind speed increases the first stage evaporation rate and decreases the transition time between two evaporative stages (soil water flow to vapor diffusion controlled) at low velocity values; then, at high wind speeds the evaporation rate becomes less dependent on the wind speed. On the contrary, the impact of wind speed on second stage evaporation (diffusion-dominant stage) is not significant. We found that the thermal and solute dispersion in free-flow systems has a significant influence on drying processes from porous media and should be taken into account.

Study of the effect of wind speed on evaporation from soil through integrated modeling of the atmospheric boundary layer and shallow subsurface

PubMed Central

Davarzani, Hossein; Smits, Kathleen; Tolene, Ryan M; Illangasekare, Tissa

2014-01-01

In an effort to develop methods based on integrating the subsurface to the atmospheric boundary layer to estimate evaporation, we developed a model based on the coupling of Navier-Stokes free flow and Darcy flow in porous medium. The model was tested using experimental data to study the effect of wind speed on evaporation. The model consists of the coupled equations of mass conservation for two-phase flow in porous medium with single-phase flow in the free-flow domain under nonisothermal, nonequilibrium phase change conditions. In this model, the evaporation rate and soil surface temperature and relative humidity at the interface come directly from the integrated model output. To experimentally validate numerical results, we developed a unique test system consisting of a wind tunnel interfaced with a soil tank instrumented with a network of sensors to measure soil-water variables. Results demonstrated that, by using this coupling approach, it is possible to predict the different stages of the drying process with good accuracy. Increasing the wind speed increases the first stage evaporation rate and decreases the transition time between two evaporative stages (soil water flow to vapor diffusion controlled) at low velocity values; then, at high wind speeds the evaporation rate becomes less dependent on the wind speed. On the contrary, the impact of wind speed on second stage evaporation (diffusion-dominant stage) is not significant. We found that the thermal and solute dispersion in free-flow systems has a significant influence on drying processes from porous media and should be taken into account. PMID:25309005

A versatile system for biological and soil chemical tests on a planetary landing craft. II - Hardware development

NASA Technical Reports Server (NTRS)

Martin, J. P.; Kok, B.; Radmer, R.

1976-01-01

A system has been under development which is designed to seek remotely for clues to life in planetary soil samples. The basic approach is a set of experiments, all having a common sensor, a gas analysis mass spectrometer which monitors gas composition in the head spaces above sealed, temperature controlled soil samples. Versatility is obtained with up to three preloaded, sealed fluid injector capsules for each of eleven soil test cells. Tests results with an engineering model has demonstrated performance capability of subsystem components such as soil distribution, gas sampling valves, injector mechanisms, temperature control, and test cell seal.

A global predictive model of carbon in mangrove soils

NASA Astrophysics Data System (ADS)

Jardine, Sunny L.; Siikamäki, Juha V.

2014-10-01

Mangroves are among the most threatened and rapidly vanishing natural environments worldwide. They provide a wide range of ecosystem services and have recently become known for their exceptional capacity to store carbon. Research shows that mangrove conservation may be a low-cost means of reducing CO2 emissions. Accordingly, there is growing interest in developing market mechanisms to credit mangrove conservation projects for associated CO2 emissions reductions. These efforts depend on robust and readily applicable, but currently unavailable, localized estimates of soil carbon. Here, we use over 900 soil carbon measurements, collected in 28 countries by 61 independent studies, to develop a global predictive model for mangrove soil carbon. Using climatological and locational data as predictors, we explore several predictive modeling alternatives, including machine-learning methods. With our predictive model, we construct a global dataset of estimated soil carbon concentrations and stocks on a high-resolution grid (5 arc min). We estimate that the global mangrove soil carbon stock is 5.00 ± 0.94 Pg C (assuming a 1 meter soil depth) and find this stock is highly variable over space. The amount of carbon per hectare in the world’s most carbon-rich mangroves (approximately 703 ± 38 Mg C ha-1) is roughly a 2.6 ± 0.14 times the amount of carbon per hectare in the world’s most carbon-poor mangroves (approximately 272 ± 49 Mg C ha-1). Considerable within country variation in mangrove soil carbon also exists. In Indonesia, the country with the largest mangrove soil carbon stock, we estimate that the most carbon-rich mangroves contain 1.5 ± 0.12 times as much carbon per hectare as the most carbon-poor mangroves. Our results can aid in evaluating benefits from mangrove conservation and designing mangrove conservation policy. Additionally, the results can be used to project changes in mangrove soil carbon stocks based on changing climatological predictors, e.g. to assess the impacts of climate change on mangrove soil carbon stocks.

Estimating Sources and Sinks of Methane from Soils in the Contiguous United States (CONUS)

NASA Astrophysics Data System (ADS)

Shu, S.; Jain, A. K.; Kheshgi, H. S.

2017-12-01

The global methane (CH4) budget estimated based on state-of-the-art models remains highly uncertain. Sources and sinks of CH4 from soils, including wetlands, are the most important source of uncertainty. Soils are estimated to account for about 45% of global CH4 emissions. At the same time oxidation of CH4 by soils is a significant sink, representing about 10% of the total sink. However, most regional and global scale modeling studies of soil CH4 fluxes have ignored the sink through soil oxidation and the source of CH4 emissions from the wet soils with shallow water tables. In this study, we link a bottom-up soil gas diffusion and CH4 biogeochemistry model to a land surface model, ISAM, to calculate the sources, emissions from both wetlands and non-wetlands, and sinks, soil oxidation, of CH4 from soils for the CONUS over the period 1900-2100. The newly developed soil CH4 model framework consists of a gas diffusion module with the vertically resolved soil hydrology (depth up to 3.5 m soil) and soil organic carbon (SOC) and CH4 biogeochemistry module. SOC profile is estimated by modeling vertical soil mixing and thus can represent the deep SOC content and estimate CH4 production from the deep non-wetland soil. For the diffusion calculations, we separately consider both the dissolved and gaseous O2 and CH4 at each soil layer. For CH4 biogeochemistry, we parameterize the production, soil oxidation, ebullition and aerenchyma transportation of CH4 for both seasonal/permanent wetland and wet soil. The SWAMP inundated fraction dataset with 8-day temporal resolution is incorporated to prescribe the extent of permanent and seasonal wetland extent for the recent decade. The model is first evaluated using a compilation of published CH4 site measurement data for CONUS. We then perform two different model experiments: 1) forced by the CRUNCEP climate data from 1900 to 2010 to estimate the contemporary CH4 emission and 2) forced by a climate projection of IPCC's highest representative concentration pathway (RCP8.5) from 2011 to 2100. Our study shows that soil oxidation has an important role attenuating the estimated natural CH4 source. We also find a wetter and warmer climate affects the dry soil CH4 sink and wet soil CH4 emissions and increases the estimated CH4 source over the CONUS.

Characterizing soil moisture and snow cover effects on boreal-arctic soil freeze/thaw dynamics and cold-season carbon emissions

NASA Astrophysics Data System (ADS)

Yi, Y.; Kimball, J. S.; Moghaddam, M.; Chen, R. H.; Reichle, R. H.; Oechel, W. C.; Zona, D.

2017-12-01

The contribution of cold season respiration to boreal-arctic carbon cycle and its potential feedbacks to climate change remain poorly quantified. Here, we developed an integrated modeling framework combining airborne low frequency (L+P-band) airborne radar retrievals and landscape level (≥1km) environmental observations from satellite optical and microwave sensors with a detailed permafrost carbon model to investigate underlying processes controlling soil freeze/thaw (FT) dynamics and cold season carbon emissions. The permafrost carbon model simulates the snow and soil thermal dynamics with soil water phase change included and accounts for soil carbon decomposition up to 3m below surface. Local-scale ( 50m) radar retrievals of active layer thickness (ALT), soil moisture and freeze/thaw (FT) status from NASA airborne UAVSAR and AirMOSS sensors are used to inform the model parameterizations of soil moisture effects on soil FT dynamics, and scaling properties of active layer processes. Both tower observed land-atmosphere fluxes and atmospheric CO2 measurements are used to evaluate the model processes controlling cold season carbon respiration, particularly the effects of snow cover and soil moisture on deep soil carbon emissions during the early cold season. Initial comparisons showed that the model can well capture the seasonality of cold season respiration in both tundra and boreal forest areas, with large emissions in late fall and early winter and gradually diminishing throughout the winter. Model sensitivity analyses are used to clarify how changes in soil thermodynamics at depth control the magnitude and seasonality of cold season respiration, and how a deeper unfrozen active layer with warming may contribute to changes in cold season respiration. Model outputs include ALT and regional carbon fluxes at 1-km resolution spanning recent satellite era (2001-present) across Alaska. These results will be used to quantify cold season respiration contributions to the annual carbon cycle and help close the boreal-arctic annual carbon budget.

Framing a future for soil science education.

NASA Astrophysics Data System (ADS)

Field, Damien

2017-04-01

The emerging concept of Global Soil Security highlights the need to have a renewed education framework that addresses the needs of those who want to; 1) know soil, 2) know of soil, and/or 3) be aware of soil. Those who know soil are soil science discipline experts and are concerned with soil as an object of study. With their discipline expertise focusing on what soil's are capable of they would be brokers of soil knowledge to those who know of soil. The connection with soil by the those in the second group focuses on the soil's utility and are responsible for managing the functionality and condition of the soil, the obvious example are farmers and agronomists. Reconnecting society with soil illustrates those who are members of the third group, i.e. those who are aware of soil. This is predicated on concepts of 'care' and is founded in the notion of beauty and utility. The utility is concerned with soil providing good Quality, clean food, or a source of pharmaceuticals. Soil also provides a place for recreation and those aware of soil know who this contributes to human health. The teaching-research-industry-learning (TRIL) nexus has been used to develop a framework for the learning and teaching of soil science applicable to a range of recipients, particularly campus-based students and practicing farm advisors. Consultation with academics, industry and professionals, by means of online (Delphi Study) and face-to-face forums, developed a heavily content-rich core body of knowledge (CBoK) relevant to industry, satisfying those who; know, and know of soil. Integrating the multidisciplinary approach in soil science teaching is a future aspiration, and will enable the development of curriculum that incorporates those who 'care' for soil. In the interim the application of the TRIL model allows the development of a learning framework more suited to real word needs. The development of a learning framework able to meet industry needs includes authentic complex scenarios that will also benefit student learning.

Soil moisture at local scale: Measurements and simulations

NASA Astrophysics Data System (ADS)

Romano, Nunzio

2014-08-01

Soil moisture refers to the water present in the uppermost part of a field soil and is a state variable controlling a wide array of ecological, hydrological, geotechnical, and meteorological processes. The literature on soil moisture is very extensive and is developing so rapidly that it might be considered ambitious to seek to present the state of the art concerning research into this key variable. Even when covering investigations about only one aspect of the problem, there is a risk of some inevitable omission. A specific feature of the present essay, which may make this overview if not comprehensive at least of particular interest, is that the reader is guided through the various traditional and more up-to-date methods by the central thread of techniques developed to measure soil moisture interwoven with applications of modeling tools that exploit the observed datasets. This paper restricts its analysis to the evolution of soil moisture at the local (spatial) scale. Though a somewhat loosely defined term, it is linked here to a characteristic length of the soil volume investigated by the soil moisture sensing probe. After presenting the most common concepts and definitions about the amount of water stored in a certain volume of soil close to the land surface, this paper proceeds to review ground-based methods for monitoring soil moisture and evaluates modeling tools for the analysis of the gathered information in various applications. Concluding remarks address questions of monitoring and modeling of soil moisture at scales larger than the local scale with the related issue of data aggregation. An extensive, but not exhaustive, list of references is provided, enabling the reader to gain further insights into this subject.

Organic Carbon Sorption and Decomposition in Selected Global Soils

DOE Data Explorer

Jagadamma, S.; Mayes, M. A.; Steinweg, J. M.; Wang, G.; Post, W. M.

2014-01-01

This data set reports the results of lab-scale experiments conducted to investigate the dynamics of organic carbon (C) decomposition from several soils from temperate, tropical, arctic, and sub-arctic environments. Results were used to test the newly developed soil microbe decomposition C model--Microbial-ENzyme-medicated Decomposition (MEND).

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...

The development of U.S. soil erosion prediction and modeling

USDA-ARS?s Scientific Manuscript database

Soil erosion prediction technology began over 70 years ago when Austin Zingg published a relationship between soil erosion (by water) and land slope and length, followed shortly by a relationship that expanded this equation to include conservation practices. But, it was nearly 20 years before this w...

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

Calibration of soil moisture flow simulation models aided by the active heated fiber optic distributed temperature sensing AHFO

NASA Astrophysics Data System (ADS)

Rodriguez-Sinobas, Leonor; Zubelzu, Sergio; Sobrino, Fernando Fernando; Sánchez, Raúl

2017-04-01

Most of the studies dealing with the development of water flow simulation models in soils, are calibrated using experimental data measured by soil probe sensors or tensiometers which locate at specific points in the study area. However since the beginning of the XXI century, the use of Distributed Fiber Optic Temperature Measurement for estimating temperature variation along a cable of fiber optic has been assessed in multiple environmental applications. Recently, its application combined with an active heating pulses technique (AHFO) has been reported as a sensor to estimate soil moisture. This method applies a known amount of heat to the soil and monitors the temperature evolution, which mainly depends on the soil moisture content. Thus, it allows estimations of soil water content every 12.5 cm along the fiber optic cable, as long as 1500 m , with 2 % accuracy , every second. This study presents the calibration of a soil water flow model (developed in Hydrus 2D) with the AHFO technique. The model predicts the distribution of soil water content of a green area irrigated by sprinkler irrigation. Several irrigation events have been evaluated in a green area located at the ETSI Agronómica, Agroalimentaria y Biosistemas in Madrid where an installation of 147 m of fiber optic cable at 15 cm depth is deployed. The Distribute Temperature Sensing unit was a SILIXA ULTIMA SR (Silixa Ltd, UK) and has spatial and temporal resolution of 0.29 m. Data logged in the DTS unit before, during and after the irrigation event were used to calibrate the estimations in the Hydrus 2D model during the infiltration and redistribution of soil water content within the irrigation interval. References: Karandish, F., & Šimůnek, J. (2016). A field-modeling study for assessing temporal variations of soil-water-crop interactions under water-saving irrigation strategies. Agricultural Water Management, 178, 291-303. Li, Y., Šimůnek, J., Jing, L., Zhang, Z., & Ni, L. (2014). Evaluation of water movement and water losses in a direct-seeded-rice field experiment using Hydrus-1D. Agricultural Water Management, 142, 38-46. Tan, X., Shao, D., & Liu, H. (2014). Simulating soil water regime in lowland paddy fields under different water managements using HYDRUS-1D. Agricultural Water Management, 132, 69-78.

Feasibility of phytoextraction to remediate cadmium and zinc contaminated soils.

PubMed

Koopmans, G F; Römkens, P F A M; Fokkema, M J; Song, J; Luo, Y M; Japenga, J; Zhao, F J

2008-12-01

A Cd and Zn contaminated soil was mixed and equilibrated with an uncontaminated, but otherwise similar soil to establish a gradient in soil contamination levels. Growth of Thlaspi caerulescens (Ganges ecotype) significantly decreased the metal concentrations in soil solution. Plant uptake of Cd and Zn exceeded the decrease of the soluble metal concentrations by several orders of magnitude. Hence, desorption of metals must have occurred to maintain the soil solution concentrations. A coupled regression model was developed to describe the transfer of metals from soil to solution and plant shoots. This model was applied to estimate the phytoextraction duration required to decrease the soil Cd concentration from 10 to 0.5 mg kg(-1). A biomass production of 1 and 5 t dm ha(-1) yr(-1) yields a duration of 42 and 11 yr, respectively. Successful phytoextraction operations based on T. caerulescens require an increased biomass production.

The Value of SMAP Soil Moisture Observations For Agricultural Applications

NASA Astrophysics Data System (ADS)

Mladenova, I. E.; Bolten, J. D.; Crow, W.; Reynolds, C. A.

2017-12-01

Knowledge of the amount of soil moisture (SM) in the root zone (RZ) is critical source of information for crop analysts and agricultural agencies as it controls crop development and crop condition changes and can largely impact end-of-season yield. Foreign Agricultural Services (FAS), a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected global crop supply and demand estimates, has been relying on RZSM estimates generated by the modified two-layer Palmer model, which has been enhanced to allow the assimilation of satellite-based soil moisture data. Generally the accuracy of model-based soil moisture estimates is dependent on the precision of the forcing data that drives the model and more specifically, the accuracy of the precipitation data. Data assimilation gives the opportunity to correct for such precipitation-related inaccuracies and enhance the quality of the model estimates. Here we demonstrate the value of ingesting passive-based soil moisture observations derived from the Soil Moisture Active Passive (SMAP) mission. In terms of agriculture, general understanding is that the change in soil moisture conditions precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop conditions. Therefore, we assess the accuracy of the SMAP enhanced Palmer model by examining the lag rank cross-correlation coefficient between the model generated soil moisture observations and the Normalized Difference Vegetation Index (NDVI).

Distribution of phenanthrene between soil and an aqueous phase in the presence of anionic micelle-like amphiphilic polyurethane particles.

PubMed

Lee, Kangtaek; Choi, Heon-Sik; Kim, Ju-Young; Ahn, Ik-Sung

2003-12-12

Sorption of micelle-like amphiphilic polyurethane (APU) particles to soil was studied and compared to that of a model anionic surfactant, sodium dodecyl sulfate (SDS). Three types of APU particles with different hydrophobicity were synthesized from urethane acrylate anionomers (UAA) and used in this study. Due to the chemically cross-linked structure, APU exhibited less sorption to the soil than SDS and a greater reduction in the sorption of phenanthrene, a model soil contaminant, to the soil was observed in the presence of APU than SDS even though the solubility of phenanthrene was higher in the presence of SDS than APU. A mathematical model was developed to describe the phenanthrene distribution between soil and an aqueous phase containing APU particles. The sorption of phenanthrene to the test soil could be well described by Linear isotherm. APU sorption to the soil was successfully described by Langmuir and Freundlich isotherms. The partition of phenanthrene between water and APU were successfully explained with a single partition coefficient. The model, which accounts for the limited solubilization of phenanthrene in sorbed APU particles, successfully described the experimental data for the distribution of phenanthrene between the soil and the aqueous phase in the presence of APU.

An Experimental and Modeling Study of Evaporation from Bare Soils Subjected to Natural Boundary Conditions at the Land-Atmospheric Interface

NASA Astrophysics Data System (ADS)

Smits, K. M.; Ngo, V. V.; Cihan, A.; Sakaki, T.; Illangasekare, T. H.; kathleen m smits

2011-12-01

Bare soil evaporation is a key process for water exchange between the land and the atmosphere and an important component of the water balance in semiarid and arid regions. However, there is no agreement on the best methodology to determine evaporation under different boundary conditions. Because it is difficult to measure evaporation from soil,with the exception of using lysimeters, numerous formulations have been proposed to establish a relationship between the rate of evaporation and soil moisture and/or soil temperature and thermal properties. Different formulations vary in how they partition available energy and include, among others, a classical bulk aerodynamic formulation which requires knowledge of the relative humidity at the soil surface and a more non-traditional heat balance method which requires knowledge of soil temperature and soil thermal properties. A need exists to systematically compare existing methods to experimental data under highly controlled conditions not achievable in the field. The goal of this work is to perform controlled experiments under transient conditions of soil moisture, temperature and wind at the land/atmospheric interface to test different conceptual and mathematical formulations for evaporation rate estimates and to develop appropriate numerical models to be used in simulations. In this study, to better understand the coupled water-vapor-heat flow processes in the shallow subsurface near the land surface, we modified a previously developed theory that allows non-equilibrium liquid/gas phase change with gas phase vapor diffusion to better account for evaporation under dry soil conditions. This theory was used to compare estimates of evaporation based on different formulations of the bulk aerodynamic and heat balance methods. In order to experimentally validate the numerical formulations/code, we performed a series of two-dimensional physical model experiments under varying boundary conditions using test sand for which the hydraulic and thermal properties were well characterized. We developed a unique two dimensional cell apparatus equipped with a network of sensors for automated and continuous monitoring of soil moisture, soil and air temperature and relative humidity, and wind velocity. Precision data under well-controlled transient heat and wind boundary conditions was generated. Results from numerical simulations were compared with experimental data. Results demonstrate the importance of properly characterizing soil thermal properties and accounting for dry soil conditions to properly estimate evaporation. Initial comparisons of various formulations of evaporation demonstrate the need for joint evaluation of heat and mass transfer for better modeling accuracy. Detailed comparisons are still underway. This knowledge is applicable to many current hydrologic and environmental problems to include climate modeling and the simulation of contaminant transport and volatilization in the shallow subsurface.

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

2016-12-01

Forest carbon processes are affected by, among other factors, soil moisture, soil temperature, soil nutrients and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve the topographically driven hill-slope land surface heterogeneity or the spatial pattern of nutrient availability. A spatially distributed forest ecosystem model, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while soil nitrogen is transported among model grids via subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation information, while BBGC provides Flux-PIHM with leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). Model results suggest that the vegetation and soil carbon distribution is primarily constrained by nitorgen availability (affected by nitorgen transport via topographically driven subsurface flow), and also constrained by solar radiation and root zone soil moisture. The predicted vegetation and soil carbon distribution generally agrees with the macro pattern observed within the watershed. The coupled ecosystem-hydrologic model provides an important tool to study the impact of topography on watershed carbon processes, as well as the impact of climate change on water resources.

A Simplified Land Model (SLM) for use in cloud-resolving models: Formulation and evaluation

NASA Astrophysics Data System (ADS)

Lee, Jungmin M.; Khairoutdinov, Marat

2015-09-01

A Simplified Land Model (SLM) that uses a minimalist set of parameters with a single-layer vegetation and multilevel soil structure has been developed distinguishing canopy and undercanopy energy budgets. The primary motivation has been to design a land model for use in the System for Atmospheric Modeling (SAM) cloud-resolving model to study land-atmosphere interactions with a sufficient level of realism. SLM uses simplified expressions for the transport of heat, moisture, momentum, and radiation in soil-vegetation system. The SLM performance has been evaluated over several land surface types using summertime tower observations of micrometeorological and biophysical data from three AmeriFlux sites, which include grassland, cropland, and deciduous-broadleaf forest. In general, the SLM captures the observed diurnal cycle of surface energy budget and soil temperature reasonably well, although reproducing the evolution of soil moisture, especially after rain events, has been challenging. The SLM coupled to SAM has been applied to the case of summertime shallow cumulus convection over land based on the Atmospheric Radiation Measurements (ARM) Southern Great Plain (SGP) observations. The simulated surface latent and sensible heat fluxes as well as the evolution of thermodynamic profiles in convective boundary layer agree well with the estimates based on the observations. Sensitivity of atmospheric boundary layer development to the soil moisture and different land cover types has been also examined.

Large scale prediction of soil properties in the West African yam belt based on mid-infrared soil spectroscopy

NASA Astrophysics Data System (ADS)

Baumann, Philipp; Lee, Juhwan; Paule Schönholzer, Laurie; Six, Johan; Frossard, Emmanuel

2016-04-01

Yam (Dioscorea sp.) is an important staple food in West Africa. Fertilizer applications have variable effects on yam tuber yields, and a management option solely based on application of mineral NPK fertilizers may bear the risk of increased organic matter mineralization. Therefore, innovative and sustainable nutrient management strategies need to be developed and evaluated for yam cultivation. The goal of this study was to establish a mid-infrared soil spectroscopic library and models to predict soil properties relevant to yam growth. Soils from yam fields at four different locations in Côte d'Ivoire and Burkina Faso that were representative of the West African yam belt were sampled. The project locations ranged from the humid forest zone (5.88 degrees N) to the northern Guinean savannah (11.07 degrees N). At each location, soils of 20 yam fields were sampled (0-30 cm). For the location in the humid forest zone additional 14 topsoil samples from positions that had been analyzed in the Land Degradation Surveillance Framework developed by ICRAF were included. In total, 94 soil samples were analyzed using established reference analysis protocols. Besides soils were milled and then scanned by fourier transform mid-infrared spectroscopy in the range between 400 and 4000 reciprocal cm. Using partial least squares (PLS) regression, PLS1 calibration models that included soils from the four locations were built using two thirds of the samples selected by Kennard-Stones sampling algorithm in the spectral principal component space. Models were independently validated with the remaining data set. Spectral models for total carbon, total nitrogen, total iron, total aluminum, total potassium, exchangeable calcium, and effective cation exchange capacity performed very well, which was indicated by R-squared values between 0.8 and 1.0 on both calibration and validation. For these soil properties, spectral models can be used for cost-effective, rapid, and accurate predictions. Measures of total silicium, total zinc, total copper, total manganese, pH, exchangeable magnesium, total sulfur, total phosphorus, resin membrane extractable phosphorus, DTPA iron, and DTPA copper were predicted with intermediate accuracy (R-squared of both calibration and validation between 0.5 and 0.8). For these measures, the models can be used to establish a rapid screening in order to distinguish high from low soil fertility status. Generally, soil fertility in West African soils is constrained by low organic C, for example, ranging between 0.2% to 2.5% in this study. The accurate prediction of total soil organic C is an important factor for monitoring soil fertility status. Results of this study showed that soil spectroscopy has a high potential to evaluate soil fertility in the selected locations.

Chemically Reactive Nitrogen Trace Species in the Planetary Boundary Layer

DTIC Science & Technology

1996-01-01

56 Biogenic NO Budget Used in the EPA Regional Oxidant Model ......... 58 Conclusions and...Regional Oxidant Model (ROM) ............................... 59 Table 2.4. Air and soil temperatures and average NO flux using W illiam s’ m odel...1985; Penkett, 1988). Yienger and Levy (1995) developed an empirically based model to estimate soil NOx emissions on a global scale. They have reported

Impact of fire disturbance on soil thermal and carbon dynamics in Alaskan Tundra and Boreal forest ecosystems

NASA Astrophysics Data System (ADS)

Jiang, Y.; Rastetter, E.; Shaver, G. R.; Rocha, A. V.

2012-12-01

In Alaska, fire disturbance is a major component influencing the soil water and energy balance in both tundra and boreal forest ecosystems. Fire-caused changes in soil environment further affect both above- and below-ground carbon cycles depending on different fire severities. Understanding the effects of fire disturbance on soil thermal change requires implicit modeling work on the post-fire soil thawing and freezing processes. In this study, we model the soil temperature profiles in multiple burned and non-burned sites using a well-developed soil thermal model which fully couples soil water and heat transport. The subsequent change in carbon dynamics is analyzed based on site level observations and simulations from the Multiple Element Limitation (MEL) model. With comparison between burned and non-burned sites, we compare and contrast fire effects on soil thermal and carbon dynamics in continuous permafrost (Anaktuvik fire in north slope), discontinuous permafrost (Erickson Creek fire at Hess Creek) and non-permafrost zone (Delta Junction fire in interior Alaska). Then we check the post-fire recovery of soil temperature profiles at sites with different fire severities in both tundra and boreal forest fire areas. We further project the future changes in soil thermal and carbon dynamics using projected climate data from Scenarios Network for Alaska & Arctic Planning (SNAP). This study provides information to improve the understanding of fire disturbance on soil thermal and carbon dynamics and the consequent response under a warming climate.

Vertical characterization of soil contamination using multi-way modeling--a case study.

PubMed

Singh, Kunwar P; Malik, Amrita; Basant, Ankita; Ojha, Priyanka

2008-11-01

This study describes application of chemometric multi-way modeling approach to analyze the dataset pertaining to soils of industrial area with a view to assess the soil/sub-soil contamination, accumulation pathways and mobility of contaminants in the soil profiles. The three-way (sampling depths, chemical variables, sampling sites) dataset on heavy metals in soil samples collected from three different sites in an industrial area, up to a depth of 60 m each was analyzed using three-way Tucker3 model validated for stability and goodness of fit. A two component Tucker3 model, explaining 66.6% of data variance, allowed interpretation of the data information in all the three modes. The interpretation of core elements revealing interactions among the components of different modes (depth, variables, sites) allowed inferring more realistic information about the contamination pattern of soils both along the horizontal and vertical coordinates, contamination pathways, and mobility of contaminants through soil profiles, as compared to the traditional data analysis techniques. It concluded that soils at site-1 and site-2 are relatively more contaminated with heavy metals of both the natural as well as anthropogenic origins, as compared to the soil of site-3. Moreover, the accumulation pathways of metals for upper shallow layers and deeper layers of soils in the area were differentiated. The information generated would be helpful in developing strategies for remediation of the contaminated soils for reducing the subsequent risk of ground-water contamination in the study region.

Heavy metals in urban soils of East St. Louis, IL. Part II: Leaching characteristics and modeling.

PubMed

Kaminski, M D; Landsberger, S

2000-09-01

The city of East St. Louis, IL, has a history of abundant industrial activities including smelters of ferrous and non-ferrous metals, a coal-fired power plant, companies that produced organic and inorganic chemicals, and petroleum refineries. Following a gross assessment of heavy metals in the community soils (see Part I of this two-part series), leaching tests were performed on specific soils to elucidate heavy metal-associated mineral fractions and general leachability. Leaching experiments, including the Toxicity Characteristic Leaching Procedure (TLCP) and column tests, and sequential extractions, illustrated the low leachability of metals in East St. Louis soils. The column leachate results were modeled using a formulation developed for fly ash leaching. The importance of instantaneous dissolution was evident from the model. By incorporating desorption/adsorption terms into the source term, the model was adapted very well to the time-dependent heavy metal leachate concentrations. The results demonstrate the utility of a simple model to describe heavy metal leaching from contaminated soils.

Heavy Metals in Urban Soils of East St. Louis, IL Part II: Leaching Characteristics and Modeling.

PubMed

Kaminski, Michael D; Landsberger, Sheldon

2000-09-01

The city of East St. Louis, IL, has a history of abundant industrial activities including smelters of ferrous and non-ferrous metals, a coal-fired power plant, companies that produced organic and inorganic chemicals, and petroleum refineries. Following a gross assessment of heavy metals in the community soils (see Part I of this two-part series), leaching tests were performed on specific soils to elucidate heavy metal-associated mineral fractions and general leachability. Leaching experiments, including the Toxicity Characteristic Leaching Procedure (TLCP) and column tests, and sequential extractions, illustrated the low leachability of metals in East St. Louis soils. The column leachate results were modeled using a formulation developed for fly ash leaching. The importance of instantaneous dissolution was evident from the model. By incorporating desorption/adsorption terms into the source term, the model was adapted very well to the time-dependent heavy metal leachate concentrations. The results demonstrate the utility of a simple model to describe heavy metal leaching from contaminated soils.

The distribution of soil phosphorus for global biogeochemical modeling

DOE PAGES

Yang, Xiaojuan; Post, Wilfred M.; Thornton, Peter E.; ...

2013-04-16

We discuss that phosphorus (P) is a major element required for biological activity in terrestrial ecosystems. Although the total P content in most soils can be large, only a small fraction is available or in an organic form for biological utilization because it is bound either in incompletely weathered mineral particles, adsorbed on mineral surfaces, or, over the time of soil formation, made unavailable by secondary mineral formation (occluded). In order to adequately represent phosphorus availability in global biogeochemistry–climate models, a representation of the amount and form of P in soils globally is required. We develop an approach that buildsmore » on existing knowledge of soil P processes and databases of parent material and soil P measurements to provide spatially explicit estimates of different forms of naturally occurring soil P on the global scale. We assembled data on the various forms of phosphorus in soils globally, chronosequence information, and several global spatial databases to develop a map of total soil P and the distribution among mineral bound, labile, organic, occluded, and secondary P forms in soils globally. The amount of P, to 50cm soil depth, in soil labile, organic, occluded, and secondary pools is 3.6 ± 3, 8.6 ± 6, 12.2 ± 8, and 3.2 ± 2 Pg P (Petagrams of P, 1 Pg = 1 × 10 15g) respectively. The amount in soil mineral particles to the same depth is estimated at 13.0 ± 8 Pg P for a global soil total of 40.6 ± 18 Pg P. The large uncertainty in our estimates reflects our limited understanding of the processes controlling soil P transformations during pedogenesis and a deficiency in the number of soil P measurements. In spite of the large uncertainty, the estimated global spatial variation and distribution of different soil P forms presented in this study will be useful for global biogeochemistry models that include P as a limiting element in biological production by providing initial estimates of the available soil P for plant uptake and microbial utilization.« less

Soil carbon sequestration potential of permanent pasture and continuous cropping soils in New Zealand.

PubMed

McNally, Sam R; Beare, Mike H; Curtin, Denis; Meenken, Esther D; Kelliher, Francis M; Calvelo Pereira, Roberto; Shen, Qinhua; Baldock, Jeff

2017-11-01

Understanding soil organic carbon (SOC) sequestration is important to develop strategies to increase the SOC stock and, thereby, offset some of the increases in atmospheric carbon dioxide. Although the capacity of soils to store SOC in a stable form is commonly attributed to the fine (clay + fine silt) fraction, the properties of the fine fraction that determine the SOC stabilization capacity are poorly known. The aim of this study was to develop an improved model to estimate the SOC stabilization capacity of Allophanic (Andisols) and non-Allophanic topsoils (0-15 cm) and, as a case study, to apply the model to predict the sequestration potential of pastoral soils across New Zealand. A quantile (90th) regression model, based on the specific surface area and extractable aluminium (pyrophosphate) content of soils, provided the best prediction of the upper limit of fine fraction carbon (FFC) (i.e. the stabilization capacity), but with different coefficients for Allophanic and non-Allophanic soils. The carbon (C) saturation deficit was estimated as the difference between the stabilization capacity of individual soils and their current C concentration. For long-term pastures, the mean saturation deficit of Allophanic soils (20.3 mg C g -1 ) was greater than that of non-Allophanic soils (16.3 mg C g -1 ). The saturation deficit of cropped soils was 1.14-1.89 times that of pasture soils. The sequestration potential of pasture soils ranged from 10 t C ha -1 (Ultic soils) to 42 t C ha -1 (Melanic soils). Although meeting the estimated national soil C sequestration potential (124 Mt C) is unrealistic, improved management practices targeted to those soils with the greatest sequestration potential could contribute significantly to off-setting New Zealand's greenhouse gas emissions. As the first national-scale estimate of SOC sequestration potential that encompasses both Allophanic and non-Allophanic soils, this serves as an informative case study for the international community. © 2017 John Wiley & Sons Ltd.

Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra

PubMed Central

Peng, Yi; Xiong, Xiong; Adhikari, Kabindra; Knadel, Maria; Grunwald, Sabine; Greve, Mogens Humlekrog

2015-01-01

There is a great challenge in combining soil proximal spectra and remote sensing spectra to improve the accuracy of soil organic carbon (SOC) models. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The first objective of this study was to integrate information of SOC derived from visible near-infrared reflectance (Vis-NIR) spectra in the laboratory with remote sensing (RS) images to improve predictions of topsoil SOC in the Skjern river catchment, Denmark. The second objective was to improve SOC prediction results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l’Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain parameters and soil maps were compiled to predict topsoil SOC using Cubist regression and Bayesian kriging. The results showed that the model developed from RS data, ancillary environmental data and laboratory spectral data yielded a lower root mean square error (RMSE) (2.8%) and higher R2 (0.59) than the model developed from only RS data and ancillary environmental data (RMSE: 3.6%, R2: 0.46). Plant-available water (PAW) was the most important predictor for all the models because of its close relationship with soil organic matter content. Moreover, vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were very important predictors in SOC spatial models. Furthermore, the ‘upland model’ was able to more accurately predict SOC compared with the ‘upland & wetland model’. However, the separately calibrated ‘upland and wetland model’ did not improve the prediction accuracy for wetland sites, since it was not possible to adequately discriminate the vegetation in the RS summer images. We conclude that laboratory Vis-NIR spectroscopy adds critical information that significantly improves the prediction accuracy of SOC compared to using RS data alone. We recommend the incorporation of laboratory spectra with RS data and other environmental data to improve soil spatial modeling and digital soil mapping (DSM). PMID:26555071

An annual model of SSM/I radiobrightness for dry soil

NASA Technical Reports Server (NTRS)

Liou, Yuei-An; England, A. W.

1992-01-01

An annual model is presented of the temperature structure within a homogeneous, dry soil halfspace that is subject to both diurnal and annual insolation, radiant heating from the atmosphere, sensible heat exchange with the atmosphere, and radiant cooling. The thermal constitutive properties of the soil are assumed to be constant so that the heat flow equation can be solved analytically. For computational economy, a variable time interval Laplace transform method is developed to predict the temperature.

Variation of Desert Soil Hydraulic Properties with Pedogenic Maturity

NASA Astrophysics Data System (ADS)

Nimmo, J. R.; Perkins, K. S.; Mirus, B. B.; Schmidt, K. M.; Miller, D. M.; Stock, J. D.; Singha, K.

2006-12-01

Older alluvial desert soils exhibit greater pedogenic maturity, having more distinct desert pavements, vesicular (Av) horizons, and more pronounced stratification from processes such as illuviation and salt accumulation. These and related effects strongly influence the soil hydraulic properties. Older soils have been observed to have lower saturated hydraulic conductivity, and possibly greater capacity to retain water, but the quantitative effect of specific pedogenic features on the soil water retention or unsaturated hydraulic conductivity (K) curves is poorly known. With field infiltration/redistribution experiments on three different-aged soils developed within alluvial wash deposits in the Mojave National Preserve, we evaluated effective hydraulic properties over a scale of several m horizontally and to 1.5 m depth. We then correlated these properties with pedogenic features. The selected soils are (1) recently deposited sediments, (2) a soil of early Holocene age, and (3) a highly developed soil of late Pleistocene age. In each experiment we ponded water in a 1-m-diameter infiltration ring for 2.3 hr. For several weeks we monitored subsurface water content and matric pressure using surface electrical resistance imaging, dielectric-constant probes, heat-dissipation probes, and tensiometers. Analysis of these data using an inverse modeling technique gives the water retention and K properties needed for predictive modeling. Some properties show a consistent trend with soil age. Progressively more developed surface and near-surface features such as desert pavement and Av horizons are the likely cause of an observed consistent decline of infiltration capacity with soil age. Other properties, such as vertical flow retardation by layer contrasts, appear to have a more complicated soil-age dependence. The wash deposits display distinct depositional layering that has a retarding effect on vertical flow, an effect that may be less pronounced in the older Holocene soil, where the original depositional structure has a relatively modest influence. Anisotropy at the scale of centimeters is of major importance in the Pleistocene soil, with developed horizons that tend to hold water within about 0.5 m of the surface for a longer duration than in the two younger soils. Correlation of these and related pedogenic features with soil hydraulic properties is a first step toward the estimation of effective hydraulic properties of widely varying Mojave Desert soils, as needed for large-scale evaluation of soil moisture dynamics in relation to ecological habitat quality.

Modeling the impact of soil aggregate size on selenium immobilization

NASA Astrophysics Data System (ADS)

Kausch, M. F.; Pallud, C. E.

2013-03-01

Soil aggregates are mm- to cm-sized microporous structures separated by macropores. Whereas fast advective transport prevails in macropores, advection is inhibited by the low permeability of intra-aggregate micropores. This can lead to mass transfer limitations and the formation of aggregate scale concentration gradients affecting the distribution and transport of redox sensitive elements. Selenium (Se) mobilized through irrigation of seleniferous soils has emerged as a major aquatic contaminant. In the absence of oxygen, the bioavailable oxyanions selenate, Se(VI), and selenite, Se(IV), can be microbially reduced to solid, elemental Se, Se(0), and anoxic microzones within soil aggregates are thought to promote this process in otherwise well-aerated soils. To evaluate the impact of soil aggregate size on selenium retention, we developed a dynamic 2-D reactive transport model of selenium cycling in a single idealized aggregate surrounded by a macropore. The model was developed based on flow-through-reactor experiments involving artificial soil aggregates (diameter: 2.5 cm) made of sand and containing Enterobacter cloacae SLD1a-1 that reduces Se(VI) via Se(IV) to Se(0). Aggregates were surrounded by a constant flow providing Se(VI) and pyruvate under oxic or anoxic conditions. In the model, reactions were implemented with double-Monod rate equations coupled to the transport of pyruvate, O2, and Se species. The spatial and temporal dynamics of the model were validated with data from experiments, and predictive simulations were performed covering aggregate sizes 1-2.5 cm in diameter. Simulations predict that selenium retention scales with aggregate size. Depending on O2, Se(VI), and pyruvate concentrations, selenium retention was 4-23 times higher in 2.5 cm aggregates compared to 1 cm aggregates. Under oxic conditions, aggregate size and pyruvate concentrations were found to have a positive synergistic effect on selenium retention. Promoting soil aggregation on seleniferous agricultural soils, through organic matter amendments and conservation tillage, may thus help decrease the impacts of selenium contaminated drainage water on downstream aquatic ecosystems.

Modeling the impact of soil aggregate size on selenium immobilization

NASA Astrophysics Data System (ADS)

Kausch, M. F.; Pallud, C. E.

2012-09-01

Soil aggregates are mm- to cm-sized microporous structures separated by macropores. Whereas fast advective transport prevails in macropores, advection is inhibited by the low permeability of intra-aggregate micropores. This can lead to mass transfer limitations and the formation of aggregate-scale concentration gradients affecting the distribution and transport of redox sensitive elements. Selenium (Se) mobilized through irrigation of seleniferous soils has emerged as a major aquatic contaminant. In the absence of oxygen, the bioavailable oxyanions selenate, Se(VI), and selenite, Se(IV), can be microbially reduced to solid, elemental Se, Se(0), and anoxic microzones within soil aggregates are thought to promote this process in otherwise well aerated soils. To evaluate the impact of soil aggregate size on selenium retention, we developed a dynamic 2-D reactive transport model of selenium cycling in a single idealized aggregate surrounded by a macropore. The model was developed based on flow-through-reactor experiments involving artificial soil aggregates (diameter: 2.5 cm) made of sand and containing Enterobacter cloacae SLD1a-1 that reduces Se(VI) via Se(IV) to Se(0). Aggregates were surrounded by a constant flow providing Se(VI) and pyruvate under oxic or anoxic conditions. In the model, reactions were implemented with double-Monod rate equations coupled to the transport of pyruvate, O2, and Se-species. The spatial and temporal dynamics of the model were validated with data from experiments and predictive simulations were performed covering aggregate sizes between 1 and 2.5 cm diameter. Simulations predict that selenium retention scales with aggregate size. Depending on O2, Se(VI), and pyruvate concentrations, selenium retention was 4-23 times higher in 2.5-cm-aggregates compared to 1-cm-aggregates. Under oxic conditions, aggregate size and pyruvate-concentrations were found to have a positive synergistic effect on selenium retention. Promoting soil aggregation on seleniferous agricultural soils, through organic matter amendments and conservation tillage, may thus help decrease the impacts of selenium contaminated drainage water on downstream aquatic ecosystems.

Simplified continuous simulation model for investigating effects of controlled drainage on long-term soil moisture dynamics with a shallow groundwater table.

PubMed

Sun, Huaiwei; Tong, Juxiu; Luo, Wenbing; Wang, Xiugui; Yang, Jinzhong

2016-08-01

Accurate modeling of soil water content is required for a reasonable prediction of crop yield and of agrochemical leaching in the field. However, complex mathematical models faced the difficult-to-calibrate parameters and the distinct knowledge between the developers and users. In this study, a deterministic model is presented and is used to investigate the effects of controlled drainage on soil moisture dynamics in a shallow groundwater area. This simplified one-dimensional model is formulated to simulate soil moisture in the field on a daily basis and takes into account only the vertical hydrological processes. A linear assumption is proposed and is used to calculate the capillary rise from the groundwater. The pipe drainage volume is calculated by using a steady-state approximation method and the leakage rate is calculated as a function of soil moisture. The model is successfully calibrated by using field experiment data from four different pipe drainage treatments with several field observations. The model was validated by comparing the simulations with observed soil water content during the experimental seasons. The comparison results demonstrated the robustness and effectiveness of the model in the prediction of average soil moisture values. The input data required to run the model are widely available and can be measured easily in the field. It is observed that controlled drainage results in lower groundwater contribution to the root zone and lower depth of percolation to the groundwater, thus helping in the maintenance of a low level of soil salinity in the root zone.

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.

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

DOE PAGES

Dong, Xiaoli; Cohen, Matthew J.; Martin, Jonathan B.; ...

2018-05-18

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study.more » Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.« less

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

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

Dong, Xiaoli; Cohen, Matthew J.; Martin, Jonathan B.

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study.more » Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.« less

On the importance of variable soil depth and process representation in the modeling of shallow landslide initiation

NASA Astrophysics Data System (ADS)

Fatichi, S.; Burlando, P.; Anagnostopoulos, G.

2014-12-01

Sub-surface hydrology has a dominant role on the initiation of rainfall-induced landslides, since changes in the soil water potential affect soil shear strength and thus apparent cohesion. Especially on steep slopes and shallow soils, loss of shear strength can lead to failure even in unsaturated conditions. A process based model, HYDROlisthisis, characterized by high resolution in space and, time is developed to investigate the interactions between surface and subsurface hydrology and shallow landslide initiation. Specifically, 3D variably saturated flow conditions, including soil hydraulic hysteresis and preferential flow, are simulated for the subsurface flow, coupled with a surface runoff routine. Evapotranspiration and specific root water uptake are taken into account for continuous simulations of soil water content during storm and inter-storm periods. The geotechnical component of the model is based on a multidimensional limit equilibrium analysis, which takes into account the basic principles of unsaturated soil mechanics. The model is applied to a small catchment in Switzerland historically prone to rainfall-triggered landslides. A series of numerical simulations were carried out with various boundary conditions (soil depths) and using hydrological and geotechnical components of different complexity. Specifically, the sensitivity to the inclusion of preferential flow and soil hydraulic hysteresis was tested together with the replacement of the infinite slope assumption with a multi-dimensional limit equilibrium analysis. The effect of the different model components on model performance was assessed using accuracy statistics and Receiver Operating Characteristic (ROC) curve. The results show that boundary conditions play a crucial role in the model performance and that the introduced hydrological (preferential flow and soil hydraulic hysteresis) and geotechnical components (multidimensional limit equilibrium analysis) considerably improve predictive capabilities in the presented case study.

Expansive Soil Crack Depth under Cumulative Damage

PubMed Central

Shi, Bei-xiao; Chen, Sheng-shui; Han, Hua-qiang; Zheng, Cheng-feng

2014-01-01

The crack developing depth is a key problem to slope stability of the expansive soil and its project governance and the crack appears under the roles of dry-wet cycle and gradually develops. It is believed from the analysis that, because of its own cohesion, the expansive soil will have a certain amount of deformation under pulling stress but without cracks. The soil body will crack only when the deformation exceeds the ultimate tensile strain that causes cracks. And it is also believed that, due to the combined effect of various environmental factors, particularly changes of the internal water content, the inherent basic physical properties of expansive soil are weakened, and irreversible cumulative damages are eventually formed, resulting in the development of expansive soil cracks in depth. Starting from the perspective of volumetric strain that is caused by water loss, considering the influences of water loss rate and dry-wet cycle on crack developing depth, the crack developing depth calculation model which considers the water loss rate and the cumulative damages is established. Both the proposal of water loss rate and the application of cumulative damage theory to the expansive soil crack development problems try to avoid difficulties in matrix suction measurement, which will surely play a good role in promoting and improving the research of unsaturated expansive soil. PMID:24737974

An evaluation of models of bare soil evaporation formulated with different land surface boundary conditions and assumptions

NASA Astrophysics Data System (ADS)

Smits, Kathleen M.; Ngo, Viet V.; Cihan, Abdullah; Sakaki, Toshihiro; Illangasekare, Tissa H.

2012-12-01

Bare soil evaporation is a key process for water exchange between the land and the atmosphere and an important component of the water balance. However, there is no agreement on the best modeling methodology to determine evaporation under different atmospheric boundary conditions. Also, there is a lack of directly measured soil evaporation data for model validation to compare these methods to establish the validity of their mathematical formulations. Thus, a need exists to systematically compare evaporation estimates using existing methods to experimental observations. The goal of this work is to test different conceptual and mathematical formulations that are used to estimate evaporation from bare soils to critically investigate various formulations and surface boundary conditions. Such a comparison required the development of a numerical model that has the ability to incorporate these boundary conditions. For this model, we modified a previously developed theory that allows nonequilibrium liquid/gas phase change with gas phase vapor diffusion to better account for dry soil conditions. Precision data under well-controlled transient heat and wind boundary conditions were generated, and results from numerical simulations were compared with experimental data. Results demonstrate that the approaches based on different boundary conditions varied in their ability to capture different stages of evaporation. All approaches have benefits and limitations, and no one approach can be deemed most appropriate for every scenario. Comparisons of different formulations of the surface boundary condition validate the need for further research on heat and vapor transport processes in soil for better modeling accuracy.

SMERGE: A multi-decadal root-zone soil moisture product for CONUS

NASA Astrophysics Data System (ADS)

Crow, W. T.; Dong, J.; Tobin, K. J.; Torres, R.

2017-12-01

Multi-decadal root-zone soil moisture products are of value for a range of water resource and climate applications. The NASA-funded root-zone soil moisture merging project (SMERGE) seeks to develop such products through the optimal merging of land surface model predictions with surface soil moisture retrievals acquired from multi-sensor remote sensing products. This presentation will describe the creation and validation of a daily, multi-decadal (1979-2015), vertically-integrated (both surface to 40 cm and surface to 100 cm), 0.125-degree root-zone product over the contiguous United States (CONUS). The modeling backbone of the system is based on hourly root-zone soil moisture simulations generated by the Noah model (v3.2) operating within the North American Land Data Assimilation System (NLDAS-2). Remotely-sensed surface soil moisture retrievals are taken from the multi-sensor European Space Agency Climate Change Initiative soil moisture data set (ESA CCI SM). In particular, the talk will detail: 1) the exponential smoothing approach used to convert surface ESA CCI SM retrievals into root-zone soil moisture estimates, 2) the averaging technique applied to merge (temporally-sporadic) remotely-sensed with (continuous) NLDAS-2 land surface model estimates of root-zone soil moisture into the unified SMERGE product, and 3) the validation of the SMERGE product using long-term, ground-based soil moisture datasets available within CONUS.

Phytoavailability of Cadmium (Cd) to Pak Choi (Brassica chinensis L.) Grown in Chinese Soils: A Model to Evaluate the Impact of Soil Cd Pollution on Potential Dietary Toxicity

PubMed Central

Yang, Xiaoe; Xiao, Wendan; Stoffella, Peter J.; Saghir, Aamir; Azam, Muhammad; Li, Tingqiang

2014-01-01

Food chain contamination by soil cadmium (Cd) through vegetable consumption poses a threat to human health. Therefore, an understanding is needed on the relationship between the phytoavailability of Cd in soils and its uptake in edible tissues of vegetables. The purpose of this study was to establish soil Cd thresholds of representative Chinese soils based on dietary toxicity to humans and develop a model to evaluate the phytoavailability of Cd to Pak choi (Brassica chinensis L.) based on soil properties. Mehlich-3 extractable Cd thresholds were more suitable for Stagnic Anthrosols, Calcareous, Ustic Cambosols, Typic Haplustalfs, Udic Ferrisols and Periudic Argosols with values of 0.30, 0.25, 0.18, 0.16, 0.15 and 0.03 mg kg−1, respectively, while total Cd is adequate threshold for Mollisols with a value of 0.86 mg kg−1. A stepwise regression model indicated that Cd phytoavailability to Pak choi was significantly influenced by soil pH, organic matter, total Zinc and Cd concentrations in soil. Therefore, since Cd accumulation in Pak choi varied with soil characteristics, they should be considered while assessing the environmental quality of soils to ensure the hygienically safe food production. PMID:25386790

Phytoavailability of cadmium (Cd) to Pak choi (Brassica chinensis L.) grown in Chinese soils: a model to evaluate the impact of soil Cd pollution on potential dietary toxicity.

PubMed

Rafiq, Muhammad Tariq; Aziz, Rukhsanda; Yang, Xiaoe; Xiao, Wendan; Stoffella, Peter J; Saghir, Aamir; Azam, Muhammad; Li, Tingqiang

2014-01-01

Food chain contamination by soil cadmium (Cd) through vegetable consumption poses a threat to human health. Therefore, an understanding is needed on the relationship between the phytoavailability of Cd in soils and its uptake in edible tissues of vegetables. The purpose of this study was to establish soil Cd thresholds of representative Chinese soils based on dietary toxicity to humans and develop a model to evaluate the phytoavailability of Cd to Pak choi (Brassica chinensis L.) based on soil properties. Mehlich-3 extractable Cd thresholds were more suitable for Stagnic Anthrosols, Calcareous, Ustic Cambosols, Typic Haplustalfs, Udic Ferrisols and Periudic Argosols with values of 0.30, 0.25, 0.18, 0.16, 0.15 and 0.03 mg kg-1, respectively, while total Cd is adequate threshold for Mollisols with a value of 0.86 mg kg-1. A stepwise regression model indicated that Cd phytoavailability to Pak choi was significantly influenced by soil pH, organic matter, total Zinc and Cd concentrations in soil. Therefore, since Cd accumulation in Pak choi varied with soil characteristics, they should be considered while assessing the environmental quality of soils to ensure the hygienically safe food production.

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.

Mapping soil landscape as spatial continua: The Neural Network Approach

NASA Astrophysics Data System (ADS)

Zhu, A.-Xing

2000-03-01

A neural network approach was developed to populate a soil similarity model that was designed to represent soil landscape as spatial continua for hydroecological modeling at watersheds of mesoscale size. The approach employs multilayer feed forward neural networks. The input to the network was data on a set of soil formative environmental factors; the output from the network was a set of similarity values to a set of prescribed soil classes. The network was trained using a conjugate gradient algorithm in combination with a simulated annealing technique to learn the relationships between a set of prescribed soils and their environmental factors. Once trained, the network was used to compute for every location in an area the similarity values of the soil to the set of prescribed soil classes. The similarity values were then used to produce detailed soil spatial information. The approach also included a Geographic Information System procedure for selecting representative training and testing samples and a process of determining the network internal structure. The approach was applied to soil mapping in a watershed, the Lubrecht Experimental Forest, in western Montana. The case study showed that the soil spatial information derived using the neural network approach reveals much greater spatial detail and has a higher quality than that derived from the conventional soil map. Implications of this detailed soil spatial information for hydroecological modeling at the watershed scale are also discussed.

Effect of aggregation on SOC transport: linking soil properties to sediment organic matter

NASA Astrophysics Data System (ADS)

Kuhn, Nikolaus J.

2016-04-01

Soils are an interface between the Earth's spheres and shaped by the nature of the interaction between them. The relevance of soil properties for the nature of the interaction between atmosphere, hydrosphere and biosphere is well-studied and accepted, on point- or ecotone-scale. However, this understanding of the largely vertical connections between spheres is not matched by a similar recognition of soil properties affecting processes acting largely in a lateral way across the land surface, such as erosion, transport and deposition of soil and the associated organic matter. Understanding the redistribution of eroded soil organic matter falls into several disciplines, most notably soil science, agronomy, hydrology and geomorphology, and recently into biogeochemistry. Accordingly, the way soil and sediment are described differs: in soil science, aggregation and structure are essential properties, while most process-based soil erosion models treat soil as a mixture of individual mineral grains, based on concepts derived in fluvial geomorphology or civil engineering. The actual behavior of aggregated sediment and the associated organic matter is not reflected by either approach and difficult to capture due to the dynamic nature of aggregation, especially in an environment such as running water. Still, a proxy to assess the uncertainties introduced by aggregation on the behavior of soil/sediment organic while moving in water across landscapes and into the aquatic system would represent a major step forward. To develop such a proxy, a database collating relevant soil, organic matter and sediment properties could serve as an initial step to identify which soil types and erosion scenarios are prone to generate a high uncertainty compared to the use of soil texture in erosion models. Furthermore, it could serve to develop standardized analytical procedures for appropriate description of soil and organic matter as sediment.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

A multimedia fate and chemical transport modeling system for pesticides: I. Model development and implementation

NASA Astrophysics Data System (ADS)

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

2011-07-01

We have combined the US EPA MM5/MCIP/SMOKE/CMAQ modeling system with a dynamic soil model, the pesticide emission model (PEM), to create a multimedia chemical transport model capable of describing the important physical and chemical processes involving pesticides in the soil, in the atmosphere, and on the surface of vegetation. These processes include: agricultural practices (e.g. soil tilling and pesticide application mode); advection and diffusion of pesticides, moisture, and heat in the soil; partitioning of pesticides between soil organic carbon and interstitial water and air; emissions from the soil to the atmosphere; gas-particle partitioning and transport in the atmosphere; and atmospheric chemistry and dry and wet deposition of pesticides to terrestrial and water surfaces. The modeling system was tested by simulating toxaphene in a domain that covers most of North America for the period from 1 January 2000 to 31 December 2000. The results show obvious transport of the pesticide from the heavily contaminated soils in the southern United States and Mexico to water bodies including the Atlantic Ocean, the Gulf of Mexico and the Great Lakes, leading to significant dry and wet deposition into these ecosystems. The spatial distributions of dry and wet depositions differ because of their different physical mechanisms; the former follows the distribution of air concentrations whereas the latter is more biased to the North East due to the effect of precipitation.

Process-oriented modelling to identify main drivers of erosion-induced carbon fluxes

NASA Astrophysics Data System (ADS)

Wilken, Florian; Sommer, Michael; Van Oost, Kristof; Bens, Oliver; Fiener, Peter

2017-05-01

Coupled modelling of soil erosion, carbon redistribution, and turnover has received great attention over the last decades due to large uncertainties regarding erosion-induced carbon fluxes. For a process-oriented representation of event dynamics, coupled soil-carbon erosion models have been developed. However, there are currently few models that represent tillage erosion, preferential water erosion, and transport of different carbon fractions (e.g. mineral bound carbon, carbon encapsulated by soil aggregates). We couple a process-oriented multi-class sediment transport model with a carbon turnover model (MCST-C) to identify relevant redistribution processes for carbon dynamics. The model is applied for two arable catchments (3.7 and 7.8 ha) located in the Tertiary Hills about 40 km north of Munich, Germany. Our findings indicate the following: (i) redistribution by tillage has a large effect on erosion-induced vertical carbon fluxes and has a large carbon sequestration potential; (ii) water erosion has a minor effect on vertical fluxes, but episodic soil organic carbon (SOC) delivery controls the long-term erosion-induced carbon balance; (iii) delivered sediments are highly enriched in SOC compared to the parent soil, and sediment delivery is driven by event size and catchment connectivity; and (iv) soil aggregation enhances SOC deposition due to the transformation of highly mobile carbon-rich fine primary particles into rather immobile soil aggregates.

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.

Generation and mobility of radon in soil

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

Rose, A.W.; Jester, W.A.; Ciolkosz, E.J.

This study has confirmed large seasonal and daily variations of Rn in soil gas, developed models for the effects of temperature and moisture on air-water Rn partition, inhibited Rn diffusion from wet soil into sparse large air-filled pores and effects of diffusion into bedrock, demonstrated that organic matter is a major host for 226Ra in soils and that organic-bound Ra largely determines the proportion of 222Rn emanated to pore space, shown that in contrast 220Rn is emanated mainly from 224Ra in Fe-oxides, detected significant disequilibrium between 226Ra and 238U in organic matter and in some recent glacial soils, demonstrated bymore » computer models that air convection driven by temperature differences is expected in moderately permeable soils on hillsides.« less

Generation and mobility of radon in soil. Technical report

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

Rose, A.W.; Jester, W.A.; Ciolkosz, E.J.

This study has confirmed large seasonal and daily variations of Rn in soil gas, developed models for the effects of temperature and moisture on air-water Rn partition, inhibited Rn diffusion from wet soil into sparse large air-filled pores and effects of diffusion into bedrock, demonstrated that organic matter is a major host for 226Ra in soils and that organic-bound Ra largely determines the proportion of 222Rn emanated to pore space, shown that in contrast 220Rn is emanated mainly from 224Ra in Fe-oxides, detected significant disequilibrium between 226Ra and 238U in organic matter and in some recent glacial soils, demonstrated bymore » computer models that air convection driven by temperature differences is expected in moderately permeable soils on hillsides.« less

SoilGrids250m: Global gridded soil information based on machine learning

PubMed Central

Mendes de Jesus, Jorge; Heuvelink, Gerard B. M.; Ruiperez Gonzalez, Maria; Kilibarda, Milan; Blagotić, Aleksandar; Shangguan, Wei; Wright, Marvin N.; Geng, Xiaoyuan; Bauer-Marschallinger, Bernhard; Guevara, Mario Antonio; Vargas, Rodrigo; MacMillan, Robert A.; Batjes, Niels H.; Leenaars, Johan G. B.; Ribeiro, Eloi; Wheeler, Ichsani; Mantel, Stephan; Kempen, Bas

2017-01-01

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods—random forest and gradient boosting and/or multinomial logistic regression—as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10–fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License. PMID:28207752

SoilGrids250m: Global gridded soil information based on machine learning.

PubMed

Hengl, Tomislav; Mendes de Jesus, Jorge; Heuvelink, Gerard B M; Ruiperez Gonzalez, Maria; Kilibarda, Milan; Blagotić, Aleksandar; Shangguan, Wei; Wright, Marvin N; Geng, Xiaoyuan; Bauer-Marschallinger, Bernhard; Guevara, Mario Antonio; Vargas, Rodrigo; MacMillan, Robert A; Batjes, Niels H; Leenaars, Johan G B; Ribeiro, Eloi; Wheeler, Ichsani; Mantel, Stephan; Kempen, Bas

2017-01-01

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.

The Unified North American Soil Map and Its Implication on the Soil Organic Carbon Stock in North America

NASA Astrophysics Data System (ADS)

Wei, Y.; Liu, S.; Huntzinger, D. N.; Michalak, A. M.; Post, W. M.; Cook, R. B.; Schaefer, K. M.; Thornton, M.

2014-12-01

The Unified North American Soil Map (UNASM) was developed by Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) to provide more accurate regional soil information for terrestrial biosphere modeling. The UNASM combines information from state-of-the-art US STATSGO2 and Soil Landscape of Canada (SLCs) databases. The area not covered by these datasets is filled by using the Harmonized World Soil Database version 1.21 (HWSD1.21). The UNASM contains maximum soil depth derived from the data source as well as seven soil attributes (including sand, silt, and clay content, gravel content, organic carbon content, pH, and bulk density) for the topsoil layer (0-30 cm) and the subsoil layer (30-100 cm), respectively, of the spatial resolution of 0.25 degrees in latitude and longitude. There are pronounced differences in the spatial distributions of soil properties and soil organic carbon between UNASM and HWSD, but the UNASM overall provides more detailed and higher-quality information particularly in Alaska and central Canada. To provide more accurate and up-to-date estimate of soil organic carbon stock in North America, we incorporated Northern Circumpolar Soil Carbon Database (NCSCD) into the UNASM. The estimate of total soil organic carbon mass in the upper 100 cm soil profile based on the improved UNASM is 365.96 Pg, of which 23.1% is under trees, 14.1% is in shrubland, and 4.6% is in grassland and cropland. This UNASM data has been provided as a resource for use in terrestrial ecosystem modeling of MsTMIP both for input of soil characteristics and for benchmarking model output.

Multisensor on-the-go mapping of readily dispersible clay, particle size and soil organic matter

NASA Astrophysics Data System (ADS)

Debaene, Guillaume; Niedźwiecki, Jacek; Papierowska, Ewa

2016-04-01

Particle size fractions affect strongly the physical and chemical properties of soil. Readily dispersible clay (RDC) is the part of the clay fraction in soils that is easily or potentially dispersible in water when small amounts of mechanical energy are applied to soil. The amount of RDC in the soil is of significant importance for agriculture and environment because clay dispersion is a cause of poor soil stability in water which in turn contributes to soil erodibility, mud flows, and cementation. To obtain a detailed map of soil texture, many samples are needed. Moreover, RDC determination is time consuming. The use of a mobile visible and near-infrared (VIS-NIR) platform is proposed here to map those soil properties and obtain the first detailed map of RDC at field level. Soil properties prediction was based on calibration model developed with 10 representative samples selected by a fuzzy logic algorithm. Calibration samples were analysed for soil texture (clay, silt and sand), RDC and soil organic carbon (SOC) using conventional wet chemistry analysis. Moreover, the Veris mobile sensor platform is also collecting electrical conductivity (EC) data (deep and shallow), and soil temperature. These auxiliary data were combined with VIS-NIR measurement (data fusion) to improve prediction results. EC maps were also produced to help understanding RDC data. The resulting maps were visually compared with an orthophotography of the field taken at the beginning of the plant growing season. Models were developed with partial least square regression (PLSR) and support vector machine regression (SVMR). There were no significant differences between calibration using PLSR or SVMR. Nevertheless, the best models were obtained with PLSR and standard normal variate (SNV) pretreatment and the fusion with deep EC data (e.g. for RDC and clay content: RMSECV = 0,35% and R2 = 0,71; RMSECV = 0,32% and R2 = 0,73 respectively). The best models were used to predict soil properties from the field spectra collected with the VIS-NIR platform. Maps of soil properties were generated using natural neighbour (NN) interpolation. Calibration results were satisfactory for all soil properties and allowed for the generation of detailed maps. The spatial variability of RDC was in accordance with the field orthophotography. Areas of high RDC content were corresponding to area of bad plant development. Soil texture has been correctly predicted by VIS-NIR spectroscopy (laboratory or on-the-go) before. However, readily dispersible clay (an important parameter for soil stability) has never been investigated before. This study introduces the possibility of using VIS-NIR for predicting readily dispersible clay at field level. The results obtained could be used in preventing soil erosion. Acknowledgement: This research was financed by a National Science Centre grant (NCN - Poland) with decision number UMO-2012/07/B/ST10/04387

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Phosphorus in global agricultural soils: spatially explicit modelling of soil phosphorus and crop uptake for 1900 to 2010

NASA Astrophysics Data System (ADS)

Zhang, J.; Beusen, A.; Bouwman, L.; Apeldoorn, D. V.; Yu, C.

2016-12-01

Phosphorus (P) plays a vital role in global crop production and food security. To explore the global P status of soils, in this study we developed a spatially explicit version of a two-pool dynamic soil P model at 0.5°resolution. With this model, we analyzed the historical changes of soil P inputs (including manure and inorganic P fertilizer) from 1900 to 2010, reproduced the historical crop P uptake, calculated the phosphorus use efficiency (PUE) and conducted a comprehensive inventory of soil P pools and P budgets (deficit and surplus) in global soils under croplands. Our results suggest that the spatially explicit model is capable of simulating the long-term soil P budget changes and crop uptake, with model simulations closely matching historical P uptake for cropland in all countries. The global P inputs from fertilizers and manure increased from 2 Tg P in 1900 to 23 Tg P in 2010 with great variation across different regions and countries of the world. The magnitude of crop uptake has also changed rapidly over the 20th century: according to our model, crop P uptake per hectare in Western Europe increased by more than three times while the total soil P stock per hectare increased by close to 37% due to long-term P surplus application, with a slight decrease in recent years. Croplands in China (total P per hectare slight decline during 1900-1970, +34% since 1970) and India (total P per hectare gradual increase by 14% since 1900, 6% since 1970) are currently in the phase of accumulation.The total soil P content per hectare in Sub-Saharan Africa has slightly decreased since 1900.Our model is a promising tool to analyze the changes in the soil P status and the capacity of soils to supply P to crops, including future projections of required nutrient inputs.

Assimilation of active and passive microwave observations for improved estimates of soil moisture and crop growth

USDA-ARS?s Scientific Manuscript database

An Ensemble Kalman Filter-based data assimilation framework that links a crop growth model with active and passive (AP) microwave models was developed to improve estimates of soil moisture (SM) and vegetation biomass over a growing season of soybean. Complementarities in AP observations were incorpo...

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.

Soil erodibility in Europe: a high-resolution dataset based on LUCAS.

PubMed

Panagos, Panos; Meusburger, Katrin; Ballabio, Cristiano; Borrelli, Pasqualle; Alewell, Christine

2014-05-01

The greatest obstacle to soil erosion modelling at larger spatial scales is the lack of data on soil characteristics. One key parameter for modelling soil erosion is the soil erodibility, expressed as the K-factor in the widely used soil erosion model, the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). The K-factor, which expresses the susceptibility of a soil to erode, is related to soil properties such as organic matter content, soil texture, soil structure and permeability. With the Land Use/Cover Area frame Survey (LUCAS) soil survey in 2009 a pan-European soil dataset is available for the first time, consisting of around 20,000 points across 25 Member States of the European Union. The aim of this study is the generation of a harmonised high-resolution soil erodibility map (with a grid cell size of 500 m) for the 25 EU Member States. Soil erodibility was calculated for the LUCAS survey points using the nomograph of Wischmeier and Smith (1978). A Cubist regression model was applied to correlate spatial data such as latitude, longitude, remotely sensed and terrain features in order to develop a high-resolution soil erodibility map. The mean K-factor for Europe was estimated at 0.032 thahha(-1)MJ(-1)mm(-1) with a standard deviation of 0.009 thahha(-1)MJ(-1)mm(-1). The yielded soil erodibility dataset compared well with the published local and regional soil erodibility data. However, the incorporation of the protective effect of surface stone cover, which is usually not considered for the soil erodibility calculations, resulted in an average 15% decrease of the K-factor. The exclusion of this effect in K-factor calculations is likely to result in an overestimation of soil erosion, particularly for the Mediterranean countries, where highest percentages of surface stone cover were observed. Copyright © 2014. Published by Elsevier B.V.

Life in the dark: Roots and how they regulate plant-soil interactions

NASA Astrophysics Data System (ADS)

Wu, Y.; Chou, C.; Peruzzo, L.; Riley, W. J.; Hao, Z.; Petrov, P.; Newman, G. A.; Versteeg, R.; Blancaflor, E.; Ma, X.; Dafflon, B.; Brodie, E.; Hubbard, S. S.

2017-12-01

Roots play a key role in regulating interactions between soil and plants, an important biosphere process critical for soil development and health, global food security, carbon sequestration, and the cycling of elements (water, carbon, nutrients, and environmental contaminants). However, their underground location has hindered studies of plant roots and the role they play in regulating plant-soil interactions. Technological limitations for root phenotyping and the lack of an integrated approach capable of linking root development, its environmental adaptation/modification with subsequent impact on plant health and productivity are major challenges faced by scientists as they seek to understand the plant's hidden half. To overcome these challenges, we combine novel experimental methods with numerical simulations, and conduct controlled studies to explore the dynamic growth of crop roots. We ask how roots adapt to and change the soil environment and their subsequent impacts on plant health and productivity. Specifically, our efforts are focused on (1) developing novel geophysical approaches for non-invasive plant root and rhizosphere characterization; (2) correlating root developments with key canopy traits indicative of plant health and productivity; (3) developing numerical algorithms for novel geophysical root signal processing; (4) establishing plant growth models to explore root-soil interactions and above and below ground traits co-variabilities; and (5) exploring how root development modifies rhizosphere physical, hydrological, and geochemical environments for adaptation and survival. Our preliminary results highlight the potential of using electro-geophysical methods to quantifying key rhizosphere traits, the capability of the ecosys model for mechanistic plant growth simulation and traits correlation exploration, and the combination of multi-physics and numerical approach for a systematic understanding of root growth dynamics, impacts on soil physicochemical environments, and plant health and productivity.

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.

Sensitivity analysis of a soil-vegetation-atmosphere transfer (SVAT) model parameterised for a British floodplain meadow

NASA Astrophysics Data System (ADS)

Morris, P. J.; Verhoef, A.; Van der Tol, C.; Macdonald, D.

2011-12-01

Rationale: Floodplain meadows are highly species-rich grassland ecosystems, unique in that their vegetation and soil structures have been shaped and maintained by ~1,000 yrs of traditional, low-intensity agricultural management. Widespread development on floodplains over the last two centuries has left few remaining examples of these once commonplace ecosystems and they are afforded high conservation value by British and European agencies. Increased incidences and severity of summer drought and winter flooding in Britain in recent years have placed floodplain plant communities under stress through altered soil moisture regimes. There is a clear need for improved management strategies if the last remaining British floodplain meadows are to be conserved under changing climates. Aim: As part of the Floodplain Underground Sensors Experiment (FUSE, a 3-year project funded by the Natural Environment Research Council) we aim to understand the environmental controls over soil-vegetation-atmosphere transfers (SVAT) of water, CO2 and energy at Yarnton Mead, a floodplain meadow in southern England. An existing model, SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes; van der Tol et al., 2009), uses remotely-sensed infrared radiance spectra to predict heat and water transfers between a vegetation canopy and the atmosphere. We intend to expand SCOPE by developing a more realistic, physically-based representation of water, gas and energy transfers between soil and vegetation. This improved understanding will eventually take the form of a new submodel within SCOPE, allowing more rigorous estimation of soil-canopy-atmosphere exchanges for the site using predominantly remotely-sensed data. In this context a number of existing SVAT models will be tested and compared to ensure that only reliable and robust underground model components will be coupled to SCOPE. Approach: For this study, we parameterised an existing and widely-used SVAT model (CoupModel; Jansson, 2011) for our study site and analysed the model's sensitivity to a comprehensive set of soil/plant biophysical processes and parameter values. Findings: The sensitivity analysis indicates those processes and parameters most important to soil-vegetation-atmosphere transfers at the site. We use the outcomes of the sensitivity analysis to indicate directly the desired structure of the new SCOPE submodel. In addition, existing soil-moisture, soil matric-potential and meteorological data for the site indicate that evapotranspiration is heavily water-limited during summer months, although soil moisture and soil matric-potential data alone provide very little explanation of the ratio of potential to actual evapotranspiration. A mechanistic representation of stomatal resistance and its response to short-term changes in meteorological conditions - independent of soil moisture status - will also likely improve SCOPE's predictions of heat and water transfers. Ultimately our work will contribute to improved understanding and management of floodplain meadows in Britain and elsewhere.

Critical zone evolution and the origins of organised complexity in watersheds

NASA Astrophysics Data System (ADS)

Harman, C.; Troch, P. A.; Pelletier, J.; Rasmussen, C.; Chorover, J.

2012-04-01

The capacity of the landscape to store and transmit water is the result of a historical trajectory of landscape, soil and vegetation development, much of which is driven by hydrology itself. Progress in geomorphology and pedology has produced models of surface and sub-surface evolution in soil-mantled uplands. These dissected, denuding modeled landscapes are emblematic of the kinds of dissipative self-organized flow structures whose hydrologic organization may also be understood by low-dimensional hydrologic models. They offer an exciting starting-point for examining the mapping between the long-term controls on landscape evolution and the high-frequency hydrologic dynamics. Here we build on recent theoretical developments in geomorphology and pedology to try to understand how the relative rates of erosion, sediment transport and soil development in a landscape determine catchment storage capacity and the relative dominance of runoff process, flow pathways and storage-discharge relationships. We do so by using a combination of landscape evolution models, hydrologic process models and data from a variety of sources, including the University of Arizona Critical Zone Observatory. A challenge to linking the landscape evolution and hydrologic model representations is the vast differences in the timescales implicit in the process representations. Furthermore the vast array of processes involved makes parameterization of such models an enormous challenge. The best data-constrained geomorphic transport and soil development laws only represent hydrologic processes implicitly, through the transport and weathering rate parameters. In this work we propose to avoid this problem by identifying the relationship between the landscape and soil evolution parameters and macroscopic climate and geological controls. These macroscopic controls (such as the aridity index) have two roles: 1) they express the water and energy constraints on the long-term evolution of the landscape system, and 2) they bound the range of plausible short-term hydroclimatic regimes that may drive a particular landscape's hydrologic dynamics. To ensure that the hydrologic dynamics implicit in the evolutionary parameters are compatible with the dynamics observed in the hydrologic modeling, a set of consistency checks based on flow process dominance are developed.

Soil type and texture impacts on soil organic carbon accumulation in a sub-tropical agro-ecosystem

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

Gonçalves, Daniel Ruiz Potma; Sa, Joao Carlos de Moraes; Mishra, Umakant

Soil organic carbon (C) plays a fundamental role in tropical and subtropical soil fertility, agronomic productivity, and soil health. As a tool for understand ecosystems dynamics, mathematical models such as Century have been used to assess soil's capacity to store C in different environments. However, as Century was initially developed for temperate ecosystems, several authors have hypothesized that C storage may be underestimated by Century in Oxisols. We tested the hypothesis that Century model can be parameterized for tropical soils and used to reliably estimate soil organic carbon (SOC) storage. The aim of this study was to investigate SOC storagemore » under two soil types and three textural classes and quantify the sources and magnitude of uncertainty using the Century model. The simulation for SOC storage was efficient and the mean residue was 10 Mg C ha -1 (13%) for n = 91. However, a different simulation bias was observed for soil with <600 g kg -1 of clay was 16.3 Mg C ha -1 (18%) for n = 30, and at >600 g kg -1 of clay, was 4 Mg C ha -1 (5%) for n = 50, respectively. The results suggest a non-linear effect of clay and silt contents on C storage in Oxisols. All types of soil contain nearly 70% of Fe and Al oxides in the clay fraction and a regression analysis showed an increase in model bias with increase in oxides content. Consequently, inclusion of mineralogical control of SOC stabilization by Fe and Al (hydro) oxides may improve results of Century model simulations in soils with high oxides contents« less

Vegetation management with fire modifies peatland soil thermal regime.

PubMed

Brown, Lee E; Palmer, Sheila M; Johnston, Kerrylyn; Holden, Joseph

2015-05-01

Vegetation removal with fire can alter the thermal regime of the land surface, leading to significant changes in biogeochemistry (e.g. carbon cycling) and soil hydrology. In the UK, large expanses of carbon-rich upland environments are managed to encourage increased abundance of red grouse (Lagopus lagopus scotica) by rotational burning of shrub vegetation. To date, though, there has not been any consideration of whether prescribed vegetation burning on peatlands modifies the thermal regime of the soil mass in the years after fire. In this study thermal regime was monitored across 12 burned peatland soil plots over an 18-month period, with the aim of (i) quantifying thermal dynamics between burned plots of different ages (from <2 to 15 + years post burning), and (ii) developing statistical models to determine the magnitude of thermal change caused by vegetation management. Compared to plots burned 15 + years previously, plots recently burned (<2-4 years) showed higher mean, maximum and range of soil temperatures, and lower minima. Statistical models (generalised least square regression) were developed to predict daily mean and maximum soil temperature in plots burned 15 + years prior to the study. These models were then applied to predict temperatures of plots burned 2, 4 and 7 years previously, with significant deviations from predicted temperatures illustrating the magnitude of burn management effects. Temperatures measured in soil plots burned <2 years previously showed significant statistical disturbances from model predictions, reaching +6.2 °C for daily mean temperatures and +19.6 °C for daily maxima. Soil temperatures in plots burnt 7 years previously were most similar to plots burned 15 + years ago indicating the potential for soil temperatures to recover as vegetation regrows. Our findings that prescribed peatland vegetation burning alters soil thermal regime should provide an impetus for further research to understand the consequences of thermal regime change for carbon processing and release, and hydrological processes, in these peatlands. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Uncertainty in predicting soil hydraulic properties at the hillslope scale with indirect methods

NASA Astrophysics Data System (ADS)

Chirico, G. B.; Medina, H.; Romano, N.

2007-02-01

SummarySeveral hydrological applications require the characterisation of the soil hydraulic properties at large spatial scales. Pedotransfer functions (PTFs) are being developed as simplified methods to estimate soil hydraulic properties as an alternative to direct measurements, which are unfeasible for most practical circumstances. The objective of this study is to quantify the uncertainty in PTFs spatial predictions at the hillslope scale as related to the sampling density, due to: (i) the error in estimated soil physico-chemical properties and (ii) PTF model error. The analysis is carried out on a 2-km-long experimental hillslope in South Italy. The method adopted is based on a stochastic generation of patterns of soil variables using sequential Gaussian simulation, conditioned to the observed sample data. The following PTFs are applied: Vereecken's PTF [Vereecken, H., Diels, J., van Orshoven, J., Feyen, J., Bouma, J., 1992. Functional evaluation of pedotransfer functions for the estimation of soil hydraulic properties. Soil Sci. Soc. Am. J. 56, 1371-1378] and HYPRES PTF [Wösten, J.H.M., Lilly, A., Nemes, A., Le Bas, C., 1999. Development and use of a database of hydraulic properties of European soils. Geoderma 90, 169-185]. The two PTFs estimate reliably the soil water retention characteristic even for a relatively coarse sampling resolution, with prediction uncertainties comparable to the uncertainties in direct laboratory or field measurements. The uncertainty of soil water retention prediction due to the model error is as much as or more significant than the uncertainty associated with the estimated input, even for a relatively coarse sampling resolution. Prediction uncertainties are much more important when PTF are applied to estimate the saturated hydraulic conductivity. In this case model error dominates the overall prediction uncertainties, making negligible the effect of the input error.

On-the-go mapping of soil mechanical resistance using a linear depth effect model.

USDA-ARS?s Scientific Manuscript database

An instrumented blade sensor was developed to map soil mechanical resistance as well as its change with depth. The sensor has become a part of the Integrated Soil Physical Properties Mapping System (ISPPMS), which also includes an optical and a capacitor-based sensor. The instrumented blade of the...