Fungal community composition and diversity vary with soil depths and landscape position in a no-till wheat cropping system.

USDA-ARS?s Scientific Manuscript database

Fungal communities in soil are critical to plant health and ecosystem processes in agricultural systems. Although the composition of fungal communities is often related to soil edaphic characteristic and host plant identity, there is a paucity of information on how communities vary with soil depth a...

Modeling soil organic carbon stocks and changes in Spain using the GEFSOC system

NASA Astrophysics Data System (ADS)

Álvaro-Fuentes, Jorge; Easter, Mark; Cantero-Martínez, Carlos; Paustian, Keith

2010-05-01

Currently, there is little information about soil organic carbon (SOC) stocks in Spain. To date the effects of land-use and soil management on SOC stocks in Spain have been evaluated in experimental fields under certain soil and climate conditions. However, these field experiments do not account for the spatial variability in management, cropping systems and soil and climate characteristics that exist in the whole territory. More realistic approaches like ecosystem-level dynamic simulation systems linked to geographic information systems (GIS) allow better assessments of SOC stocks at a regional or national level. The Global Environmental Facility Soil Organic Carbon (GEFSOC) system was recently built for this purpose (Milne et al., 2007) and it incorporates three widely used models for estimating SOC dynamics: (a) the Century ecosystem model; (b) the RothC soil C decomposition model; and (c) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. We modeled 9.5 Mha in northeast Spain using the GEFSOC system to predict SOC stocks and changes comprising: pasture, forest, cereal-fallow, cereal monoculture, orchards, rice, irrigated land and grapes and olives. The spatial distribution of the different land use categories and their change over time was obtained from the European Corine database and from Spanish census data on land use from 1926 to 2007. At the same time, current and historical management information was collected from different sources in order to have a fairly well picture of changes in land use and management for this area. Soil parameters needed by the system were obtained from the European soil map (1 km x 1 km) and climate data was produced by the Meteorology State Agency (Ministry of the Environment and Rural and Marine Environs of Spain). The SOC stocks simulated were validated with SOC values from the European SOC map and from other national studies. Modeled SOC results suggested that spatial-based approaches are crucial for quantify SOC stocks and changes in Spain.

Soil and Land Resources Information System (SLISYS-Tarim) for Sustainable Management of River Oases along the Tarim River, China

NASA Astrophysics Data System (ADS)

Othmanli, Hussein; Zhao, Chengyi; Stahr, Karl

2017-04-01

The Tarim River Basin is the largest continental basin in China. The region has extremely continental desert climate characterized by little rainfall <50 mm/a and high potential evaporation >3000 mm/a. The climate change is affecting severely the basin causing soil salinization, water shortage, and regression in crop production. Therefore, a Soil and Land Resources Information System (SLISYS-Tarim) for the regional simulation of crop yield production in the basin was developed. The SLISYS-Tarim consists of a database and an agro-ecological simulation model EPIC (Environmental Policy Integrated Climate). The database comprises relational tables including information about soils, terrain conditions, land use, and climate. The soil data implicate information of 50 soil profiles which were dug, analyzed, described and classified in order to characterize the soils in the region. DEM data were integrated with geological maps to build a digital terrain structure. Remote sensing data of Landsat images were applied for soil mapping, and for land use and land cover classification. An additional database for climate data, land management and crop information were linked to the system, too. Construction of the SLISYS-Tarim database was accomplished by integrating and overlaying the recommended thematic maps within environment of the geographic information system (GIS) to meet the data standard of the global and national SOTER digital database. This database forms appropriate input- and output data for the crop modelling with the EPIC model at various scales in the Tarim Basin. The EPIC model was run for simulating cotton production under a constructed scenario characterizing the current management practices, soil properties and climate conditions. For the EPIC model calibration, some parameters were adjusted so that the modeled cotton yield fits to the measured yield on the filed scale. The validation of the modeling results was achieved in a later step based on remote sensing data. The simulated cotton yield varied according to field management, soil type and salinity level, where soil salinity was the main limiting factor. Furthermore, the calibrated and validated EPIC model was run under several scenarios of climate conditions and land management practices to estimate the effect of climate change on cotton production and sustainability of agriculture systems in the basin. The application of SLISYS-Tarim showed that this database can be a suitable framework for storage and retrieval of soil and terrain data at various scales. The simulation with the EPIC model can assess the impact of climate change and management strategies. Therefore, SLISYS-Tarim can be a good tool for regional planning and serve the decision support system on regional and national scale.

A potential global soils data base

NASA Technical Reports Server (NTRS)

Stoner, E. R.; Joyce, A. T.; Hogg, H. C.

1984-01-01

A general procedure is outlined for refining the existing world soil maps from the existing 1:1 million scale to 1:250,000 through the interpretation of Landsat MSS and TM images, and the use of a Geographic Information System to relate the soils maps to available information on climate, topography, geology, and vegetation.

SOIL Geo-Wiki: A tool for improving soil information

NASA Astrophysics Data System (ADS)

Skalský, Rastislav; Balkovic, Juraj; Fritz, Steffen; See, Linda; van der Velde, Marijn; Obersteiner, Michael

2014-05-01

Crowdsourcing is increasingly being used as a way of collecting data for scientific research, e.g. species identification, classification of galaxies and unravelling of protein structures. The WorldSoilProfiles.org database at ISRIC is a global collection of soil profiles, which have been 'crowdsourced' from experts. This system, however, requires contributors to have a priori knowledge about soils. Yet many soil parameters can be observed in the field without specific knowledge or equipment such as stone content, soil depth or color. By crowdsourcing this information over thousands of locations, the uncertainty in current soil datasets could be radically reduced, particularly in areas currently without information or where multiple interpretations are possible from different existing soil maps. Improved information on soils could benefit many research fields and applications. Better soil data could enhance assessments of soil ecosystem services (e.g. soil carbon storage) and facilitate improved process-based ecosystem modeling from local to global scales. Geo-Wiki is a crowdsourcing tool that was developed at IIASA for land cover validation using satellite imagery. Several branches are now available focused on specific aspects of land cover validation, e.g. validating cropland extent or urbanized areas. Geo-Wiki Pictures is a smart phone application for collecting land cover related information on the ground. The extension of Geo-Wiki to a mobile environment provides a tool for experts in land cover validation but is also a way of reaching the general public in the validation of land cover. Here we propose a Soil Geo-Wiki tool that builds on the existing functionality of the Geo-Wiki application, which will be largely designed for the collection and sharing of soil information. Two distinct applications are envisaged: an expert-oriented application mainly for scientific purposes, which will use soil science related language (e.g. WRB or any other global reference soil classification system) and allow experts to upload and share scientifically rigorous soil data; and an application oriented towards the general public, which will be more focused on describing well observed, individual soil properties using simplified classification keys. The latter application will avoid the use of soil science related terminology and focus on the most useful soil parameters such as soil surface features, stone content, soil texture, soil plasticity, calcium carbonate presence, soil color, soil pH, soil repellency, and soil depth. Collection of soil and landscape pictures will also be supported in Soil Geo-Wiki to allow for comprehensive data collection while simultaneously allowing for quality checking by experts.

NASA Soil Moisture Data Products and Their Incorporation in DREAM

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette

2005-01-01

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

Integrated Universal Soil Loss Equation (USLE) and Geographical Information System (GIS) for Soil Erosion Measurement in basin of Asap river, Central Vietnam

NASA Astrophysics Data System (ADS)

Pham Gia, Tung; Degener, Jan; Kappas, Martin

2017-04-01

The study was conducted in Asap river basin, A Luoi district, Thua Thien Hue Province, Vietnam, using the Universal Soil Loss Equation (USLE) and Geographical Information System (GIS) to determine the soil erosion status. The results show strong effect of the heavy rainfall and high slope on the erosion level in the research area. More than 40% of land area lost over 10 tons/ha/year. The natural forest land lost the most by averagely is 38.4 tons/ha/year, while the agricultural land showed less with 2.79 tons for paddy rice land use type and 7.58 tons for upland crops yearly. Comparison between some places of Vietnam and the Southeast Asia showed that soil erosion in watersheds of Asap is more serious. We have been proposed a recommendation on changing the classification system of land use type in Vietnam for more accurate in soil erosion measurement. Keywords: Land use type, Soil erosion, USLE, Central Vietnam.

Toward Soil Spatial Information Systems (SSIS) for global modeling and ecosystem management

NASA Technical Reports Server (NTRS)

Baumgardner, Marion F.

1995-01-01

The general objective is to conduct research to contribute toward the realization of a world soils and terrain (SOTER) database, which can stand alone or be incorporated into a more complete and comprehensive natural resources digital information system. The following specific objectives are focussed on: (1) to conduct research related to (a) translation and correlation of different soil classification systems to the SOTER database legend and (b) the inferfacing of disparate data sets in support of the SOTER Project; (2) to examine the potential use of AVHRR (Advanced Very High Resolution Radiometer) data for delineating meaningful soils and terrain boundaries for small scale soil survey (range of scale: 1:250,000 to 1:1,000,000) and terrestrial ecosystem assessment and monitoring; and (3) to determine the potential use of high dimensional spectral data (220 reflectance bands with 10 m spatial resolution) for delineating meaningful soils boundaries and conditions for the purpose of detailed soil survey and land management.

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

PubMed

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

2017-05-16

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

Targeting the right input data to improve crop modeling at global level

NASA Astrophysics Data System (ADS)

Adam, M.; Robertson, R.; Gbegbelegbe, S.; Jones, J. W.; Boote, K. J.; Asseng, S.

2012-12-01

Designed for location-specific simulations, the use of crop models at a global level raises important questions. Crop models are originally premised on small unit areas where environmental conditions and management practices are considered homogeneous. Specific information describing soils, climate, management, and crop characteristics are used in the calibration process. However, when scaling up for global application, we rely on information derived from geographical information systems and weather generators. To run crop models at broad, we use a modeling platform that assumes a uniformly generated grid cell as a unit area. Specific weather, specific soil and specific management practices for each crop are represented for each of the cell grids. Studies on the impacts of the uncertainties of weather information and climate change on crop yield at a global level have been carried out (Osborne et al, 2007, Nelson et al., 2010, van Bussel et al, 2011). Detailed information on soils and management practices at global level are very scarce but recognized to be of critical importance (Reidsma et al., 2009). Few attempts to assess the impact of their uncertainties on cropping systems performances can be found. The objectives of this study are (i) to determine sensitivities of a crop model to soil and management practices, inputs most relevant to low input rainfed cropping systems, and (ii) to define hotspots of sensitivity according to the input data. We ran DSSAT v4.5 globally (CERES-CROPSIM) to simulate wheat yields at 45arc-minute resolution. Cultivar parameters were calibrated and validated for different mega-environments (results not shown). The model was run for nitrogen-limited production systems. This setting was chosen as the most representative to simulate actual yield (especially for low-input rainfed agricultural systems) and assumes crop growth to be free of any pest and diseases damages. We conducted a sensitivity analysis on contrasting management practices, initial soil conditions, and soil characteristics information. Management practices were represented by planting date and the amount of fertilizer, initial conditions estimates for initial nitrogen, soil water, and stable soil carbon, and soil information is based on a simplified version of the WISE database, characterized by soil organic matter, texture and soil depth. We considered these factors as the most important determinants of nutrient supply to crops during their growing season. Our first global results demonstrate that the model is most sensitive to the initial conditions in terms of soil carbon and nitrogen (CN): wheat yields decreased by 45% when soil CN is null and increase by 15% when twice the soil CN content of the reference run is used. The yields did not appear to be very sensitive to initial soil water conditions, varying from 0% yield increase when initial soil water is set to wilting point to 6% yield increase when it was set to field capacity. They are slightly sensitive to nitrogen application: 8% yield decrease when no N is applied to 9% yield increase when 150 kg.ha-1 is applied. However, with closer examination of results, the model is more sensitive to nitrogen application than to initial soil CN content in Vietnam, Thailand and Japan compared to the rest of the world. More analyses per region and results on the planting dates and soil properties will be presented.

Recent development in preparation of European soil hydraulic maps

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

77 FR 12234 - Changes in Hydric Soils Database Selection Criteria

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-29

... Conservation Service [Docket No. NRCS-2011-0026] Changes in Hydric Soils Database Selection Criteria AGENCY... Changes to the National Soil Information System (NASIS) Database Selection Criteria for Hydric Soils of the United States. SUMMARY: The National Technical Committee for Hydric Soils (NTCHS) has updated the...

The Use of a Geographic Information System and Remote Sensing Technology for Monitoring Land Use and Soil Carbon Change in the Subtropical Dry Forest Life Zone of Puerto Rico

NASA Technical Reports Server (NTRS)

Velez-Rodriguez, Linda L. (Principal Investigator)

1996-01-01

Aerial photography, one of the first form of remote sensing technology, has long been an invaluable means to monitor activities and conditions at the Earth's surface. Geographic Information Systems or GIS is the use of computers in showing and manipulating spatial data. This report will present the use of geographic information systems and remote sensing technology for monitoring land use and soil carbon change in the subtropical dry forest life zone of Puerto Rico. This research included the south of Puerto Rico that belongs to the subtropical dry forest life zone. The Guanica Commonwealth Forest Biosphere Reserve and the Jobos Bay National Estuarine Research Reserve are studied in detail, because of their location in the subtropical dry forest life zone. Aerial photography, digital multispectral imagery, soil samples, soil survey maps, field inspections, and differential global positioning system (DGPS) observations were used.

Black walnut suitability index: a Natural Resources Conservation Service national soil information system based interpretive model

Treesearch

Douglas c. Wallace; Fred J. Young

2008-01-01

Suitable site conditions are essential for productive growth of black walnut (Juglans nigra L.). Field officers at the Natural Resources Conservation Service (NRCS) in the Midwest are often asked, "What is a good walnut soil?" Current NRCS information available to most field offices rates soils only as "suitable" or "...

BOREAS Regional Soils Data in Raster Format and AEAC Projection

NASA Technical Reports Server (NTRS)

Monette, Bryan; Knapp, David; Hall, Forrest G. (Editor); Nickeson, Jaime (Editor)

2000-01-01

This data set was gridded by BOREAS Information System (BORIS) Staff from a vector data set received from the Canadian Soil Information System (CanSIS). The original data came in two parts that covered Saskatchewan and Manitoba. The data were gridded and merged into one data set of 84 files covering the BOREAS region. The data were gridded into the AEAC projection. Because the mapping of the two provinces was done separately in the original vector data, there may be discontinuities in some of the soil layers because of different interpretations of certain soil properties. The data are stored in binary, image format files.

Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring

NASA Astrophysics Data System (ADS)

Crow, W. T.; Bolten, J. D.

2014-12-01

Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.

Accessing Queensland's soil information - an open data revolution!

NASA Astrophysics Data System (ADS)

Bryant, Kelly; O'Brien, Lauren; Brough, Daniel

2015-07-01

The Queensland government is the custodian of soil and land resource information with an estimated value of 75 million. The Soil and Land Information (SALI) system houses this data from over 600 distinct studies with some 96,000 soil observations dating back to the 1940s. This data is now not only used by government but by universities, councils, landowners, consultants and schools. Providing this information to the public in an easy and accessible way, with a focus towards online delivery is crucial. Previous issues with distribution of online soils information in Queensland have stemmed not only from limits to technology but also, changing departmental structures and multiple websites. The department which manages soils information in Queensland has undergone nine name changes in the last 12 years due to Machinery of Government (MoG) restructures. This constantly changing web presence and branding is as confusing for people sourcing soils information as it is for those providing it. The Queensland government has now moved to a whole of government online environment. This is a single website with no reference to the convoluted structures within government or department names. The aim is to prevent impacts from future MoG changes on the provision of data and information to the public. Queensland government soils now has a single dedicated website (qld.gov.au/environment/land/soil) which has allowed us to start to build a repository for soils information and is a single portal for people to access soils data. It has been demonstrated that this consistent approach to websites improves trust and confidence of users [1] and from this, confidence in using Queensland soils information and data and ultimately better land management decisions.

Perennial crop phase effects on soil fertility

USDA-ARS?s Scientific Manuscript database

There is a need to develop agricultural management systems that enhance soil fertility and reduce reliance on external inputs. Perennial phases in crop rotations are effective at restoring soil fertility, though little information exists in the northern Great Plains regarding soil-based outcomes re...

Urban gray vs. urban green vs. soil protection — Development of a systemic solution to soil sealing management on the example of Germany

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

Artmann, Martina, E-mail: m.artmann@ioer.de

Managing urban soil sealing is a difficult venture due to its spatial heterogeneity and embedding in a socio-ecological system. A systemic solution is needed to tackle its spatial, ecological and social sub-systems. This study develops a guideline for urban actors to find a systemic solution to soil sealing management based on two case studies in Germany: Munich and Leipzig. Legal-planning, informal-planning, economic-fiscal, co-operative and informational responses were evaluated by indicators to proof which strategy considers the spatial complexity of urban soil sealing (systemic spatial efficiency) and, while considering spatial complexity, to assess what the key management areas for action aremore » to reduce the ecological impacts by urban soil sealing (ecological impact efficiency) and to support an efficient implementation by urban actors (social implementation efficiency). Results suggest framing the systemic solution to soil sealing management through a cross-scale, legal-planning development strategy embedded in higher European policies. Within the socio-ecological system, the key management area for action should focus on the protection of green infrastructure being of high value for actors from the European to local scales. Further efforts are necessary to establish a systemic monitoring concept to optimize socio-ecological benefits and avoid trade-offs such as between urban infill development and urban green protection. This place-based study can be regarded as a stepping stone on how to develop systemic strategies by considering different spatial sub-targets and socio-ecological systems. - Highlights: • Urban soil sealing management is spatially complex. • The legal-planning strategy supports a systemic sealing management. • Urban green infrastructure protection should be in the management focus. • Soil protection requires policies from higher levels of government. • A systemic urban soil sealing monitoring concept is needed.« less

Prioritization of catchments based on soil erosion using remote sensing and GIS.

PubMed

Khadse, Gajanan K; Vijay, Ritesh; Labhasetwar, Pawan K

2015-06-01

Water and soil are the most essential natural resources for socioeconomic development and sustenance of life. A study of soil and water dynamics at a watershed level facilitates a scientific approach towards their conservation and management. Remote sensing and Geographic Information System are tools that help to plan and manage natural resources on watershed basis. Studies were conducted for the formulation of catchment area treatment plan based on watershed prioritization with soil erosion studies using remote sensing techniques, corroborated with Geographic Information System (GIS), secondary data and ground truth information. Estimation of runoff and sediment yield is necessary in prioritization of catchment for the design of soil conservation structures and for identifying the critical erosion-prone areas of a catchment for implementation of best management plan with limited resources. The Universal Soil Loss Equation, Sediment Yield Determination and silt yield index methods are used for runoff and soil loss estimation for prioritization of the catchments. On the basis of soil erosion classes, the watersheds were grouped into very high, high, moderate and low priorities. High-priority watersheds need immediate attention for soil and water conservation, whereas low-priority watershed having good vegetative cover and low silt yield index may not need immediate attention for such treatments.

Soil quality differences in a mature alley cropping system in temperate North America

USDA-ARS?s Scientific Manuscript database

Alley cropping in agroforestry practices has been shown to improve soil quality, however information on long-term effects (>10 years) of alley cropping on soils in the temperate zone is very limited. The objective of this study was to examine effects of management, landscape, and soil depth on soil...

The auto-tuned land data assimilation system (ATLAS)

USDA-ARS?s Scientific Manuscript database

Land data assimilation systems are tasked with the merging remotely-sensed soil moisture retrievals with information derived from a soil water balance model driven (principally) by observed rainfall. The performance of such systems is frequently degraded by the imprecise specification of parameters ...

The History of Soil Mapping and Classification in Europe: The role of the European Commission

NASA Astrophysics Data System (ADS)

Montanarella, Luca

2014-05-01

Early systematic soil mapping in Europe dates back to the early times of soil science in the 19th Century and was developed at National scales mostly for taxation purposes. National soil classification systems emerged out of the various scientific communities active at that time in leading countries like Germany, Austria, France, Belgium, United Kingdom and many others. Different scientific communities were leading in the various countries, in some cases stemming from geological sciences, in others as a branch of agricultural sciences. Soil classification for the purpose of ranking soils for their capacity to be agriculturally productive emerged as the main priority, allowing in some countries for very detailed and accurate soil maps at 1:5,000 scale and larger. Detailed mapping was mainly driven by taxation purposes in the early times but evolved in several countries also as a planning and management tool for farms and local administrations. The need for pan-European soil mapping and classification efforts emerged only after World War II in the early 1950's under the auspices of FAO with the aim to compile a common European soil map as a contribution to the global soil mapping efforts of FAO at that time. These efforts evolved over the next decades, with the support of the European Commission, towards the establishment of a permanent network of National soil survey institutions (the European Soil Bureau Network). With the introduction of digital soil mapping technologies, the new European Soil Information System (EUSIS) was established, incorporating data at multiple scales for the EU member states and bordering countries. In more recent years, the formal establishment of the European Soil Data Centre (ESDAC) hosted by the European Commission, together with a formal legal framework for soil mapping and soil classification provided by the INSPIRE directive and the related standardization and harmonization efforts, has led to the operational development of advanced digital soil mapping techniques supporting the contribution of Europe to a common global soil information system under the coordination of the Global Soil Partnership (GSP) of FAO. Further information: http://eusoils.jrc.ec.europa.eu/ References: Mark G Kibblewhite, Ladislav Miko, Luca Montanarella, Legal frameworks for soil protection: current development and technical information requirements, Current Opinion in Environmental Sustainability, Volume 4, Issue 5, November 2012, Pages 573-577. Luca Montanarella, Ronald Vargas, Global governance of soil resources as a necessary condition for sustainable development, Current Opinion in Environmental Sustainability, Volume 4, Issue 5, November 2012, Pages 559-564.

7 CFR 1470.3 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

..., tribal, or territorial law for the express purpose of developing and carrying out a local soil and water...,” “soil conservation district,” “soil and water conservation district,” “resource conservation district... practices and conservation management systems. It contains detailed information on the conservation of soil...

7 CFR 1470.3 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

..., tribal, or territorial law for the express purpose of developing and carrying out a local soil and water...,” “soil conservation district,” “soil and water conservation district,” “resource conservation district... practices and conservation management systems. It contains detailed information on the conservation of soil...

7 CFR 1470.3 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

..., tribal, or territorial law for the express purpose of developing and carrying out a local soil and water...,” “soil conservation district,” “soil and water conservation district,” “resource conservation district... practices and conservation management systems. It contains detailed information on the conservation of soil...

Coupling HYDRUS-1D with ArcGIS to estimate pesticide accumulation and leaching risk on a regional basis.

PubMed

Anlauf, Ruediger; Schaefer, Jenny; Kajitvichyanukul, Puangrat

2018-07-01

HYDRUS-1D is a well-established reliable instrument to simulate water and pesticide transport in soils. It is, however, a point-specific model which is usually used for site-specific simulations. Aim of the investigation was the development of pesticide accumulation and leaching risk maps for regions combining HYDRUS-1D as a model for pesticide fate with regional data in a geographical information system (GIS). It was realized in form of a python tool in ArcGIS. Necessary high resolution local soil information, however, is very often not available. Therefore, worldwide interpolated 250-m-grid soil data (SoilGrids.org) were successfully incorporated to the system. The functionality of the system is shown by examples from Thailand, where example regions that differ in soil properties and climatic conditions were exposed in the model system to pesticides with different properties. A practical application of the system will be the identification of areas where measures to optimize pesticide use should be implemented with priority. Copyright © 2018 Elsevier Ltd. All rights reserved.

Plant-uptake of uranium: Hydroponic and soil system studies

USGS Publications Warehouse

Ramaswami, A.; Carr, P.; Burkhardt, M.

2001-01-01

Limited information is available on screening and selection of terrestrial plants for uptake and translocation of uranium from soil. This article evaluates the removal of uranium from water and soil by selected plants, comparing plant performance in hydroponic systems with that in two soil systems (a sandy-loam soil and an organic-rich soil). Plants selected for this study were Sunflower (Helianthus giganteus), Spring Vetch (Vicia sativa), Hairy Vetch (Vicia villosa), Juniper (Juniperus monosperma), Indian Mustard (Brassica juncea), and Bush Bean (Phaseolus nanus). Plant performance was evaluated both in terms of the percent uranium extracted from the three systems, as well as the biological absorption coefficient (BAC) that normalized uranium uptake to plant biomass. Study results indicate that uranium extraction efficiency decreased sharply across hydroponic, sandy and organic soil systems, indicating that soil organic matter sequestered uranium, rendering it largely unavailable for plant uptake. These results indicate that site-specific soils must be used to screen plants for uranium extraction capability; plant behavior in hydroponic systems does not correlate well with that in soil systems. One plant species, Juniper, exhibited consistent uranium extraction efficiencies and BACs in both sandy and organic soils, suggesting unique uranium extraction capabilities.

Survey of methods for soil moisture determination

NASA Technical Reports Server (NTRS)

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

1979-01-01

Existing and proposed methods for soil moisture determination are discussed. These include: (1) in situ investigations including gravimetric, nuclear, and electromagnetic techniques; (2) remote sensing approaches that use the reflected solar, thermal infrared, and microwave portions of the electromagnetic spectrum; and (3) soil physics models that track the behavior of water in the soil in response to meteorological inputs (precipitation) and demands (evapotranspiration). The capacities of these approaches to satisfy various user needs for soil moisture information vary from application to application, but a conceptual scheme for merging these approaches into integrated systems to provide soil moisture information is proposed that has the potential for meeting various application requirements.

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

2014-01-01

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

SoilInfo App: global soil information on your palm

NASA Astrophysics Data System (ADS)

Hengl, Tomislav; Mendes de Jesus, Jorge

2015-04-01

ISRIC ' World Soil Information has released in 2014 and app for mobile de- vices called 'SoilInfo' (http://soilinfo-app.org) and which aims at providing free access to the global soil data. SoilInfo App (available for Android v.4.0 Ice Cream Sandwhich or higher, and Apple v.6.x and v.7.x iOS) currently serves the Soil- Grids1km data ' a stack of soil property and class maps at six standard depths at a resolution of 1 km (30 arc second) predicted using automated geostatistical mapping and global soil data models. The list of served soil data includes: soil organic carbon (), soil pH, sand, silt and clay fractions (%), bulk density (kg/m3), cation exchange capacity of the fine earth fraction (cmol+/kg), coarse fragments (%), World Reference Base soil groups, and USDA Soil Taxonomy suborders (DOI: 10.1371/journal.pone.0105992). New soil properties and classes will be continuously added to the system. SoilGrids1km are available for download under a Creative Commons non-commercial license via http://soilgrids.org. They are also accessible via a Representational State Transfer API (http://rest.soilgrids.org) service. SoilInfo App mimics common weather apps, but is also largely inspired by the crowdsourcing systems such as the OpenStreetMap, Geo-wiki and similar. Two development aspects of the SoilInfo App and SoilGrids are constantly being worked on: Data quality in terms of accuracy of spatial predictions and derived information, and Data usability in terms of ease of access and ease of use (i.e. flexibility of the cyberinfrastructure / functionalities such as the REST SoilGrids API, SoilInfo App etc). The development focus in 2015 is on improving the thematic and spatial accuracy of SoilGrids predictions, primarily by using finer resolution covariates (250 m) and machine learning algorithms (such as random forests) to improve spatial predictions.

Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations

NASA Technical Reports Server (NTRS)

Reichle, R. H.

2010-01-01

Root zone soil moisture controls the land-atmosphere exchange of water and energy and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments we assimilate synthetic surface soil moisture observations into four different models (Catchment, Mosaic, Noah and CLM) using the Ensemble Kalman Filter. We demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Our experiments also suggest that (faced with unknown true subsurface physics) overestimating surface to root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Finally, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.

Unified Science Information Model for SoilSCAPE using the Mercury Metadata Search System

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Lu, Kefa; Palanisamy, Giri; Cook, Robert; Santhana Vannan, Suresh; Moghaddam, Mahta Clewley, Dan; Silva, Agnelo; Akbar, Ruzbeh

2013-12-01

SoilSCAPE (Soil moisture Sensing Controller And oPtimal Estimator) introduces a new concept for a smart wireless sensor web technology for optimal measurements of surface-to-depth profiles of soil moisture using in-situ sensors. The objective is to enable a guided and adaptive sampling strategy for the in-situ sensor network to meet the measurement validation objectives of spaceborne soil moisture sensors such as the Soil Moisture Active Passive (SMAP) mission. This work is being carried out at the University of Michigan, the Massachusetts Institute of Technology, University of Southern California, and Oak Ridge National Laboratory. At Oak Ridge National Laboratory we are using Mercury metadata search system [1] for building a Unified Information System for the SoilSCAPE project. This unified portal primarily comprises three key pieces: Distributed Search/Discovery; Data Collections and Integration; and Data Dissemination. Mercury, a Federally funded software for metadata harvesting, indexing, and searching would be used for this module. Soil moisture data sources identified as part of this activity such as SoilSCAPE and FLUXNET (in-situ sensors), AirMOSS (airborne retrieval), SMAP (spaceborne retrieval), and are being indexed and maintained by Mercury. Mercury would be the central repository of data sources for cal/val for soil moisture studies and would provide a mechanism to identify additional data sources. Relevant metadata from existing inventories such as ORNL DAAC, USGS Clearinghouse, ARM, NASA ECHO, GCMD etc. would be brought in to this soil-moisture data search/discovery module. The SoilSCAPE [2] metadata records will also be published in broader metadata repositories such as GCMD, data.gov. Mercury can be configured to provide a single portal to soil moisture information contained in disparate data management systems located anywhere on the Internet. Mercury is able to extract, metadata systematically from HTML pages or XML files using a variety of methods including OAI-PMH [3]. The Mercury search interface then allows users to perform simple, fielded, spatial and temporal searches across a central harmonized index of metadata. Mercury supports various metadata standards including FGDC, ISO-19115, DIF, Dublin-Core, Darwin-Core, and EML. This poster describes in detail how Mercury implements the Unified Science Information Model for Soil moisture data. References: [1]Devarakonda R., et al. Mercury: reusable metadata management, data discovery and access system. Earth Science Informatics (2010), 3(1): 87-94. [2]Devarakonda R., et al. Daymet: Single Pixel Data Extraction Tool. http://daymet.ornl.gov/singlepixel.html (2012). Last Accesses 10-01-2013 [3]Devarakonda R., et al. Data sharing and retrieval using OAI-PMH. Earth Science Informatics (2011), 4(1): 1-5.

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.

The effects of anaerobic soil disinfestation on weed and nematode control, fruit yield and quality of Florida fresh-market tomato

USDA-ARS?s Scientific Manuscript database

Anaerobic soil disinfestation (ASD) is considered a promising sustainable alternative to chemical soil fumigation (CSF), and has been shown to be effective against soil-borne diseases, plant-parasitic nematodes, and weeds in several crop production systems. Nevertheless, limited information is avail...

Information and Complexity Measures Applied to Observed and Simulated Soil Moisture Time Series

USDA-ARS?s Scientific Manuscript database

Time series of soil moisture-related parameters provides important insights in functioning of soil water systems. Analysis of patterns within these time series has been used in several studies. The objective of this work was to compare patterns in observed and simulated soil moisture contents to u...

Using a spatial and tabular database to generate statistics from terrain and spectral data for soil surveys

USGS Publications Warehouse

Horvath , E.A.; Fosnight, E.A.; Klingebiel, A.A.; Moore, D.G.; Stone, J.E.; Reybold, W.U.; Petersen, G.W.

1987-01-01

A methodology has been developed to create a spatial database by referencing digital elevation, Landsat multispectral scanner data, and digitized soil premap delineations of a number of adjacent 7.5-min quadrangle areas to a 30-m Universal Transverse Mercator projection. Slope and aspect transformations are calculated from elevation data and grouped according to field office specifications. An unsupervised classification is performed on a brightness and greenness transformation of the spectral data. The resulting spectral, slope, and aspect maps of each of the 7.5-min quadrangle areas are then plotted and submitted to the field office to be incorporated into the soil premapping stages of a soil survey. A tabular database is created from spatial data by generating descriptive statistics for each data layer within each soil premap delineation. The tabular data base is then entered into a data base management system to be accessed by the field office personnel during the soil survey and to be used for subsequent resource management decisions.Large amounts of data are collected and archived during resource inventories for public land management. Often these data are stored as stacks of maps or folders in a file system in someone's office, with the maps in a variety of formats, scales, and with various standards of accuracy depending on their purpose. This system of information storage and retrieval is cumbersome at best when several categories of information are needed simultaneously for analysis or as input to resource management models. Computers now provide the resource scientist with the opportunity to design increasingly complex models that require even more categories of resource-related information, thus compounding the problem.Recently there has been much emphasis on the use of geographic information systems (GIS) as an alternative method for map data archives and as a resource management tool. Considerable effort has been devoted to the generation of tabular databases, such as the U.S. Department of Agriculture's SCS/S015 (Soil Survey Staff, 1983), to archive the large amounts of information that are collected in conjunction with mapping of natural resources in an easily retrievable manner.During the past 4 years the U.S. Geological Survey's EROS Data Center, in a cooperative effort with the Bureau of Land Management (BLM) and the Soil Conservation Service (SCS), developed a procedure that uses spatial and tabular databases to generate elevation, slope, aspect, and spectral map products that can be used during soil premapping. The procedure results in tabular data, residing in a database management system, that are indexed to the final soil delineations and help quantify soil map unit composition.The procedure was developed and tested on soil surveys on over 600 000 ha in Wyoming, Nevada, and Idaho. A transfer of technology from the EROS Data Center to the BLM will enable the Denver BLM Service Center to use this procedure in soil survey operations on BLM lands. Also underway is a cooperative effort between the EROS Data Center and SCS to define and evaluate maps that can be produced as derivatives of digital elevation data for 7.5-min quadrangle areas, such as those used during the premapping stage of the soil surveys mentioned above, the idea being to make such products routinely available.The procedure emphasizes the applications of digital elevation and spectral data to order-three soil surveys on rangelands, and will:Incorporate digital terrain and spectral data into a spatial database for soil surveys.Provide hardcopy products (that can be generated from digital elevation model and spectral data) that are useful during the soil pre-mapping process.Incorporate soil premaps into a spatial database that can be accessed during the soil survey process along with terrain and spectral data.Summarize useful quantitative information for soil mapping and for making interpretations for resource management.

Mapping soil texture classes and optimization of the result by accuracy assessment

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Takács, Katalin; Bakacsi, Zsófia; Szabó, József; Pásztor, László

2014-05-01

There are increasing demands nowadays on spatial soil information in order to support environmental related and land use management decisions. The GlobalSoilMap.net (GSM) project aims to make a new digital soil map of the world using state-of-the-art and emerging technologies for soil mapping and predicting soil properties at fine resolution. Sand, silt and clay are among the mandatory GSM soil properties. Furthermore, soil texture class information is input data of significant agro-meteorological and hydrological models. Our present work aims to compare and evaluate different digital soil mapping methods and variables for producing the most accurate spatial prediction of texture classes in Hungary. In addition to the Hungarian Soil Information and Monitoring System as our basic data, digital elevation model and its derived components, geological database, and physical property maps of the Digital Kreybig Soil Information System have been applied as auxiliary elements. Two approaches have been applied for the mapping process. At first the sand, silt and clay rasters have been computed independently using regression kriging (RK). From these rasters, according to the USDA categories, we have compiled the texture class map. Different combinations of reference and training soil data and auxiliary covariables have resulted several different maps. However, these results consequentially include the uncertainty factor of the three kriged rasters. Therefore we have suited data mining methods as the other approach of digital soil mapping. By working out of classification trees and random forests we have got directly the texture class maps. In this way the various results can be compared to the RK maps. The performance of the different methods and data has been examined by testing the accuracy of the geostatistically computed and the directly classified results. We have used the GSM methodology to assess the most predictive and accurate way for getting the best among the several result maps. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Geostatistics, remote sensing and precision farming.

PubMed

Mulla, D J

1997-01-01

Precision farming is possible today because of advances in farming technology, procedures for mapping and interpolating spatial patterns, and geographic information systems for overlaying and interpreting several soil, landscape and crop attributes. The key component of precision farming is the map showing spatial patterns in field characteristics. Obtaining information for this map is often achieved by soil sampling. This approach, however, can be cost-prohibitive for grain crops. Soil sampling strategies can be simplified by use of auxiliary data provided by satellite or aerial photo imagery. This paper describes geostatistical methods for estimating spatial patterns in soil organic matter, soil test phosphorus and wheat grain yield from a combination of Thematic Mapper imaging and soil sampling.

Remote Sensing of Soils for Environmental Assessment and Management.

NASA Technical Reports Server (NTRS)

DeGloria, Stephen D.; Irons, James R.; West, Larry T.

2014-01-01

The next generation of imaging systems integrated with complex analytical methods will revolutionize the way we inventory and manage soil resources across a wide range of scientific disciplines and application domains. This special issue highlights those systems and methods for the direct benefit of environmental professionals and students who employ imaging and geospatial information for improved understanding, management, and monitoring of soil resources.

Holistic information evaluation of divergence of soil's properties by using of legacy data of large scale monitoring surveys

NASA Astrophysics Data System (ADS)

Mikheeva, Irina

2017-04-01

Identification of tendencies of soil's transformations is very important for adequate ecological and economical assessment of degradation of soils. But monitoring of conditions of soils, and other natural objects, bring up a number of important methodological questions, including the probabilistic and statistical analysis of the accumulated legacy data and their use for verification of quantitative estimates of natural processes. Owing to considerable natural variability there is a problem of a reliable assessment of contemporary soil evolution under the influence of environmental management and climate changes. When studying dynamics of soil quality it is necessary to consider soil as open complex system with parameters which significantly vary in space. The analysis of probabilistic distributions of attributes of studied system is informative for the characteristic of holistic state and behavior of the system. Therefore earlier we had offered the method of evaluation of alterations of soils by analysis of changes of pdf of their properties and their statistical entropy. The executed analysis of dynamics of pdf showed that often opposite tendencies to decrease and to increase of property can be shown at the same time. However to give an adequate quantitative evaluation of changes of soil properties it is necessary to characterize them in general. We proposed that it is reasonable to name processes of modern changes in soil properties concerning their start meaning by the term "divergence" and investigate it quantitatively. For this purpose we suggested to use value of information divergence which is defined as a measure of distinctions of pdf in compared objects or in various time. As the measure of dissimilarity, divergence should satisfy come conditions, the most important is scale-invariance property. Information divergence was used by us for evaluation of distinctions of soils according heterogeneity of factors of soil formation and with course of natural and anthropogenous processes. This characteristic allowed to allocate the most changed and vulnerable kinds and layers of soils, and also to range natural changes and anthropogenous impacts in size of their influence on properties of the soil. Case study was conducted on considerable part of the Priirtyshskaya plain in South of Western Siberia. Climate here is sharply continental and droughty. Soils were formed from ancient lake and alluvial deposits. It determined their mainly easy particle size distribution and spatial diversity of the texture. It is possible to judge rates and extent of manifestation of processes of degradation on alteration of properties of the main types of soils here: chestnut soils and Haplic Chernozems.

Study on an agricultural environment monitoring server system using Wireless Sensor Networks.

PubMed

Hwang, Jeonghwan; Shin, Changsun; Yoe, Hyun

2010-01-01

This paper proposes an agricultural environment monitoring server system for monitoring information concerning an outdoors agricultural production environment utilizing Wireless Sensor Network (WSN) technology. The proposed agricultural environment monitoring server system collects environmental and soil information on the outdoors through WSN-based environmental and soil sensors, collects image information through CCTVs, and collects location information using GPS modules. This collected information is converted into a database through the agricultural environment monitoring server consisting of a sensor manager, which manages information collected from the WSN sensors, an image information manager, which manages image information collected from CCTVs, and a GPS manager, which processes location information of the agricultural environment monitoring server system, and provides it to producers. In addition, a solar cell-based power supply is implemented for the server system so that it could be used in agricultural environments with insufficient power infrastructure. This agricultural environment monitoring server system could even monitor the environmental information on the outdoors remotely, and it could be expected that the use of such a system could contribute to increasing crop yields and improving quality in the agricultural field by supporting the decision making of crop producers through analysis of the collected information.

Exploring the potential offered by legacy soil databases for ecosystem services mapping of Central African soils

NASA Astrophysics Data System (ADS)

Verdoodt, Ann; Baert, Geert; Van Ranst, Eric

2014-05-01

Central African soil resources are characterised by a large variability, ranging from stony, shallow or sandy soils with poor life-sustaining capabilities to highly weathered soils that recycle and support large amounts of biomass. Socio-economic drivers within this largely rural region foster inappropriate land use and management, threaten soil quality and finally culminate into a declining soil productivity and increasing food insecurity. For the development of sustainable land use strategies targeting development planning and natural hazard mitigation, decision makers often rely on legacy soil maps and soil profile databases. Recent development cooperation financed projects led to the design of soil information systems for Rwanda, D.R. Congo, and (ongoing) Burundi. A major challenge is to exploit these existing soil databases and convert them into soil inference systems through an optimal combination of digital soil mapping techniques, land evaluation tools, and biogeochemical models. This presentation aims at (1) highlighting some key characteristics of typical Central African soils, (2) assessing the positional, geographic and semantic quality of the soil information systems, and (3) revealing its potential impacts on the use of these datasets for thematic mapping of soil ecosystem services (e.g. organic carbon storage, pH buffering capacity). Soil map quality is assessed considering positional and semantic quality, as well as geographic completeness. Descriptive statistics, decision tree classification and linear regression techniques are used to mine the soil profile databases. Geo-matching as well as class-matching approaches are considered when developing thematic maps. Variability in inherent as well as dynamic soil properties within the soil taxonomic units is highlighted. It is hypothesized that within-unit variation in soil properties highly affects the use and interpretation of thematic maps for ecosystem services mapping. Results will mainly be based on analyses done in Rwanda, but can be complemented with ongoing research results or prospects for Burundi.

Data Assimilation using observed streamflow and remotely-sensed soil moisture for improving sub-seasonal-to-seasonal forecasting

NASA Astrophysics Data System (ADS)

Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.

2017-12-01

Subseasonal-to-seasonal (S2S) forecasts of soil moisture and streamflow provides critical information for water and agricultural systems to support short-term planning and mangement. This study evaluates the role of observed streamflow and remotely-sensed soil moisture from SMAP (Soil Moisture Active Passive) mission in improving S2S streamflow and soil moisture forecasting using data assimilation (DA). We first show the ability to forecast soil moisture at monthly-to-seaasonal time scale by forcing climate forecasts with NASA's Land Information System and then compares the developed soil moisture forecast with the SMAP data over the Southeast US. Our analyses show significant skill in forecasting real-time soil moisture over 1-3 months using climate information. We also show that the developed soil moisture forecasts capture the observed severe drought conditions (2007-2008) over the Southeast US. Following that, we consider both SMAP data and observed streamflow for improving S2S streamflow and soil moisture forecasts for a pilot study area, Tar River basin, in NC. Towards this, we consider variational assimilation (VAR) of gauge-measured daily streamflow data in improving initial hydrologic conditions of Variable Infiltration Capacity (VIC) model. The utility of data assimilation is then assessed in improving S2S forecasts of streamflow and soil moisture through a retrospective analyses. Furthermore, the optimal frequency of data assimilation and optimal analysis window (number of past observations to use) are also assessed in order to achieve the maximum improvement in S2S forecasts of streamflow and soil moisture. Potential utility of updating initial conditions using DA and providing skillful forcings are also discussed.

Soil compaction vulnerability at Organ Pipe Cactus National Monument, Arizona

USGS Publications Warehouse

Webb, Robert H.; Nussear, Kenneth E.; Carmichael, Shinji; Esque, Todd C.

2014-01-01

Compaction vulnerability of different types of soils by hikers and vehicles is poorly known, particularly for soils of arid and semiarid regions. Engineering analyses have long shown that poorly sorted soils (for example, sandy loams) compact to high densities, whereas well-sorted soils (for example, eolian sand) do not compact, and high gravel content may reduce compaction. Organ Pipe Cactus National Monument (ORPI) in southwestern Arizona, is affected greatly by illicit activities associated with the United States–Mexico border, and has many soils that resource managers consider to be highly vulnerable to compaction. Using geospatial soils data for ORPI, compaction vulnerability was estimated qualitatively based on the amount of gravel and the degree of sorting of sand and finer particles. To test this qualitative assessment, soil samples were collected from 48 sites across all soil map units, and undisturbed bulk densities were measured. A scoring system was used to create a vulnerability index for soils on the basis of particle-size sorting, soil properties derived from Proctor compaction analyses, and the field undisturbed bulk densities. The results of the laboratory analyses indicated that the qualitative assessments of soil compaction vulnerability underestimated the area of high vulnerability soils by 73 percent. The results showed that compaction vulnerability of desert soils, such as those at ORPI, can be quantified using laboratory tests and evaluated using geographic information system analyses, providing a management tool that managers potentially could use to inform decisions about activities that reduce this type of soil disruption in protected areas.

Challenges in Interpreting and Validating Satellite Soil Moisture Information

USDA-ARS?s Scientific Manuscript database

Global soil moisture products are now being generated routinely using microwave-based satellite observing systems. These include the NASA Soil Moisture Active Passive (SMAP) mission. In order to fully exploit these observations they must be integrated with both in situ measurements and model-based e...

Benchmarking a soil moisture data assimilation system for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

Agricultural drought is defined as a shortage of moisture in the root zone of plants. Recently available satellite-based remote sensing data have accelerated development of drought early warning system by providing spatially continuous soil moisture information repeatedly at short-term interval. Non...

Digital mapping of soil properties in Zala County, Hungary for the support of county-level spatial planning and land management

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Fodor, Nándor; Bakacsi, Zsófia; Szabó, József; Illés, Gábor

2014-05-01

The main objective of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project is to significantly extend the potential, how demands on spatial soil related information could be satisfied in Hungary. Although a great amount of soil information is available due to former mappings and surveys, there are more and more frequently emerging discrepancies between the available and the expected data. The gaps are planned to be filled with optimized DSM products heavily based on legacy soil data, which still represent a valuable treasure of soil information at the present time. Impact assessment of the forecasted climate change and the analysis of the possibilities of the adaptation in the agriculture and forestry can be supported by scenario based land management modelling, whose results can be incorporated in spatial planning. This framework requires adequate, preferably timely and spatially detailed knowledge of the soil cover. For the satisfaction of these demands in Zala County (one of the nineteen counties of Hungary), the soil conditions of the agricultural areas were digitally mapped based on the most detailed, available recent and legacy soil data. The agri-environmental conditions were characterized according to the 1:10,000 scale genetic soil mapping methodology and the category system applied in the Hungarian soil-agricultural chemistry practice. The factors constraining the fertility of soils were featured according to the biophysical criteria system elaborated for the delimitation of naturally handicapped areas in the EU. Production related soil functions were regionalized incorporating agro-meteorological modelling. The appropriate derivatives of a 20m digital elevation model were used in the analysis. Multitemporal MODIS products were selected from the period of 2009-2011 representing different parts of the growing season and years with various climatic conditions. Additionally two climatic data layers, the 1:100.000 Geological Map of Hungary and the map of groundwater depth were used as auxiliary environmental covariables. Various soil related information were mapped in three distinct sets: (i) basic soil properties determining agri-environmental conditions (soil type according to the Hungarian genetic classification, rootable depth, sand and clay content for the 1st and 2nd soil layers, pH, OM and carbonate content for the plough layer); (ii) biophysical criteria of natural handicaps defined by common European system and (iii) agro-meteorologically modelled yield values for different crops, meteorological and management scenarios. The applied method(s) for the spatial inference of specific themes was/were suitably selected: regression and classification trees for categorical data, indicator kriging for probabilistic management of criterion information; and typically regression kriging for quantitative data. Our paper will present the mapping processes themselves, the resulted maps and some conclusions drawn from the experiences. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and by the European Union with the co-financing of the European Social Fund (TÁMOP-4.2.2.A-11/1/KONV-2012-0013.).

The role of soil microbes in the global carbon cycle: tracking the below-ground microbial processing of plant-derived carbon for manipulating carbon dynamics in agricultural systems

PubMed Central

Gougoulias, Christos; Clark, Joanna M; Shaw, Liz J

2014-01-01

It is well known that atmospheric concentrations of carbon dioxide (CO2) (and other greenhouse gases) have increased markedly as a result of human activity since the industrial revolution. It is perhaps less appreciated that natural and managed soils are an important source and sink for atmospheric CO2 and that, primarily as a result of the activities of soil microorganisms, there is a soil-derived respiratory flux of CO2 to the atmosphere that overshadows by tenfold the annual CO2 flux from fossil fuel emissions. Therefore small changes in the soil carbon cycle could have large impacts on atmospheric CO2 concentrations. Here we discuss the role of soil microbes in the global carbon cycle and review the main methods that have been used to identify the microorganisms responsible for the processing of plant photosynthetic carbon inputs to soil. We discuss whether application of these techniques can provide the information required to underpin the management of agro-ecosystems for carbon sequestration and increased agricultural sustainability. We conclude that, although crucial in enabling the identification of plant-derived carbon-utilising microbes, current technologies lack the high-throughput ability to quantitatively apportion carbon use by phylogentic groups and its use efficiency and destination within the microbial metabolome. It is this information that is required to inform rational manipulation of the plant–soil system to favour organisms or physiologies most important for promoting soil carbon storage in agricultural soil. PMID:24425529

Analyzing existing conventional soil information sources to be incorporated in thematic Spatial Data Infrastructures

NASA Astrophysics Data System (ADS)

Pascual-Aguilar, J. A.; Rubio, J. L.; Domínguez, J.; Andreu, V.

2012-04-01

New information technologies give the possibility of widespread dissemination of spatial information to different geographical scales from continental to local by means of Spatial Data Infrastructures. Also administrative awareness on the need for open access information services has allowed the citizens access to this spatial information through development of legal documents, such as the INSPIRE Directive of the European Union, adapted by national laws as in the case of Spain. The translation of the general criteria of generic Spatial Data Infrastructures (SDI) to thematic ones is a crucial point for the progress of these instruments as large tool for the dissemination of information. In such case, it must be added to the intrinsic criteria of digital information, such as the harmonization information and the disclosure of metadata, the own environmental information characteristics and the techniques employed in obtaining it. In the case of inventories and mapping of soils, existing information obtained by traditional means, prior to the digital technologies, is considered to be a source of valid information, as well as unique, for the development of thematic SDI. In this work, an evaluation of existing and accessible information that constitutes the basis for building a thematic SDI of soils in Spain is undertaken. This information framework has common features to other European Union states. From a set of more than 1,500 publications corresponding to the national territory of Spain, the study was carried out in those documents (94) found for five autonomous regions of northern Iberian Peninsula (Asturias, Cantabria, Basque Country, Navarra and La Rioja). The analysis was performed taking into account the criteria of soil mapping and inventories. The results obtained show a wide variation in almost all the criteria: geographic representation (projections, scales) and geo-referencing the location of the profiles, map location of profiles integrated with edaphic units, description and taxonomic classification systems of soils (FAO, Soil taxonomy, etc.), amount and type of soil analysis parameters and dates of the inventories. In conclusion, the construction of thematic SDI on soil should take into account, prior to the integration of all maps and inventories, a series of processes of harmonization that allows spatial continuity between existing information and also temporal identification of the inventories and maps. This should require the development of at least two types of integration tools: (1) enabling spatial continuity without contradictions between maps made at different times and with different criteria and (2) the development of information systems data (metadata) to highlight the characteristics of information and connection possibilities with other sources that comprise the Spatial Data Infrastructure. Acknowledgements This research has financed by the European Union within the framework of the GS Soil project (eContentplus Programme ECP-2008-GEO-318004).

Topographic controls on soil nutrient variations in a Silvopasture system

USDA-ARS?s Scientific Manuscript database

Topography plays a crucial role in the spatial distribution of nutrients in soils because of its influence on the flow and (re)distribution of water and energy in a landscape. Information on the spatial pattern of soil nutrient distribution would benefit management decisions to maximize crop yield a...

Sampling Soil for Characterization and Site Description

NASA Technical Reports Server (NTRS)

Levine, Elissa

1999-01-01

The sampling scheme for soil characterization within the GLOBE program is uniquely different from the sampling methods of the other protocols. The strategy is based on an understanding of the 5 soil forming factors (parent material, climate, biota, topography, and time) at each study site, and how each of these interact to produce a soil profile with unique characteristics and unique input and control into the atmospheric, biological, and hydrological systems. Soil profile characteristics, as opposed to soil moisture and temperature, vegetative growth, and atmospheric and hydrologic conditions, change very slowly, depending on the parameter being measured, ranging from seasonally to many thousands of years. Thus, soil information, including profile description and lab analysis, is collected only one time for each profile at a site. These data serve two purposes: 1) to supplement existing spatial information about soil profile characteristics across the landscape at local, regional, and global scales, and 2) to provide specific information within a given area about the basic substrate to which elements within the other protocols are linked. Because of the intimate link between soil properties and these other environmental elements, the static soil properties at a given site are needed to accurately interpret and understand the continually changing dynamics of soil moisture and temperature, vegetation growth and phenology, atmospheric conditions, and chemistry and turbidity in surface waters. Both the spatial and specific soil information can be used for modeling purposes to assess and make predictions about global change.

Evaluation of automated global mapping of Reference Soil Groups of WRB2015

NASA Astrophysics Data System (ADS)

Mantel, Stephan; Caspari, Thomas; Kempen, Bas; Schad, Peter; Eberhardt, Einar; Ruiperez Gonzalez, Maria

2017-04-01

SoilGrids is an automated system that provides global predictions for standard numeric soil properties at seven standard depths down to 200 cm, currently at spatial resolutions of 1km and 250m. In addition, the system provides predictions of depth to bedrock and distribution of soil classes based on WRB and USDA Soil Taxonomy (ST). In SoilGrids250m(1), soil classes (WRB, version 2006) consist of the RSG and the first prefix qualifier, whereas in SoilGrids1km(2), the soil class was assessed at RSG level. Automated mapping of World Reference Base (WRB) Reference Soil Groups (RSGs) at a global level has great advantages. Maps can be updated in a short time span with relatively little effort when new data become available. To translate soil names of older versions of FAO/WRB and national classification systems of the source data into names according to WRB 2006, correlation tables are used in SoilGrids. Soil properties and classes are predicted independently from each other. This means that the combinations of soil properties for the same cells or soil property-soil class combinations do not necessarily yield logical combinations when the map layers are studied jointly. The model prediction procedure is robust and probably has a low source of error in the prediction of RSGs. It seems that the quality of the original soil classification in the data and the use of correlation tables are the largest sources of error in mapping the RSG distribution patterns. Predicted patterns of dominant RSGs were evaluated in selected areas and sources of error were identified. Suggestions are made for improvement of WRB2015 RSG distribution predictions in SoilGrids. Keywords: Automated global mapping; World Reference Base for Soil Resources; Data evaluation; Data quality assurance References 1 Hengl T, de Jesus JM, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, et al. (2016) SoilGrids250m: global gridded soil information based on Machine Learning. Earth System Science Data (ESSD), in review. 2 Hengl T, de Jesus JM, MacMillan RA, Batjes NH, Heuvelink GBM, et al. (2014) SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE 9(8): e105992. doi:10.1371/journal.pone.0105992

National Soil Information System in Turkey

NASA Astrophysics Data System (ADS)

Emrah Erdogan, Hakki; Sahin, Mehmet; Sahin, Yuksel

2013-04-01

Land consolidation (LC) represents complexity if management, legal, economic and technical procedures realized in order to adjust the land structure according to actual human preferences and needs. It includes changes in ownership rights to land and other real estate property, exchange of parcels among owners, changes in parcel borders, parcel size and shape, joining and dividing of parcels, changes in land use, construction works as roads, bridges, water changes etc.. Since the subject of LC is agricultural lands, the quality of consolidation depends on the quality of soil data. General Directorate of Agrarian Reform (GDAR) is the responsible institution on land consolidation whole of Turkey. Under GDAR, National Soil Information System (NSIS) has been build up with base soil data in relevant scale (1:5000). NSIS contain detailed information on soil chemical and physical properties, current land use, parent material, land capability class, Storie Index Values. SI were used on land consolidation, land use planning and farm development services. LCC was used for land distribution, rental land; define of village settlement, consolidation, expropriation, reconstruction, reclamation, non-agricultural usage. LCC were also specified to subclasses in four different limited factors as i) flow and erosion risk ii) requirement of drainage and soil moisture iii) Limits of soil tillage and root (shallow soils, low water retention capacity, stony, salty .etc) iv) climatic limits. In this study, digital soil survey and mapping project located in Yumurtalik, Adana is presented as an example of NSIS data structure. The project cover an area of 45709 ha that include crop lands as an area of 28528 ha and other land use (urban, roads..etc) as an area of 17181 ha. Soil profiles were described in 45 different points and totally 1279 soil samples were collected in field study and the check bore hole were made in 3170 points.

History of Soil Survey and Evolution of the Brazilian Soil Classification System - SiBCS

NASA Astrophysics Data System (ADS)

Cunha dos Anjos, Lúcia Helena; Csekö Nolasco de Carvalho, Claudia; Homem Antunes, Mauro Antonio; Muggler, Cristine Carole

2014-05-01

In Brazil soil surveys started around 1940 and the first map with soil information of São Paulo State was published in 1943. The Committee of Soils of the National Service for Agronomic Research was created in 1947 by the Agriculture Ministry and became an historical landmark for soil survey in Brazil. In 1953, the National Program of soil survey was approved and the first soil map and report of Rio de Janeiro State was released in 1958, followed by São Paulo State in 1960. This is also the origin of Embrapa Soil Research institution. Other milestones were the soil surveys published by the Agronomic Institute of Campinas (IAC) and the natural resources studies published within the RADAMBRASIL Project, initially planned for the Amazon region and later covering the whole country. Many soil studies followed and a comprehensive knowledge of tropical soils was achieved resulting in successful technologies for agriculture production, in lands considered by many as of "low fertility and acid soils with limited or no agricultural potential". However, detailed soil surveys are still lacking; only 5% of the country soils are mapped in 1:25.000 scales, and 15-20% in 1:100.000. In the first soil survey reports of Rio de Janeiro (1958) and São Paulo (1960), soil classes were defined according to Baldwin, Kellog & Thorp (Yearbook of Agriculture for 1938), and Thorp & Smith (Soil Science, 67, 1949) publications. It was already clear that the existing classification systems were not adequate to represent the highly weathered tropical soils of the large old landscapes in the cerrado (savanna like) region, or the soils formed on recent hydromorphic conditions at the Amazon Basin and Pantanal region. A national classification system to embody the country's large territory and environmental variation from tropical to subtropical and semiarid conditions, as well as the diversity of soil forming processes in old and new landscapes had to be developed. In 1964, the first attempt of a national soil classification was presented by Marcelo Camargo (Embrapa Soils) and Jacob Bennema (FAO adviser). When Soil Taxonomy was first published in 1975, a field workshop was held in Brazil, and the system was not accepted by the country scientists; one main reason was the usage of climate as a main attribute for suborders. In 1978, the first national soil field correlation meeting was held with the goal of developing the national system, giving origin to the Brazilian Soil Classification System (SiBCS). In 1980, a working group was created by Embrapa Soils and other institutes resulting in four approximations of the system. In 1999, the first edition of the SiBCS was released, followed by a second edition in 2006 and the third in 2013. The SiBCS is a hierarchic system, based on morphogenetic soil attributes, with six categorical levels: order, suborder, great group, subgroup, family, and series. It has 13 soil orders, and it is structured as a key down to subgroup level. Many soil attributes are based on concepts adopted by the Soil Taxonomy (United States) and by the World Reference Base for Soil Resources (WRB - FAO). The development of the SiBCS is supervised by a national executive committee, and information is available at http://www.cnps.embrapa.br/sibcs (in Portuguese).

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Changes in labile soil organic matter fractions following land use change from monocropping to poplar-based agroforestry systems in a semiarid region of Northeast China.

PubMed

Mao, Rong; Zeng, De-Hui; Li, Lu-Jun; Hu, Ya-Lin

2012-11-01

Labile fractions of soil organic matter (SOM) respond rapidly to land management practices and can be used as a sensitive indicator of changes in SOM. However, there is little information about the effect of agroforestry practices on labile SOM fractions in semiarid regions of China. In order to test the effects of land use change from monocropping to agroforestry systems on labile SOM fractions, we investigated soil microbial biomass C (MBC) and N, particulate organic matter C (POMC) and N (POMN), as well as total organic C (TOC) and total N (TN) in the 0- to 15-cm and the 15- to 30-cm layers in 4-year-old poplar-based agroforestry systems and adjoining monocropping systems with two different soil textures (sandy loam and sandy clay loam) in a semiarid region of Northeast China. Our results showed that poplar-based agroforestry practices affected soil MBC, POMC, and POMN, albeit there was no significant difference in TOC and TN. Agroforestry practices increased MBC, POMC, and POMN in sandy clay loam soils. However, in sandy loam soils, agroforestry practices only increased MBC and even decreased POMC and POMN at the 0- to 15-cm layer. Our results suggest that labile SOM fractions respond sensitively to poplar-based agroforestry practices and can provide early information about the changes in SOM in semiarid regions of Northeast China and highlight that the effects of agroforestry practices on labile SOM fractions vary with soil texture.

Assimilation of SMOS (and SMAP) Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey

2016-01-01

Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.

Influences of traffic on Pb, Cu and Zn concentrations in roadside soils of an urban park in Dublin, Ireland.

PubMed

Dao, Ligang; Morrison, Liam; Zhang, Hongxuan; Zhang, Chaosheng

2014-06-01

Soils in the vicinity of roads are recipients of contaminants from traffic emissions. In order to obtain a better understanding of the impacts of traffic on soils, a total of 225 surface soil samples were collected from an urban park (Phoenix Park, Dublin, Ireland) in a grid system. Metal (Pb, Cu and Zn) concentrations were determined using a portable X-ray fluorescence analyzer. Strong spatial variations for the concentrations of Pb, Cu and Zn were observed. The spatial distribution maps created using geographical information system techniques revealed elevated metal concentrations close to the main traffic route in the park. The relationships between the accumulation of Pb, Cu and Zn in the roadside soils and the distance from the road were well fitted with an exponential model. Elevated metal concentrations from traffic pollution extended to a distance of approximately 40 m from the roadside. The results of this study provide useful information for the management of urban parks particularly in relation to policies aimed at reducing the impact of traffic related pollution on soils.

THE DIRT ON SOILS

EPA Science Inventory

This keynote presentation will provide basic information regarding the physical, chemical, and biological importance of soils to 50 second grade teachers within the Cincinnati Public School System as part of a Hamilton County Department of Environmenatl Services Sois Workshop.

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.

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.

Multifrequency passive microwave observations of soil moisture in an arid rangeland environment

NASA Technical Reports Server (NTRS)

Jackson, T. J.; Schmugge, T. J.; Parry, R.; Kustas, W. P.; Ritchie, J. C.; Shutko, A. M.; Khaldin, A.; Reutov, E.; Novichikhin, E.; Liberman, B.

1992-01-01

A cooperative experiment was conducted by teams from the U.S. and U.S.S.R. to evaluate passive microwave instruments and algorithms used to estimate surface soil moisture. Experiments were conducted as part of an interdisciplinary experiment in an arid rangeland watershed located in the southwest United States. Soviet microwave radiometers operating at wavelengths of 2.25, 21 and 27 cm were flown on a U.S. aircraft. Radio frequency interference limited usable data to the 2.25 and 21 cm systems. Data have been calibrated and compared to ground observations of soil moisture. These analyses showed that the 21 cm system could produce reliable and useful soil moisture information and that the 2.25 cm system was of no value for soil moisture estimation in this experiment.

Soil information system of Arunachal Pradesh in a GIS environment for land use planning

NASA Astrophysics Data System (ADS)

Maji, Amal K.; Nayak, Dulal C.; Krishna, Nadimpalli, , DR; Srinivas, Challa V.; Kamble, Kalpana; Reddy, Gangalakunta P. Obi; Velayutham, Mariappan

Arunachal Pradesh, the largest mountainous state of India, is situated in the northeastern part of the Himalayan region and characterized by high annual rainfall, forest vegetation and diversity in soils. Information on the soils of the state is essential for scientific land use planning and sustainable production. A soil resource inventory and subsequent database creation for thematic mapping using a Geographical Information System (GIS) is presented in this paper. Physiographically, Arunachal Pradesh can be divided into four distinct zones: snow-capped mountains (5500 m amsl); lower Himalayan ranges (3500 m amsl); the sub-Himalayan Siwalik hills (700 m amsl); and the eastern Assam plains. Soils occurring in these physiographic zones are Inceptisols (37 percent), Entisols (35 percent), Ultisols (14 percent) and Alfisols (0.5 percent). The remaining soils can be classed as miscellaneous. Soil resource inventory studies show that the soils of the warm perhumid eastern Himalayan ecosystem, with a 'thermic' temperature regime, are Inceptisols and Entisols; and that they are highly acidic in nature. Soils of the warm perhumid Siwalik hill ecosystem, with a 'hyperthermic' temperature regime, are also Entisols and Inceptisols with a high to moderate acidic condition. The dominant soils of the northeastern Purvachal hill ecosystem, with 'hyperthermic' and 'thermic' temperature regimes, are Ultisols and Inceptisols. Inceptisols and Entisols are the dominant soils in the hot and humid plain ecosystem. Steeply sloping landform and high rainfall are mainly responsible for a high erosion hazard in the state. The soil erosion map indicates that very severe (20 percent of TGA) to severe (25 percent of TGA) soil erosion takes place in the warm per-humid zone, whereas, moderate erosion takes place in the Siwalik hills and hot, humid plain areas. This is evident from the soil depth class distribution of Arunachal Pradesh, which shows that shallow soils cover 20 percent of the TGA of the state. Most of the state is covered by hills and agricultural practices are limited to valley regions. However, the soils of other physiographic zones (lower altitudinal, moderately hilly terrain) provide scope for plantations, such as orange, banana and tea plantations.

Analyzing and Visualizing Precipitation and Soil Moisture in ArcGIS

NASA Technical Reports Server (NTRS)

Yang, Wenli; Pham, Long; Zhao, Peisheng; Kempler, Steve; Wei, Jennifer

2016-01-01

Precipitation and soil moisture are among the most important parameters in many land GIS (Geographic Information System) research and applications. These data are available globally from NASA GES DISC (Goddard Earth Science Data and Information Services Center) in GIS-ready format at 10-kilometer spatial resolution and 24-hour or less temporal resolutions. In this presentation, well demonstrate how rainfall and soil moisture data are used in ArcGIS to analyze and visualize spatiotemporal patterns of droughts and their impacts on natural vegetation and agriculture in different parts of the world.

Land management effects on near-surface soil properties of southern U.S. coastal plain kandiudults.

Treesearch

M. Levi; J. Shaw; C. Wood; S. Herman; E. Carter; Y. Feng

2010-01-01

A comparative assessment of land management systems and relatively undisturbed ecosystems is useful for evaluating anthropogenic impacts on soil properties (Larson and Pierce, 1994). Such information is useful for the restoration and evaluation of C sequestration potential. Comparison of disturbed with natural ecosystems allows the measurement of soil properties...

Linking aboveground net primary productivity to soil carbon and dissolved organic carbon in complex terrain

Treesearch

F.S. Peterson; K. Lajtha

2013-01-01

Factors influencing soil organic matter (SOM) stabilization and dissolved organic carbon (DOC) content in complex terrain, where vegetation, climate, and topography vary over the scale of a few meters, are not well understood. We examined the spatial correlations of lidar and geographic information system-derived landscape topography, empirically measured soil...

Soil factors involved in the diversity and structure of soil bacterial communities in commercial organic olive orchards in Southern Spain.

PubMed

Landa, B B; Montes-Borrego, M; Aranda, S; Soriano, M A; Gómez, J A; Navas-Cortés, J A

2014-04-01

Nowadays, there is a tendency in olive production systems to reduce tillage or keep a vegetative cover to reduce soil erosion and degradation. However, there is scarce information on the effects of different soil management systems (SMS) in soil bacterial community composition of olive groves. In this study, we have evaluated the effects of soil type and different SMS implemented to control weeds in the structure and diversity of bacterial communities of 58 soils in the two geographic areas that best represent the organic olive production systems in Spain. Bacterial community composition assessed by frequency and intensity of occurrence of terminal restriction profiles (TRFs) derived from terminal restriction fragment length polymorphism (T-RFLP) analysis of amplified 16S ribosomal deoxyribonucleic acid were strongly correlated with soil type/field site (Eutric/Calcaric) that differed mainly in soil particle size distribution and soil pH, followed by a strong effect of SMS, in that order. Canonical discriminant (CD) analysis of TRFs properly classified all of the olive orchard soils as belonging to their respective soil type or SMS. Furthermore, only a small set of TRFs were enough to clearly and significantly differentiate soil samples according to soil type or SMS. Those specific TRFs could be used as bioindicators to assess the effect of changes in SMS aimed to enhance soil quality in olive production systems. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial prediction of these attributes also showed a high performance (validations with R2> 0.78). These models allowed to increase spatial resolution of soil weathering information. On the other hand, the comparison between the analog and digital soil maps showed a global accuracy of 69% for the ASC-N map and 62% in the ASC-H map, with kappa indices of 0.52 and 0.45 respectively.

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

USGS Publications Warehouse

Norman, Laura

2004-01-01

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

[Development of an analyzing system for soil parameters based on NIR spectroscopy].

PubMed

Zheng, Li-Hua; Li, Min-Zan; Sun, Hong

2009-10-01

A rapid estimation system for soil parameters based on spectral analysis was developed by using object-oriented (OO) technology. A class of SOIL was designed. The instance of the SOIL class is the object of the soil samples with the particular type, specific physical properties and spectral characteristics. Through extracting the effective information from the modeling spectral data of soil object, a map model was established between the soil parameters and its spectral data, while it was possible to save the mapping model parameters in the database of the model. When forecasting the content of any soil parameter, the corresponding prediction model of this parameter can be selected with the same soil type and the similar soil physical properties of objects. And after the object of target soil samples was carried into the prediction model and processed by the system, the accurate forecasting content of the target soil samples could be obtained. The system includes modules such as file operations, spectra pretreatment, sample analysis, calibrating and validating, and samples content forecasting. The system was designed to run out of equipment. The parameters and spectral data files (*.xls) of the known soil samples can be input into the system. Due to various data pretreatment being selected according to the concrete conditions, the results of predicting content will appear in the terminal and the forecasting model can be stored in the model database. The system reads the predicting models and their parameters are saved in the model database from the module interface, and then the data of the tested samples are transferred into the selected model. Finally the content of soil parameters can be predicted by the developed system. The system was programmed with Visual C++6.0 and Matlab 7.0. And the Access XP was used to create and manage the model database.

A framework of connections between soil and people can help improve sustainability of the food system and soil functions.

PubMed

Ball, Bruce C; Hargreaves, Paul R; Watson, Christine A

2018-04-01

Globally soil quality and food security continue to decrease indicating that agriculture and the food system need to adapt. Improving connection to the soil by knowledge exchange can help achieve this. We propose a framework of three types of connections that allow the targeting of appropriate messages to different groups of people. Direct connection by, for example, handling soil develops soil awareness for management that can be fostered by farmers joining groups on soil-focused farming such as organic farming or no-till. Indirect connections between soil, food and ecosystem services can inform food choices and environmental awareness in the public and can be promoted by, for example, gardening, education and art. Temporal connection revealed from past usage of soil helps to bring awareness to policy workers of the need for the long-term preservation of soil quality for environmental conservation. The understanding of indirect and temporal connections can be helped by comparing them with the operations of the networks of soil organisms and porosity that sustain soil fertility and soil functions.

Rapid prototyping of soil moisture estimates using the NASA Land Information System

NASA Astrophysics Data System (ADS)

Anantharaj, V.; Mostovoy, G.; Li, B.; Peters-Lidard, C.; Houser, P.; Moorhead, R.; Kumar, S.

2007-12-01

The Land Information System (LIS), developed at the NASA Goddard Space Flight Center, is a functional Land Data Assimilation System (LDAS) that incorporates a suite of land models in an interoperable computational framework. LIS has been integrated into a computational Rapid Prototyping Capabilities (RPC) infrastructure. LIS consists of a core, a number of community land models, data servers, and visualization systems - integrated in a high-performance computing environment. The land surface models (LSM) in LIS incorporate surface and atmospheric parameters of temperature, snow/water, vegetation, albedo, soil conditions, topography, and radiation. Many of these parameters are available from in-situ observations, numerical model analysis, and from NASA, NOAA, and other remote sensing satellite platforms at various spatial and temporal resolutions. The computational resources, available to LIS via the RPC infrastructure, support e- Science experiments involving the global modeling of land-atmosphere studies at 1km spatial resolutions as well as regional studies at finer resolutions. The Noah Land Surface Model, available with-in the LIS is being used to rapidly prototype soil moisture estimates in order to evaluate the viability of other science applications for decision making purposes. For example, LIS has been used to further extend the utility of the USDA Soil Climate Analysis Network of in-situ soil moisture observations. In addition, LIS also supports data assimilation capabilities that are used to assimilate remotely sensed soil moisture retrievals from the AMSR-E instrument onboard the Aqua satellite. The rapid prototyping of soil moisture estimates using LIS and their applications will be illustrated during the presentation.

Mapping patterns of soil properties and soil moisture using electromagnetic induction to investigate the impact of land use changes on soil processes

NASA Astrophysics Data System (ADS)

Robinet, Jérémy; von Hebel, Christian; van der Kruk, Jan; Govers, Gerard; Vanderborght, Jan

2016-04-01

As highlighted by many authors, classical or geophysical techniques for measuring soil moisture such as destructive soil sampling, neutron probes or Time Domain Reflectometry (TDR) have some major drawbacks. Among other things, they provide point scale information, are often intrusive and time-consuming. ElectroMagnetic Induction (EMI) instruments are often cited as a promising alternative hydrogeophysical methods providing more efficiently soil moisture measurements ranging from hillslope to catchment scale. The overall objective of our research project is to investigate whether a combination of geophysical techniques at various scales can be used to study the impact of land use change on temporal and spatial variations of soil moisture and soil properties. In our work, apparent electrical conductivity (ECa) patterns are obtained with an EM multiconfiguration system. Depth profiles of ECa were subsequently inferred through a calibration-inversion procedure based on TDR data. The obtained spatial patterns of these profiles were linked to soil profile and soil water content distributions. Two catchments with contrasting land use (agriculture vs. natural forest) were selected in a subtropical region in the south of Brazil. On selected slopes within the catchments, combined EMI and TDR measurements were carried out simultaneously, under different atmospheric and soil moisture conditions. Ground-truth data for soil properties were obtained through soil sampling and auger profiles. The comparison of these data provided information about the potential of the EMI technique to deliver qualitative and quantitative information about the variability of soil moisture and soil properties.

Drought monitoring with soil moisture active passive (SMAP) measurements

NASA Astrophysics Data System (ADS)

Mishra, Ashok; Vu, Tue; Veettil, Anoop Valiya; Entekhabi, Dara

2017-09-01

Recent launch of space-borne systems to estimate surface soil moisture may expand the capability to map soil moisture deficit and drought with global coverage. In this study, we use Soil Moisture Active Passive (SMAP) soil moisture geophysical retrieval products from passive L-band radiometer to evaluate its applicability to forming agricultural drought indices. Agricultural drought is quantified using the Soil Water Deficit Index (SWDI) based on SMAP and soil properties (field capacity and available water content) information. The soil properties are computed using pedo-transfer function with soil characteristics derived from Harmonized World Soil Database. The SMAP soil moisture product needs to be rescaled to be compatible with the soil parameters derived from the in situ stations. In most locations, the rescaled SMAP information captured the dynamics of in situ soil moisture well and shows the expected lag between accumulations of precipitation and delayed increased in surface soil moisture. However, the SMAP soil moisture itself does not reveal the drought information. Therefore, the SMAP based SWDI (SMAP_SWDI) was computed to improve agriculture drought monitoring by using the latest soil moisture retrieval satellite technology. The formulation of SWDI does not depend on longer data and it will overcome the limited (short) length of SMAP data for agricultural drought studies. The SMAP_SWDI is further compared with in situ Atmospheric Water Deficit (AWD) Index. The comparison shows close agreement between SMAP_SWDI and AWD in drought monitoring over Contiguous United States (CONUS), especially in terms of drought characteristics. The SMAP_SWDI was used to construct drought maps for CONUS and compared with well-known drought indices, such as, AWD, Palmer Z-Index, sc-PDSI and SPEI. Overall the SMAP_SWDI is an effective agricultural drought indicator and it provides continuity and introduces new spatial mapping capability for drought monitoring. As an agricultural drought index, SMAP_SWDI has potential to capture short term moisture information similar to AWD and related drought indices.

Environmental sciences information storage and retrieval system

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

Engstrom, D.E.; White, M.G.; Dunaway, P.B.

Reynolds Electrical and Engineering Co., Inc. (REECo), has since 1970 accumulated information relating to the AEC's Nevada Applied Ecology Group (NAEG) programs at the Nevada Test Site (NTS). These programs, involving extensive soil, vegetation, and small-animal studies, have generated informational data concerning the collecting, processing, analyzing, and shipping of sample materials to various program participants and contractors. Future plans include incorporation of Lawrence Livermore Laboratory's resuspension study data, REECo's on-site air data, and EPA's large-animal, off-site air, and off-site soil data. (auth)

The Effect of Land Use on Soil Erosion in the Guadiana Watershed in Puerto Rico

Treesearch

TANIA DEL MAR LÓPEZ; T. MITCHELL AIDE; SCATENA F. N.

1998-01-01

The Revised Universal Soil Loss Equation (RUSLE) was used in conjunction with a Geographic Information System to determine the influence of land use and other environmental factors on soil erosion in the Guadiana watershed in Puerto Rico. Mean annual erosion, suspended sediment discharge, and the rainfall-erosion factor of the RUSLE increased with annual rainfall....

Land Data Assimilation of Satellite-Based Soil Moisture Products Using the Land Information System Over the NLDAS Domain

NASA Technical Reports Server (NTRS)

Mocko, David M.; Kumar, S. V.; Peters-Lidard, C. D.; Tian, Y.

2011-01-01

This presentation will include results from data assimilation simulations using the NASA-developed Land Information System (LIS). Using the ensemble Kalman filter in LIS, two satellite-based soil moisture products from the AMSR-E instrument were assimilated, one a NASA-based product and the other from the Land Parameter Retrieval Model (LPRM). The domain and land-surface forcing data from these simulations were from the North American Land Data Assimilation System Phase-2, over the period 2002-2008. The Noah land-surface model, version 3.2, was used during the simulations. Changes to estimates of land surface states, such as soil moisture, as well as changes to simulated runoff/streamflow will be presented. Comparisons over the NLDAS domain will also be made to two global reference evapotranspiration (ET) products, one an interpolated product based on FLUXNET tower data and the other a satellite- based algorithm from the MODIS instrument. Results of an improvement metric show that assimilating the LPRM product improved simulated ET estimates while the NASA-based soil moisture product did not.

Correlation of spacecraft passive microwave system data with soil moisture indices (API). [great plains corridor

NASA Technical Reports Server (NTRS)

Blanchard, B. J.; Mcfarland, M. J.; Theis, S.; Richter, J. G.

1981-01-01

Electrical scanning microwave radiometer brightness temperature, meteorological data, climatological data, and winter wheat crop information were used to estimate that soil moisture content in the Great Plains region. Results over the predominant winter wheat areas indicate that the best potential to infer soil moisture occurs during fall and spring. These periods encompass the growth stages when soil moisture is most important to winter wheat yield. Other significant results are reported.

Quantitative modeling of soil genesis processes

NASA Technical Reports Server (NTRS)

Levine, E. R.; Knox, R. G.; Kerber, A. G.

1992-01-01

For fine spatial scale simulation, a model is being developed to predict changes in properties over short-, meso-, and long-term time scales within horizons of a given soil profile. Processes that control these changes can be grouped into five major process clusters: (1) abiotic chemical reactions; (2) activities of organisms; (3) energy balance and water phase transitions; (4) hydrologic flows; and (5) particle redistribution. Landscape modeling of soil development is possible using digitized soil maps associated with quantitative soil attribute data in a geographic information system (GIS) framework to which simulation models are applied.

Importance of Vertical Coupling in Agricultural Models on Assimilation of Satellite-derived Soil Moisture

NASA Astrophysics Data System (ADS)

Mladenova, I. E.; Crow, W. T.; Teng, W. L.; Doraiswamy, P.

2010-12-01

Crop yield in crop production models is simulated as a function of weather, ground conditions and management practices and it is driven by the amount of nutrients, heat and water availability in the root-zone. It has been demonstrated that assimilation of satellite-derived soil moisture data has the potential to improve the model root-zone soil water (RZSW) information. However, the satellite estimates represent the moisture conditions of the top 3 cm to 5 cm of the soil profile depending on system configuration and surface conditions (i.e. soil wetness, density of the canopy cover, etc). The propagation of this superficial information throughout the profile will depend on the model physics. In an Ensemble Kalman Filter (EnKF) data assimilation system, as the one examined here, the update of each soil layer is done through the Kalman Gain, K. K is a weighing factor that determines how much correction will be performed on the forecasts. Furthermore, K depends on the strength of the correlation between the surface and the root-zone soil moisture; the stronger this correlation is, the more observations will impact the analysis. This means that even if the satellite-derived product has higher sensitivity and accuracy as compared to the model estimates, the improvement of the RZSW will be negligible if the surface-root zone coupling is weak, where the later is determined by the model subsurface physics. This research examines: (1) the strength of the vertical coupling in the Environmental Policy Integrated Climate (EPIC) model over corn and soybeans covered fields in Iowa, US, (2) the potential to improve EPIC RZSW information through assimilation of satellite soil moisture data derived from the Advanced Microwave Scanning Radiometer (AMSR-E) and (3) the impact of the vertical coupling on the EnKF performance.

Estimates of Soil Moisture Using the Land Information System for Land Surface Water Storage: Case Study for the Western States Water Mission

NASA Astrophysics Data System (ADS)

Liu, P. W.; Famiglietti, J. S.; Levoe, S.; Reager, J. T., II; David, C. H.; Kumar, S.; Li, B.; Peters-Lidard, C. D.

2017-12-01

Soil moisture is one of the critical factors in terrestrial hydrology. Accurate soil moisture information improves estimation of terrestrial water storage and fluxes, that is essential for water resource management including sustainable groundwater pumping and agricultural irrigation practices. It is particularly important during dry periods when water stress is high. The Western States Water Mission (WSWM), a multiyear mission project of NASA's Jet Propulsion Laboratory, is operated to understand and estimate quantities of the water availability in the western United States by integrating observations and measurements from in-situ and remote sensing sensors, and hydrological models. WSWM data products have been used to assess and explore the adverse impacts of the California drought (2011-2016) and provide decision-makers information for water use planning. Although the observations are often more accurate, simulations using land surface models can provide water availability estimates at desired spatio-temporal scales. The Land Information System (LIS), developed by NASA's Goddard Space Flight Center, integrates developed land surface models and data processing and management tools, that enables to utilize the measurements and observations from various platforms as forcings in the high performance computing environment to forecast the hydrologic conditions. The goal of this study is to implement the LIS in the western United States for estimates of soil moisture. We will implement the NOAH-MP model at the 12km North America Land Data Assimilation System grid and compare to other land surface models included in the LIS. Findings will provide insight into the differences between model estimates and model physics. Outputs from a multi-model ensemble from LIS can also be used to enhance estimated reliability and provide quantification of uncertainty. We will compare the LIS-based soil moisture estimates to the SMAP enhanced 9 km soil moisture product to understand the mechanistic differences between the model and observation. These outcomes will contribute to the WSWM for providing robust products.

Evaluating the new soil erosion map of Hungary

NASA Astrophysics Data System (ADS)

Waltner, István; Centeri, Csaba; Takács, Katalin; Pirkó, Béla; Koós, Sándor; László, Péter; Pásztor, László

2017-04-01

With growing concerns on the effects of climate change and land use practices on our soil resources, soil erosion by water is becoming a significant issue internationally. Since the 1964 publication of the first soil erosion map of Hungary, there have been several attempts to provide a countrywide assessment of erosion susceptibility. However, there has been no up-to-date map produced in the last decade. In 2016, a new, 1:100 000 scale soil erosion map was published, based on available soil, elevation, land use and meteorological data for the extremely wet year of 2010. The map utilized combined outputs for two spatially explicit methods: the widely used empirical Universal Soil Loss Equation (USLE) and the process-based Pan-European Soil Erosion Risk Assessment (PESERA) models. The present study aims to provide a detailed analysis of the model results. In lieu of available national monitoring data, information from other sources were used. The Soil Degradation Subsystem (TDR) of the National Environmental Information System (OKIR) is a digital database based on a soil survey and farm dairy data collected from representative farms in Hungary. During the survey all kind of degradation forms - including soil erosion - were considered. Agricultural and demographic data was obtained from the Hungarian Central Statistical Office (KSH). Data from an interview-based survey was also used in an attempt to assess public awareness of soil erosion risks. Point-based evaluation of the model results was complemented with cross-regional assessment of soil erosion estimates. This, combined with available demographic information provides us with an opportunity to address soil erosion on a community level, with the identification of regions with the highest risk of being affected by soil erosion.

Comparing the performance of various digital soil mapping approaches to map physical soil properties

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Takács, Katalin; Pásztor, László

2015-04-01

Spatial information on physical soil properties is intensely expected, in order to support environmental related and land use management decisions. One of the most widely used properties to characterize soils physically is particle size distribution (PSD), which determines soil water management and cultivability. According to their size, different particles can be categorized as clay, silt, or sand. The size intervals are defined by national or international textural classification systems. The relative percentage of sand, silt, and clay in the soil constitutes textural classes, which are also specified miscellaneously in various national and/or specialty systems. The most commonly used is the classification system of the United States Department of Agriculture (USDA). Soil texture information is essential input data in meteorological, hydrological and agricultural prediction modelling. Although Hungary has a great deal of legacy soil maps and other relevant soil information, it often occurs, that maps do not exist on a certain characteristic with the required thematic and/or spatial representation. The recent developments in digital soil mapping (DSM), however, provide wide opportunities for the elaboration of object specific soil maps (OSSM) with predefined parameters (resolution, accuracy, reliability etc.). Due to the simultaneous richness of available Hungarian legacy soil data, spatial inference methods and auxiliary environmental information, there is a high versatility of possible approaches for the compilation of a given soil map. This suggests the opportunity of optimization. For the creation of an OSSM one might intend to identify the optimum set of soil data, method and auxiliary co-variables optimized for the resources (data costs, computation requirements etc.). We started comprehensive analysis of the effects of the various DSM components on the accuracy of the output maps on pilot areas. The aim of this study is to compare and evaluate different digital soil mapping methods and sets of ancillary variables for producing the most accurate spatial prediction of texture classes in a given area of interest. Both legacy and recently collected data on PSD were used as reference information. The predictor variable data set consisted of digital elevation model and its derivatives, lithology, land use maps as well as various bands and indices of satellite images. Two conceptionally different approaches can be applied in the mapping process. Textural classification can be realized after particle size data were spatially extended by proper geostatistical method. Alternatively, the textural classification is carried out first, followed by the spatial extension through suitable data mining method. According to the first approach, maps of sand, silt and clay percentage have been computed through regression kriging (RK). Since the three maps are compositional (their sum must be 100%), we applied Additive Log-Ratio (alr) transformation, instead of kriging them independently. Finally, the texture class map has been compiled according to the USDA categories from the three maps. Different combinations of reference and training soil data and auxiliary covariables resulted several different maps. On the basis of the other way, the PSD were classified firstly into the USDA categories, then the texture class maps were compiled directly by data mining methods (classification trees and random forests). The various results were compared to each other as well as to the RK maps. The performance of the different methods and data sets has been examined by testing the accuracy of the geostatistically computed and the directly classified results to assess the most predictive and accurate method. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Soils and public health: the vital nexus

NASA Astrophysics Data System (ADS)

Pachepsky, Yakov

2015-04-01

Soils sustain life. They affect human health via quantity, quality, and safety of available food and water, and via direct exposure of individuals to soils. Throughout the history of civilization, soil-health relationships have inspired spiritual movements, philosophical systems, cultural exchanges, and interdisciplinary interactions, and provided medicinal substances of paramount impact. Given the climate, resource, and population pressures, understanding and managing the soil-health interactions becomes a modern imperative. We are witnessing a paradigm shift from recognizing and yet disregarding the 'soil-health' nexus complexity to parameterizing this complexity and identifying reliable controls. This becomes possible with the advent of modern research tools as a source of 'big data' on multivariate nonlinear soil systems and the multiplicity of health metrics. The phenomenon of suppression of human pathogens in soils and plants presents a recent example of these developments. Evidence is growing about the dependence of pathogen suppression on the soil microbial community structure which, in turn, is affected by the soil-plant system management. Soil eutrophication appears to create favorable conditions for pathogen survival. Another example of promising information-rich research considers links and feedbacks between the soil microbial community structure and structure of soil physical pore space. The two structures are intertwined and involved in the intricate self-organization that controls soil services to public health. This, in particular, affects functioning of soils as a powerful water filter and the capacity of this filter with respect to emerging contaminants in both 'green' and 'blue' waters. To evaluate effects of soil services to public health, upscaling procedures are needed for relating the fine-scale mechanistic knowledge to available coarse-scale information on soil properties and management. More needs to be learned about health effects of soils in organic agriculture that are often used for soil quality comparison and benchmarking. The influence of soil degradation and rehabilitation on public health has to be assessed in quantitative terms. Some links between soils and public health regarding, for example, immune maturation, antibiotic resistance development, and mental well-being, have been long hypothesized but remain to be examined. The data on soil-health relationships are scarce and very much disjointed, and a concerted international effort appears to be needed to encompass various economic and geographical settings. Current definitions of healthy soil broadly include aspects that are conducive for human health, and functional evaluation of soil quality with a focus on public health will have useful applications in public policies and perception. The 'soil-health' connection is complex in character, global in manifestation, and applicable to every human being.

An inversion method for retrieving soil moisture information from satellite altimetry observations

NASA Astrophysics Data System (ADS)

Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne

2016-04-01

Soil moisture represents an important component of the terrestrial water cycle that controls., evapotranspiration and vegetation growth. Consequently, knowledge on soil moisture variability is essential to understand the interactions between land and atmosphere. Yet, terrestrial measurements are sparse and their information content is limited due to the large spatial variability of soil moisture. Therefore, over the last two decades, several active and passive radar and satellite missions such as ERS/SCAT, AMSR, SMOS or SMAP have been providing backscatter information that can be used to estimate surface conditions including soil moisture which is proportional to the dielectric constant of the upper (few cm) soil layers . Another source of soil moisture information are satellite radar altimeters, originally designed to measure sea surface height over the oceans. Measurements of Jason-1/2 (Ku- and C-Band) or Envisat (Ku- and S-Band) nadir radar backscatter provide high-resolution along-track information (~ 300m along-track resolution) on backscatter every ~10 days (Jason-1/2) or ~35 days (Envisat). Recent studies found good correlation between backscatter and soil moisture in upper layers, especially in arid and semi-arid regions, indicating the potential of satellite altimetry both to reconstruct and to monitor soil moisture variability. However, measuring soil moisture using altimetry has some drawbacks that include: (1) the noisy behavior of the altimetry-derived backscatter (due to e.g., existence of surface water in the radar foot-print), (2) the strong assumptions for converting altimetry backscatters to the soil moisture storage changes, and (3) the need for interpolating between the tracks. In this study, we suggest a new inversion framework that allows to retrieve soil moisture information from along-track Jason-2 and Envisat satellite altimetry data, and we test this scheme over the Australian arid and semi-arid regions. Our method consists of: (i) deriving time-invariant spatial patterns (base-functions) by applying principal component analysis (PCA) to simulated soil moisture from a large-scale land surface model. (ii) Estimating time-variable soil moisture evolution by fitting these base functions of (i) to the along-track retracked backscatter coefficients in a least squares sense. (iii) Combining the estimated time-variable amplitudes and the pre-computed base-functions, which results in reconstructed (spatio-temporal) soil moisture information. We will show preliminary results that are compared to available high-resolution soil moisture model data over the region (the Australian Water Resource Assessment, AWRA model). We discuss the possibility of using altimetry-derived soil moisture estimations to improve the simulation skill of soil moisture in the Global Land Data Assimilation System (GLDAS) over Australia.

What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system

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

Yang, Xiaofan; Varga, Tamas; Liu, Chongxuan

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere. X-ray Computed Tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and in-house developed code was used to non-invasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure, and extract quantitative information from the 3D data, respectively. Based on the explicitly-resolved root structure, pore-scale computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soilmore » hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. Furthermore, the coupled imaging-modeling approach demonstrates a realistic platform to investigate rhizosphere flow processes and would be feasible to provide useful information linked to upscaled models.« less

What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system

DOE PAGES

Yang, Xiaofan; Varga, Tamas; Liu, Chongxuan; ...

2017-05-04

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere. X-ray Computed Tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and in-house developed code was used to non-invasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure, and extract quantitative information from the 3D data, respectively. Based on the explicitly-resolved root structure, pore-scale computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soilmore » hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. Furthermore, the coupled imaging-modeling approach demonstrates a realistic platform to investigate rhizosphere flow processes and would be feasible to provide useful information linked to upscaled models.« less

Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Brad

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain

NASA Astrophysics Data System (ADS)

Gruber, A.; Crow, W. T.; Dorigo, W. A.

2018-02-01

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.

High-Resolution Time-Lapse Monitoring of Unsaturated Flow using Automated GPR Data Collection

NASA Astrophysics Data System (ADS)

Mangel, A. R.; Moysey, S. M.; Lytle, B. A.; Bradford, J. H.

2015-12-01

High-resolution ground-penetrating radar (GPR) data provide the detailed information required to image subsurface structures. Recent advances in GPR monitoring now also make it possible to study transient hydrologic processes, but high-speed data acquisition is critical for this application. We therefore highlight the capabilities of our automated system to acquire time-lapse, high-resolution multifold GPR data during infiltration of water into soils. The system design allows for fast acquisition of constant-offset (COP) and common-midpoint profiles (CMP) to monitor unsaturated flow at multiple locations. Qualitative interpretation of the unprocessed COPs can provide substantial information regarding the hydrologic response of the system, such as the complexities of patterns associated with the wetting of the soil and geophysical evidence of non-uniform propagation of a wetting front. While we find that unprocessed images are informative, we show that the spatial variability of velocity introduced by infiltration events can complicate the images and that migration of the data is an effective tool to improve interpretability of the time-lapse images. The ability of the system to collect high density CMP data also introduces the potential for improving the velocity model along with the image via reflection tomography in the post-migrated domain. We show that for both simulated and empirical time-lapse GPR profiles we can resolve a propagating wetting front in the soil that is in good agreement with the response of in-situ soil moisture measurements. The data from these experiments illustrate the importance of high-speed, high-resolution GPR data acquisition for obtaining insight about the dynamics of hydrologic events. Continuing research is aimed at improving the quantitative analysis of surface-based GPR monitoring data for identifying preferential flow in soils.

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.

Introduction of digital soil mapping techniques for the nationwide regionalization of soil condition in Hungary; the first results of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Takács, Katalin; Bakacsi, Zsófia; Szabó, József; Dobos, Endre

2014-05-01

Due to the former soil surveys and mapping activities significant amount of soil information has accumulated in Hungary. Present soil data requirements are mainly fulfilled with these available datasets either by their direct usage or after certain specific and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable imperfection as for the accuracy and reliability of the delivered products. With a recently started project (DOSoReMI.hu; Digital, Optimized, Soil Related Maps and Information in Hungary) we would like to significantly extend the potential, how countrywide soil information requirements could be satisfied in Hungary. We started to compile digital soil related maps which fulfil optimally the national and international demands from points of view of thematic, spatial and temporal accuracy. The spatial resolution of the targeted countrywide, digital, thematic maps is at least 1:50.000 (approx. 50-100 meter raster resolution). DOSoReMI.hu results are also planned to contribute to the European part of GSM.net products. In addition to the auxiliary, spatial data themes related to soil forming factors and/or to indicative environmental elements we heavily lean on the various national soil databases. The set of the applied digital soil mapping techniques is gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. In our paper we will present the first results. - Regression kriging (RK) has been used for the spatial inference of certain quantitative data, like particle size distribution components, rootable depth and organic matter content. In the course of RK-based mapping spatially segmented categorical information provided by the SMUs of Digital Kreybig Soil Information System (DKSIS) has been also used in the form of indicator variables. - Classification and regression trees (CART) were used to improve the spatial resolution of category-type soil maps (thematic downscaling), like genetic soil type and soil productivity maps. The approach was justified by the fact that certain thematic soil maps are not available in the required scale. Decision trees were applied for the understanding of the soil-landscape models involved in existing soil maps, and for the post-formalization of survey/compilation rules. The relationships identified and expressed in decision rules made the creation of spatially refined maps possible with the aid of high resolution environmental auxiliary variables. Among these co-variables, a special role was played by larger scale spatial soil information with diverse attributes. As a next step, the testing of random forests for the same purposes has been started. - Due to the simultaneous richness of available Hungarian legacy soil data, spatial inference methods and auxiliary environmental information, there is a high versatility of possible approaches for the compilation of a given soil (related) map. This suggests the opportunity of optimization. For the creation of an object specific soil (related) map with predefined parameters (resolution, accuracy, reliability etc.) one might intend to identify the optimum set of soil data, method and auxiliary co-variables optimized for the resources (data costs, computation requirements etc.). The first findings on the inclusion and joint usage of spatial soil data as well as on the consistency of various evaluations of the result maps will be also presented. Acknowledgement: Our work has been supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Using Large-Scale Precipitation to Validate AMSR-E Satellite Soil Moisture Estimates by Means of Mutual Information

NASA Astrophysics Data System (ADS)

Tuttle, S. E.; Salvucci, G.

2013-12-01

Validation of remotely sensed soil moisture is complicated by the difference in scale between remote sensing footprints and traditional ground-based soil moisture measurements. To address this issue, a new method was developed to evaluate the useful information content of remotely sensed soil moisture data using only large-scale precipitation (i.e. without modeling). Under statistically stationary conditions [Salvucci, 2001], precipitation conditionally averaged according to soil moisture (denoted E[P|S]) results in a sigmoidal shape in a manner that reflects the dependence of drainage, runoff, and evapotranspiration on soil moisture. However, errors in satellite measurement and algorithmic conversion of satellite data to soil moisture can degrade this relationship. Thus, remotely sensed soil moisture products can be assessed by the degree to which the natural sigmoidal relationship is preserved. The metric of mutual information was used as an error-dependent measure of the strength of the sigmoidal relationship, calculated from a two-dimensional histogram of soil moisture versus precipitation estimated using Gaussian mixture models. Three AMSR-E algorithms (VUA-NASA [Owe et al., 2001], NASA [Njoku et al., 2003], and U. Montana [Jones & Kimball, 2010]) were evaluated with the method for a nine-year period (2002-2011) over the contiguous United States at ¼° latitude-longitude resolution, using precipitation from the North American Land Data Assimilation System (NLDAS). The U. Montana product resulted in the highest mutual information for 57% of the region, followed by VUA-NASA and NASA at 40% and 3%, respectively. Areas where the U. Montana product yielded the maximum mutual information generally coincided with low vegetation biomass and flatter terrain, while the VUA-NASA product contained more useful information in more rugged and highly vegetated areas. Additionally, E[P|S] curves resulting from the Gaussian mixture method can potentially be decomposed into their conditional evapotranspiration and drainage plus runoff components using matrix factorization methods, allowing for time-averaged mapping of these fluxes over the study area.

Information Requirements for Integrating Spatially Discrete, Feature-Based Earth Observations

NASA Astrophysics Data System (ADS)

Horsburgh, J. S.; Aufdenkampe, A. K.; Lehnert, K. A.; Mayorga, E.; Hsu, L.; Song, L.; Zaslavsky, I.; Valentine, D. L.

2014-12-01

Several cyberinfrastructures have emerged for sharing observational data collected at densely sampled and/or highly instrumented field sites. These include the CUAHSI Hydrologic Information System (HIS), the Critical Zone Observatory Integrated Data Management System (CZOData), the Integrated Earth Data Applications (IEDA) and EarthChem system, and the Integrated Ocean Observing System (IOOS). These systems rely on standard data encodings and, in some cases, standard semantics for classes of geoscience data. Their focus is on sharing data on the Internet via web services in domain specific encodings or markup languages. While they have made progress in making data available, it still takes investigators significant effort to discover and access datasets from multiple repositories because of inconsistencies in the way domain systems describe, encode, and share data. Yet, there are many scenarios that require efficient integration of these data types across different domains. For example, understanding a soil profile's geochemical response to extreme weather events requires integration of hydrologic and atmospheric time series with geochemical data from soil samples collected over various depth intervals from soil cores or pits at different positions on a landscape. Integrated access to and analysis of data for such studies are hindered because common characteristics of data, including time, location, provenance, methods, and units are described differently within different systems. Integration requires syntactic and semantic translations that can be manual, error-prone, and lossy. We report information requirements identified as part of our work to define an information model for a broad class of earth science data - i.e., spatially-discrete, feature-based earth observations resulting from in-situ sensors and environmental samples. We sought to answer the question: "What information must accompany observational data for them to be archivable and discoverable within a publication system as well as interpretable once retrieved from such a system for analysis and (re)use?" We also describe development of multiple functional schemas (i.e., physical implementations for data storage, transfer, and archival) for the information model that capture the requirements reported here.

Development and Validation of EPH Material Model for Engineered Roadway Soil

DTIC Science & Technology

2014-08-01

MODEL FOR ENGINEERED ROADWAY SOIL Ching Hsieh, PhD Altair Engineering Troy, MI Jianping Sheng, Ph.D. Jai Ramalingam System Engineering...0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing...of information if it does not display a currently valid OMB control number. 1 . REPORT DATE 11 AUG 2014 2. REPORT TYPE Journal Article 3. DATES

Management of water repellency in Australia, and risks associated with preferential flow, pesticide concentration and leaching

NASA Astrophysics Data System (ADS)

Blackwell, P. S.

2000-05-01

The three most westerly states of southern Australia have the largest area of water repellent soils, which limit agricultural production, of any country in the world. Simplified principles of the problems caused by repellency and the principles of soil management solutions are considered and related to experimental evidence. The phenomena of diverted soil water flow and isolated dry soil can explain most of the problems caused by repellency. Plant adaptation, soil or hydrophobic removal, reduced soil drying, reduced surface tension, water harvesting, avoidance, masking and, perhaps, water movement along dead root systems are the main soil management principles. Dead roots may play a role in zero till cropping systems, allowing more uniform wetting of dry hydrophobic soil at the base of a dead plant and along the dendritic pattern of the dead root system. Application of these management principles, especially water harvesting, avoidance and masking (by the use of deep trenching, furrow sowing methods or claying), have made a considerable improvement to sustainability and productivity of farming systems on the water repellent soils of Australia. Evidence is selected to assess risks of preferential flow, pesticide concentration and leaching for different agricultural soil management methods. All management methods can have some risks, but claying seems to have the least risk and furrowing the highest risk of encouraging preferential flow, pesticide concentration and leaching. It is suggested we have insufficient information and understanding to quantify the risks of groundwater contamination for different environments, farming systems and soil management methods to control repellency. There is an urgent need to develop quantified guidelines to minimise any possible groundwater contamination hazard for the extensive areas using farming systems with furrows and increasing amounts of pesticide and fertiliser.

Soil warming response: field experiments to Earth system models

NASA Astrophysics Data System (ADS)

Todd-Brown, K. E.; Bradford, M.; Wieder, W. R.; Crowther, T. W.

2017-12-01

The soil carbon response to climate change is extremely uncertain at the global scale, in part because of the uncertainty in the magnitude of the temperature response. To address this uncertainty we collected data from 48 soil warming manipulations studies and examined the temperature response using two different methods. First, we constructed a mixed effects model and extrapolated the effect of soil warming on soil carbon stocks under anticipated shifts in surface temperature during the 21st century. We saw significant vulnerability of soil carbon stocks, especially in high carbon soils. To place this effect in the context of anticipated changes in carbon inputs and moisture shifts, we applied a one pool decay model with temperature sensitivities to the field data and imposed a post-hoc correction on the Earth system model simulations to integrate the field with the simulated temperature response. We found that there was a slight elevation in the overall soil carbon losses, but that the field uncertainty of the temperature sensitivity parameter was as large as the variation in the among model soil carbon projections. This implies that model-data integration is unlikely to constrain soil carbon simulations and highlights the importance of representing parameter uncertainty in these Earth system models to inform emissions targets.

BOREAS HYD-6 Ground Gravimetric Soil Moisture Data

NASA Technical Reports Server (NTRS)

Carroll, Thomas; Knapp, David E. (Editor); Hall, Forrest G. (Editor); Peck, Eugene L.; Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-6 team collected several data sets related to the moisture content of soil and overlying humus layers. This data set contains percent soil moisture ground measurements. These data were collected on the ground along the various flight lines flown in the Southern Study Area (SSA) and Northern Study Area (NSA) during 1994 by the gamma ray instrument. The data are available in tabular ASCII files. The HYD-06 ground gravimetric soil moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Understanding Dynamic Soil Water Repellency and its Hydrological Implications

NASA Astrophysics Data System (ADS)

Beatty, S. M.; Smith, J. E.

2009-05-01

The adverse effects of water repellent soils on vadose zone hydrology are being increasingly identified worldwide in both rural and urban landscapes. Among the affected landscapes are agricultural fields, forests, effluent application sites, golf greens, wetlands, and wildfire sites. In spite of cross-discipline research efforts put forth in recent years, understanding of fundamental parameters controlling soil water behaviour in these systems is lacking. This is due, in part, to inherent complexities of water repellent soil systems and logistical shortcomings of methods commonly used by researchers in-situ and in the lab. As a result, modeling flow in these systems has further proven to be a difficult task. The objectives of our study were 1) to systematically measure and quantify water infiltration and distribution in dynamic water repellent systems and 2) to identify fundamental hydraulic behaviours that lead to the expression of changes in soil water repellency. To achieve this, we combined techniques to elucidate soil- water interactions at a post-wildfire site. Field tests and subsequent lab work reveal essential hydrological information on fire-affected water repellent soils at variable scales and under different burn conditions. Through the use of traditional and newer techniques, our work shows unique and previously unreported behaviour of soil water in these systems. We also address limitations of current field methods used to study repellency and associated infiltration behaviours.

In-situ Subsurface Soil Analyzer

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

Ulmer, Chris

The Department of Energy’s (DOE’s) Terrestrial Ecosystem Science (TES) program is seeking improved sensor systems for monitoring hydro-biogeochemical processes in complex subsurface environments. The TES program is specifically interested in acquiring chemical and structural information regarding the type and nature of the hydration and redox states of subsurface chemical species. The technology should be able to perform on-site and real-time measurements to provide information not available using current sample acquisition and preservation processes. To address the needs of the DOE and the terrestrial science community, Physical Optics Corporation (POC) worked on the development of a new In-Situ Subsurface Soil Analyzermore » (ISSA) based on magnetic resonance technologies. Benchtop testing was performed to assess the feasibility of continuous wave electron pair resonance (CW-EPR) detection of chemical species in subsurface soil systems.« less

Soil nitrogen balance assessment and its application for sustainable agriculture and environment.

PubMed

Roy, Rabindra Nath; Misra, Ram Vimal

2005-12-01

Soil nitrogen balance assessment (SNBA) serves as an effective tool for estimating the magnitude of nitrogen loss/gain of the agro-eco systems and to appraise their sustainability. SNBA brings forth awareness of soil fertility problems, besides providing information relating to the resultant release of nitrogen into the environment consequent to agricultural practices. Quantitative information relating to nitrogen escape into the environment through such exercises can be gainfully utilized for identification of causative factors, enhancing fertilizer use efficiency and formulating programmes aimed at plugging N leakages. An overview of nitrogen balance approaches and methodologies is presented. A deeper understanding and insight into the agro-eco systems provided by the SNBA exercises can lay the basis for the formulation of effective agronomic interventions and policies aimed at promoting sustainable agriculture and a benign environment.

Soil nitrogen balance assessment and its application for sustainable agriculture and environment.

PubMed

Roy, Rabindra Nath; Misra, Ram Vimal

2005-09-01

Soil nitrogen balance assessment (SNBA) serves as an effective tool for estimating the magnitude of nitrogen loss/gain of the agro-eco systems and to appraise their sustainability. SNBA brings forth awareness of soil fertility problems, besides providing information relating to the resultant release of nitrogen into the environment consequent to agricultural practices. Quantitative information relating to nitrogen escape into the environment through such exercises can be gainfully utilized for identification of causative factors, enhancing fertilizer use efficiency and formulating programmes aimed at plugging N leakages. An overview of nitrogen balance approaches and methodologies is presented. A deeper understanding and insight into the agro-eco systems provided by the SNBA exercises can lay the basis for the formulation of effective agronomic interventions and policies aimed at promoting sustainable agriculture and a benign environment.

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

NASA Technical Reports Server (NTRS)

Pelletier, R. E.; Griffin, R. H.

1985-01-01

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

Can soil change be assessed for the Victorian dairy industry?

NASA Astrophysics Data System (ADS)

Aarons, Sharon R.; Crawford, Douglas; Imhof, Mark; Gourley, Cameron

2015-07-01

Meeting the increased demand for dairy products will require careful management of soils to minimise land degradation and sustain increased production. Key to providing farmers with the tools to manage their soils sustainably, is firstly understanding the soil types currently managed by dairy farmers, and secondly quantifying changes in soil properties in response to management. The Victorian Land Use Information System was interrogated to identify dairy land parcels and these data overlaid on soil survey information to identify the dominant soil orders managed by dairy farmers in the three dairy regions of Victoria. Of the approximately 590,000 hectares of dairy land identified across the state, Sodosols (33%), Chromosols (20%), Dermosols (16%), and Vertosols (11%) are the major soil Orders represented, although the dominant soil Orders vary for each region. Legacy data from research and extension activities undertaken between 1995 and 2010 were collated to understand regional differences in dairy soil properties. All soil properties were significantly and positively skewed with higher median pH, EC and available K in northern Victorian soils. Further analysis compared the 1995 to 2010 data with data from samples analysed by the government analytical laboratory between 1973 and 1980 to assess any differences over 38 years. The older soil chemical data were also positively skewed but had lower median soil pH, Olsen P and available K, consistent with the greater use of inputs by the industry in more recent years.

BOREAS HYD-1 Soil Hydraulic Properties

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David E. (Editor); Kelly, Shaun F.; Stangel, David E.; Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-1 team coordinated a program of data collection to measure and monitor soil properties in collaboration with other science team measurement needs. This data set contains soil hydraulic properties determined at the Northern Study Area (NSA) and Southern Study Area (SSA) flux tower sites based on analysis of in situ tension infiltrometer tests and laboratory-determined water retention from soil cores collected during the 1994-95 field campaigns. Results from this analysis are saturated hydraulic conductivity, and fitting parameters for the van Genuchten-Mualem soil hydraulic conductivity and water retention function at flux tower sites. The data are contained in tabular ASCII files. The HYD-01 soil hydraulic properties data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system

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

Yang, Xiaofan; Varga, Tamas; Liu, Chongxuan

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to farming, forest management and climate change. X-ray computed tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and our own code was used to noninvasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure at 31µm resolution, and extract quantitative information (root volume and surface area) from the 3D data, respectively. Based on themore » mesh generated from the root structure, computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soil hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. The flow variability and soil water distributions under different scenarios were investigated. Parameterizations were evaluated to show their impacts on the average conductivity. The pore-scale modeling approach provides realistic simulations of rhizosphere flow processes and provides useful information that can be linked to upscaled models.« less

Benefit assessment of soil and water conservation from cropland to forest in hilly Loess Plateau at Qinghai.

PubMed

Zhao, Chuanchuan; Yang, Ninggui; Wang, Zhen; Liu, Sili; Dong, Xu; Xin, Wenrong

2013-01-01

The information of slope and vegetation coverage of the monitoring region were extracted, based on DEM (Digital Evaluation Model) and Spot5 Satellite data images, and fishnet grid was generated using GIS (Geographic Information System) and RS (Remote Sensing) technique. Applying the information of slop and vegetation coverage layers into the corresponding space grid by using the function of zonal statistics and analysis, it can realize overlay analysis based on Standards for Classification and Gradation of Soil Erosion (SL190-2007), and obtains the map of soil erosion intensity of the monitoring region. Finally, according to Specifications for Assessment of Forest Ecosystem Services (LY/T1721-2008) and monitoring data of typical plot, the soil and water conservation value from cropland to forest was evaluated quantitatively in 2009. The results showed that the area, on and below the moderate level, was 93600 ha, taking up 50.03% of total conversion of farmland to forest area (185100 ha), which indicates a 14.64 million (t/a) of soil conversion, and a 1520 million Yuan for erosion control. The results of the study showed that the soil and water conservation was very effective.

A model framework to represent plant-physiology and rhizosphere processes in soil profile simulation models

NASA Astrophysics Data System (ADS)

Vanderborght, J.; Javaux, M.; Couvreur, V.; Schröder, N.; Huber, K.; Abesha, B.; Schnepf, A.; Vereecken, H.

2013-12-01

Plant roots play a crucial role in several key processes in soils. Besides their impact on biogeochemical cycles and processes, they also have an important influence on physical processes such as water flow and transport of dissolved substances in soils. Interaction between plant roots and soil processes takes place at different scales and ranges from the scale of an individual root and its directly surrounding soil or rhizosphere over the scale of a root system of an individual plant in a soil profile to the scale of vegetation patterns in landscapes. Simulation models that are used to predict water flow and solute transport in soil-plant systems mainly focus on the individual plant root system scale, parameterize single-root scale phenomena, and aggregate the root system scale to the vegetation scale. In this presentation, we will focus on the transition from the single root to the root system scale. Using high resolution non-invasive imaging techniques and methods, gradients in soil properties and states around roots and their difference from the bulk soil properties could be demonstrated. Recent developments in plant sciences provide new insights in the mechanisms that control water fluxes in plants and in the adaptation of root properties or root plasticity to changing soil conditions. However, since currently used approaches to simulate root water uptake neither resolve these small scale processes nor represent processes and controls within the root system, transferring this information to the whole soil-plant system scale is a challenge. Using a simulation model that describes flow and transport processes in the soil, resolves flow and transport towards individual roots, and describes flow and transport within the root system, such a transfer could be achieved. We present a few examples that illustrate: (i) the impact of changed rhizosphere hydraulic properties, (ii) the effect of root hydraulic properties and root system architecture, (iii) the regulation of plant transpiration by root-zone produced plant hormones, and (iv) the impact of salt accumulation at the soil-root interface on root water uptake. We further propose a framework how this process knowledge could be implemented in root zone simulation models that do not resolve small scale processes.

Mixed cropping regimes promote the soil fungal community under zero tillage.

PubMed

Silvestro, L B; Biganzoli, F; Stenglein, S A; Forjan, H; Manso, L; Moreno, M V

2018-07-01

Fungi of yield soils represent a significant portion of the microbial biomass and reflect sensitivity to changes in the ecosystem. Our hypothesis was that crops included in cropping regimes under the zero tillage system modify the structure of the soil fungi community. Conventional and molecular techniques provide complementary information for the analysis of diversity of fungal species and successful information to accept our hypothesis. The composition of the fungal community varied according to different crops included in the cropping regimes. However, we detected other factors as sources of variation among them, season and sampling depth. The mixed cropping regimes including perennial pastures and one crop per year promote fungal diversity and species with potential benefit to soil and crop. The winter season and 0-5 cm depth gave the largest evenness and fungal diversity. Trichoderma aureoviride and Rhizopus stolonifer could be used for monitoring changes in soil under zero tillage.

Application of remote sensing to estimating soil erosion potential

NASA Technical Reports Server (NTRS)

Morris-Jones, D. R.; Kiefer, R. W.

1980-01-01

A variety of remote sensing data sources and interpretation techniques has been tested in a 6136 hectare watershed with agricultural, forest and urban land cover to determine the relative utility of alternative aerial photographic data sources for gathering the desired land use/land cover data. The principal photographic data sources are high altitude 9 x 9 inch color infrared photos at 1:120,000 and 1:60,000 and multi-date medium altitude color and color infrared photos at 1:60,000. Principal data for estimating soil erosion potential include precipitation, soil, slope, crop, crop practice, and land use/land cover data derived from topographic maps, soil maps, and remote sensing. A computer-based geographic information system organized on a one-hectare grid cell basis is used to store and quantify the information collected using different data sources and interpretation techniques. Research results are compared with traditional Universal Soil Loss Equation field survey methods.

A Real-time Irrigation Forecasting System in Jiefangzha Irrigation District, China

NASA Astrophysics Data System (ADS)

Cong, Z.

2015-12-01

In order to improve the irrigation efficiency, we need to know when and how much to irrigate in real time. If we know the soil moisture content at this time, we can forecast the soil moisture content in the next days based on the rainfall forecasting and the crop evapotranspiration forecasting. Then the irrigation should be considered when the forecasting soil moisture content reaches to a threshold. Jiefangzha Irrigation District, a part of Hetao Irrigation District, is located in Inner Mongolia, China. The irrigated area of this irrigation district is about 140,000 ha mainly planting wheat, maize and sunflower. The annual precipitation is below 200mm, so the irrigation is necessary and the irrigation water comes from the Yellow river. We set up 10 sites with 4 TDR sensors at each site (20cm, 40cm, 60cm and 80cm depth) to monitor the soil moisture content. The weather forecasting data are downloaded from the website of European Centre for Medium-Range Weather Forecasts (ECMWF). The reference evapotranspiration is estimated based on FAO-Blaney-Criddle equation with only the air temperature from ECMWF. Then the crop water requirement is forecasted by the crop coefficient multiplying the reference evapotranspiration. Finally, the soil moisture content is forecasted based on soil water balance with the initial condition is set as the monitoring soil moisture content. When the soil moisture content reaches to a threshold, the irrigation warning will be announced. The irrigation mount can be estimated through three ways: (1) making the soil moisture content be equal to the field capacity; (2) making the soil moisture saturated; or (3) according to the irrigation quota. The forecasting period is 10 days. The system is developed according to B2C model with Java language. All the databases and the data analysis are carried out in the server. The customers can log in the website with their own username and password then get the information about the irrigation forecasting and other information about the irrigation. This system can be expanded in other irrigation districts. In future, it is even possible to upgrade the system for the mobile user.

Determination of Soil Erosion Risk in the Mustafakemalpasa River Basin, Turkey, Using the Revised Universal Soil Loss Equation, Geographic Information System, and Remote Sensing

NASA Astrophysics Data System (ADS)

Ozsoy, Gokhan; Aksoy, Ertugrul; Dirim, M. Sabri; Tumsavas, Zeynal

2012-10-01

Sediment transport from steep slopes and agricultural lands into the Uluabat Lake (a RAMSAR site) by the Mustafakemalpasa (MKP) River is a serious problem within the river basin. Predictive erosion models are useful tools for evaluating soil erosion and establishing soil erosion management plans. The Revised Universal Soil Loss Equation (RUSLE) function is a commonly used erosion model for this purpose in Turkey and the rest of the world. This research integrates the RUSLE within a geographic information system environment to investigate the spatial distribution of annual soil loss potential in the MKP River Basin. The rainfall erosivity factor was developed from local annual precipitation data using a modified Fournier index: The topographic factor was developed from a digital elevation model; the K factor was determined from a combination of the soil map and the geological map; and the land cover factor was generated from Landsat-7 Enhanced Thematic Mapper (ETM) images. According to the model, the total soil loss potential of the MKP River Basin from erosion by water was 11,296,063 Mg year-1 with an average soil loss of 11.2 Mg year-1. The RUSLE produces only local erosion values and cannot be used to estimate the sediment yield for a watershed. To estimate the sediment yield, sediment-delivery ratio equations were used and compared with the sediment-monitoring reports of the Dolluk stream gauging station on the MKP River, which collected data for >41 years (1964-2005). This station observes the overall efficiency of the sediment yield coming from the Orhaneli and Emet Rivers. The measured sediment in the Emet and Orhaneli sub-basins is 1,082,010 Mg year-1 and was estimated to be 1,640,947 Mg year-1 for the same two sub-basins. The measured sediment yield of the gauge station is 127.6 Mg km-2 year-1 but was estimated to be 170.2 Mg km-2 year-1. The close match between the sediment amounts estimated using the RUSLE-geographic information system (GIS) combination and the measured values from the Dolluk sediment gauge station shows that the potential soil erosion risk of the MKP River Basin can be estimated correctly and reliably using the RUSLE function generated in a GIS environment.

Land Use Planning Exercise Using Geographic Information Systems and Digital Soil Surveys

ERIC Educational Resources Information Center

Stout, Heidi M.; Lee, Brad D.

2004-01-01

Geographic information system (GIS) technology has become a valuable tool for environmental science professionals. By incorporating GIS into college-level course curricula, agricultural students become better qualified for employment opportunities. We have developed a case study-based laboratory exercise that introduces students to GIS and the…

A thermal-based remote sensing modeling system for estimating evapotranspiration from field to global scales

USDA-ARS?s Scientific Manuscript database

Thermal-infrared remote sensing of land surface temperature provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. This paper describes a robust but relatively simple thermal-based energy balance model that parameterizes the key soil/s...

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2011-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours

Using agricultural practices information for multiscale environmental assessment of phosphorus risk

NASA Astrophysics Data System (ADS)

Matos Moreira, Mariana; Lemercier, Blandine; Michot, Didier; Dupas, Rémi; Gascuel-Odoux, Chantal

2015-04-01

Phosphorus (P) is an essential nutrient for plant growth. In intensively farmed areas, excessive applications of animal manure and mineral P fertilizers to soils have raised both economic and ecological concerns. P accumulation in agricultural soils leads to increased P losses to surface waterbodies contributing to eutrophication. Increasing soil P content over time in agricultural soils is often correlated with agricultural practices; in Brittany (NW France), an intensive livestock farming region, soil P content is well correlated with animal density (Lemercier et al.,2008). Thus, a better understanding of the factors controlling P distribution is required to enable environmental assessment of P risk. The aim of this study was to understand spatial distribution of extractable (Olsen method) and total P contents and its controlling factors at the catchment scale in order to predict P contents at regional scale (Brittany). Data on soil morphology, soil tests (including P status, particles size, organic carbon…) for 198 punctual positions, crops succession since 20 years, agricultural systems, field and animal manure management were obtained on a well-characterized catchment (ORE Agrhys, 10 km²). A multivariate analysis with mixed quantitative variables and factors and a digital soil mapping approach were performed to identify variables playing a significant role in soil total and extractable P contents and distribution. Spatial analysis was performed by means of the Cubist model, a decision tree-based algorithm. Different scenarios were assessed, considering various panels of predictive variables: soil data, terrain attributes derived from digital elevation model, gamma-ray spectrometry (from airborne geophysical survey) and agricultural practices information. In the research catchment, mean extractable and total P content were 140.0 ± 63.4 mg/kg and 2862.7 ± 773.0 mg/kg, respectively. Organic and mineral P inputs, P balance, soil pH, and Al contents were positively correlated with soil P contents. Also land use, crop rotation and livestock production system influenced P contents. The highest mean values of P were found in croplands and close to pig farms. The lowest mean values of P were found in pastures and nearby dairy farms. The spatial analysis showed that sand content, geophysical parameters and P input by organic fertilization were the most significant variables for the linear predictive model of extractable P contents. For total P, geophysical parameters and P balance had the highest importance for the respective linear predictive model. This study revealed that agricultural practices information plays a significant role in soil P distribution. Once controlling factors of P spatial distribution were identified, relationships could be extrapolated at regional scale using the National Soil Test Database providing information on extractable P content and available information on agricultural practices in order to improve predictions of total P content at regional scale. Lemercier B., Gaudin, L., Walter C., Aurousseau P., Arrouays D., Schvartz C., Saby N., Follain S., Abrassart J., 2008. Soil phosphorus monitoring at the regional level by means of a soil test database. Soil Use and Management, 24, 131-138.

Assimilation of SMOS Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2016-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm(sub 3 cm(sub -3). These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve.

Assimilation of SMOS Retrievals in the Land Information System

PubMed Central

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2018-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm3 cm−3. These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve. PMID:29367795

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.

Critical carbon input to maintain current soil organic carbon stocks in global wheat systems

PubMed Central

Wang, Guocheng; Luo, Zhongkui; Han, Pengfei; Chen, Huansheng; Xu, Jingjing

2016-01-01

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1° × 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha−1 yr−1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content. PMID:26759192

Quantified carbon input for maintaining existing soil organic carbon stocks in global wheat systems

NASA Astrophysics Data System (ADS)

Wang, G.

2017-12-01

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1°× 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha-1 yr-1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

The southern Brazilian grassland biome: soil carbon stocks, fluxes of greenhouse gases and some options for mitigation.

PubMed

Pillar, V D; Tornquist, C G; Bayer, C

2012-08-01

The southern Brazilian grassland biome contains highly diverse natural ecosystems that have been used for centuries for grazing livestock and that also provide other important environmental services. Here we outline the main factors controlling ecosystem processes, review and discuss the available data on soil carbon stocks and greenhouse gases emissions from soils, and suggest opportunities for mitigation of climatic change. The research on carbon and greenhouse gases emissions in these ecosystems is recent and the results are still fragmented. The available data indicate that the southern Brazilian natural grassland ecosystems under adequate management contain important stocks of organic carbon in the soil, and therefore their conservation is relevant for the mitigation of climate change. Furthermore, these ecosystems show a great and rapid loss of soil organic carbon when converted to crops based on conventional tillage practices. However, in the already converted areas there is potential to mitigate greenhouse gas emissions by using cropping systems based on no soil tillage and cover-crops, and the effect is mainly related to the potential of these crop systems to accumulate soil organic carbon in the soil at rates that surpass the increased soil nitrous oxide emissions. Further modelling with these results associated with geographic information systems could generate regional estimates of carbon balance.

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.

Accumulation of metals by microorganisms — processes and importance for soil systems

NASA Astrophysics Data System (ADS)

Ledin, Maria

2000-08-01

Metal accumulation by solid substances can counteract metal mobilization in the environment if the solid substance is immobile. Microorganisms have a high surface area-to-volume ratio because of their small size and therefore provide a large contact area that can interact with metals in the surrounding environment. Microbial metal accumulation has received much attention in the last years due to the potential use of microorganisms for cleaning metal-polluted water. However, considerably less attention has been paid to the role of microorganisms for metal mobility in soil even though the same processes may occur there. Therefore, this paper highlights this area. The different accumulation processes that microorganisms perform are analyzed and their potential significance in soil systems is discussed. Different kinds of mechanisms can be involved in the accumulation of metals by microorganisms, e.g. adsorption, precipitation, complexation and active transport into the cell. Physicochemical parameters like pH and ionic composition, as well as biological factors are of importance for the magnitude of accumulation. Often large amounts of metals can be accumulated with varying specificity, and microorganisms may provide nucleation sites for mineral formation. Several studies of microbial metal accumulation have been made with different methods and aims. Most of these studies concern single-component systems with one organism at a time. Data from accumulation experiments with pure cultures of microorganisms have been used to model the overall metal retention in soil. A further development is experimental model systems using various solid soil components in salt medium. Microbial metal accumulation is difficult to study in situ, but some experimental methods have been applied as tools for studying real soil systems, e.g. litter bags buried in soil containing microorganisms, a method where discs with microorganisms have been put onto agar plates with soil extracts, and comparison of sterilized and non-sterilized soils or soils with or without nutrient amendment. Different aspects of microbial metal accumulation are emphasized with the different methods applied. Single-component systems have the advantage of providing excellent information of the metal binding properties of microorganisms but cannot directly be applied to metal behavior in the heterogenous systems that real soils constitute. Studies focused on the behavior of metals in real soils can, in contrast, provide information on the overall metal distribution but less insight into the processes involved. Obviously, a combination of approaches is needed to describe metal distribution and mobility in polluted soil such as areas around mines. Different kinds of multi-component systems as well as modelling may bridge the gap between these two types of studies. Several experimental methods, complementary to each other and designed to allow for comparison, may emphasize different aspects of metal accumulation and should therefore be considered. To summarize, there are studies that indicate that microorganisms may also accumulate metals in soil and that the amounts may be considerable. However, much work remains to be done, with the focus of microorganisms in soil. It is also important to put microbial metal accumulation in relation to other microbial processes in soil, which can influence metal mobility, to determine the overall influence of soil microorganisms on metal mobility, and to be able to quantify these processes.

The Impact of AMSR-E Soil Moisture Assimilation on Evapotranspiration Estimation

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Kumar, Sujay; Mocko, David; Tian, Yudong

2012-01-01

An assessment ofETestimates for current LDAS systems is provided along with current research that demonstrates improvement in LSM ET estimates due to assimilating satellite-based soil moisture products. Using the Ensemble Kalman Filter in the Land Information System, we assimilate both NASA and Land Parameter Retrieval Model (LPRM) soil moisture products into the Noah LSM Version 3.2 with the North American LDAS phase 2 CNLDAS-2) forcing to mimic the NLDAS-2 configuration. Through comparisons with two global reference ET products, one based on interpolated flux tower data and one from a new satellite ET algorithm, over the NLDAS2 domain, we demonstrate improvement in ET estimates only when assimilating the LPRM soil moisture product.

Heavy Metal Pollution in a Soil-Rice System in the Yangtze River Region of China.

PubMed

Liu, Zhouping; Zhang, Qiaofen; Han, Tiqian; Ding, Yanfei; Sun, Junwei; Wang, Feijuan; Zhu, Cheng

2015-12-22

Heavy metals are regarded as toxic trace elements in the environment. Heavy metal pollution in soil or rice grains is of increasing concern. In this study, 101 pairs of soil and rice samples were collected from the major rice-producing areas along the Yangtze River in China. The soil properties and heavy metal (i.e., Cd, Hg, Pb and Cr) concentrations in the soil and rice grains were analyzed to evaluate the heavy metal accumulation characteristics of the soil-rice systems. The results showed that the Cd, Hg, Pb and Cr concentrations in the soil ranged from 0.10 to 4.64, 0.01 to 1.46, 7.64 to 127.56, and 13.52 to 231.02 mg·kg(-)¹, respectively. Approximately 37%, 16%, 60% and 70% of the rice grain samples were polluted by Cd, Hg, Pb, and Cr, respectively. The degree of heavy metal contamination in the soil-rice systems exhibited a regional variation. The interactions among the heavy metal elements may also influence the migration and accumulation of heavy metals in soil or paddy rice. The accumulation of heavy metals in soil and rice grains is related to a certain extent to the pH and soil organic matter (SOM). This study provides useful information regarding heavy metal accumulation in soil to support the safe production of rice in China. The findings from this study also provide a robust scientific basis for risk assessments regarding ecological protection and food safety.

Heavy Metal Pollution in a Soil-Rice System in the Yangtze River Region of China

PubMed Central

Liu, Zhouping; Zhang, Qiaofen; Han, Tiqian; Ding, Yanfei; Sun, Junwei; Wang, Feijuan; Zhu, Cheng

2015-01-01

Heavy metals are regarded as toxic trace elements in the environment. Heavy metal pollution in soil or rice grains is of increasing concern. In this study, 101 pairs of soil and rice samples were collected from the major rice-producing areas along the Yangtze River in China. The soil properties and heavy metal (i.e., Cd, Hg, Pb and Cr) concentrations in the soil and rice grains were analyzed to evaluate the heavy metal accumulation characteristics of the soil-rice systems. The results showed that the Cd, Hg, Pb and Cr concentrations in the soil ranged from 0.10 to 4.64, 0.01 to 1.46, 7.64 to 127.56, and 13.52 to 231.02 mg·kg−1, respectively. Approximately 37%, 16%, 60% and 70% of the rice grain samples were polluted by Cd, Hg, Pb, and Cr, respectively. The degree of heavy metal contamination in the soil-rice systems exhibited a regional variation. The interactions among the heavy metal elements may also influence the migration and accumulation of heavy metals in soil or paddy rice. The accumulation of heavy metals in soil and rice grains is related to a certain extent to the pH and soil organic matter (SOM). This study provides useful information regarding heavy metal accumulation in soil to support the safe production of rice in China. The findings from this study also provide a robust scientific basis for risk assessments regarding ecological protection and food safety. PMID:26703698

Analysis of the bacterial community changes in soil for septic tank effluent treatment in response to bio-clogging.

PubMed

Nie, J Y; Zhu, N W; Zhao, K; Wu, L; Hu, Y H

2011-01-01

Soil columns were set up to survey the bacterial community in the soil for septic tank effluent treatment. When bio-clogging occurred in the soil columns, the effluent from the columns was in poorer quality. To evaluate changes of the soil bacterial community in response to bio-clogging, the bacterial community was characterized by DNA gene sequences from soil samples after polymerase chain reaction coupled with denaturing gradient gel electrophoresis process. Correspondence analysis showed that Proteobacteria related bacteria were the main bacteria within the soil when treating septic tank effluent. However, Betaproteobacteria related bacteria were the dominant microorganisms in the normal soil, whereas Alphaproteobacteria related bacteria were more abundant in the clogged soil. This study provided insight into changes of the soil bacterial community in response to bio-clogging. The results can supply some useful information for the design and management of soil infiltration systems.

Hyperspectral Imaging Analysis for the Classification of Soil Types and the Determination of Soil Total Nitrogen

PubMed Central

Jia, Shengyao; Li, Hongyang; Wang, Yanjie; Tong, Renyuan; Li, Qing

2017-01-01

Soil is an important environment for crop growth. Quick and accurately access to soil nutrient content information is a prerequisite for scientific fertilization. In this work, hyperspectral imaging (HSI) technology was applied for the classification of soil types and the measurement of soil total nitrogen (TN) content. A total of 183 soil samples collected from Shangyu City (People’s Republic of China), were scanned by a near-infrared hyperspectral imaging system with a wavelength range of 874–1734 nm. The soil samples belonged to three major soil types typical of this area, including paddy soil, red soil and seashore saline soil. The successive projections algorithm (SPA) method was utilized to select effective wavelengths from the full spectrum. Pattern texture features (energy, contrast, homogeneity and entropy) were extracted from the gray-scale images at the effective wavelengths. The support vector machines (SVM) and partial least squares regression (PLSR) methods were used to establish classification and prediction models, respectively. The results showed that by using the combined data sets of effective wavelengths and texture features for modelling an optimal correct classification rate of 91.8%. could be achieved. The soil samples were first classified, then the local models were established for soil TN according to soil types, which achieved better prediction results than the general models. The overall results indicated that hyperspectral imaging technology could be used for soil type classification and soil TN determination, and data fusion combining spectral and image texture information showed advantages for the classification of soil types. PMID:28974005

A data base approach for prediction of deforestation-induced mass wasting events

NASA Technical Reports Server (NTRS)

Logan, T. L.

1981-01-01

A major topic of concern in timber management is determining the impact of clear-cutting on slope stability. Deforestation treatments on steep mountain slopes have often resulted in a high frequency of major mass wasting events. The Geographic Information System (GIS) is a potentially useful tool for predicting the location of mass wasting sites. With a raster-based GIS, digitally encoded maps of slide hazard parameters can be overlayed and modeled to produce new maps depicting high probability slide areas. The present investigation has the objective to examine the raster-based information system as a tool for predicting the location of the clear-cut mountain slopes which are most likely to experience shallow soil debris avalanches. A literature overview is conducted, taking into account vegetation, roads, precipitation, soil type, slope-angle and aspect, and models predicting mass soil movements. Attention is given to a data base approach and aspects of slide prediction.

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

7 CFR 611.11 - Soil survey information.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 6 2014-01-01 2014-01-01 false Soil survey information. 611.11 Section 611.11..., DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SOIL SURVEYS Soil Survey Operations § 611.11 Soil survey information. (a) Availability. NRCS disseminates soil survey information to the public by any of the means...

7 CFR 611.11 - Soil survey information.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 6 2011-01-01 2011-01-01 false Soil survey information. 611.11 Section 611.11..., DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SOIL SURVEYS Soil Survey Operations § 611.11 Soil survey information. (a) Availability. NRCS disseminates soil survey information to the public by any of the means...

7 CFR 611.11 - Soil survey information.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 6 2010-01-01 2010-01-01 false Soil survey information. 611.11 Section 611.11..., DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SOIL SURVEYS Soil Survey Operations § 611.11 Soil survey information. (a) Availability. NRCS disseminates soil survey information to the public by any of the means...

7 CFR 611.11 - Soil survey information.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 6 2013-01-01 2013-01-01 false Soil survey information. 611.11 Section 611.11..., DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SOIL SURVEYS Soil Survey Operations § 611.11 Soil survey information. (a) Availability. NRCS disseminates soil survey information to the public by any of the means...

7 CFR 611.11 - Soil survey information.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 6 2012-01-01 2012-01-01 false Soil survey information. 611.11 Section 611.11..., DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SOIL SURVEYS Soil Survey Operations § 611.11 Soil survey information. (a) Availability. NRCS disseminates soil survey information to the public by any of the means...

Emergent Imaging and Geospatial Technologies for Soil Investigations

NASA Technical Reports Server (NTRS)

DeGloria, Stephen D.; Beaudette, Dylan E.; Irons, James R.; Libohova, Zamir; O'Neill, Peggy E.; Owens, Phillip R.; Schoeneberger, Philip J.; West, Larry T.; Wysocki, Douglas A.

2014-01-01

Soil survey investigations and inventories form the scientific basis for a wide spectrum of agronomic and environmental management programs. Soil data and information help formulate resource conservation policies of federal, state, and local governments that seek to sustain our agricultural production system while enhancing environmental quality on both public and private lands. The dual challenges of increasing agricultural production and ensuring environmental integrity require electronically available soil inventory data with both spatial and attribute quality. Meeting this societal need in part depends on development and evaluation of new methods for updating and maintaining soil inventories for sophisticated applications, and implementing an effective framework to conceptualize and communicate tacit knowledge from soil scientists to numerous stakeholders.

Physical and hydrological properties of the soil after Pine harvesting in Maule, Chile

NASA Astrophysics Data System (ADS)

Fernández Raga, María; Fuentes Espoz, Juan Pablo

2014-05-01

The south of Chile has been under great pressure for about 150 years, with the replacement of native forests by agricultural crops and subsequently by plantations with fast-growing exotic species. Historically, it was considered that these plantations have stopped the degradation process of the ground. However, the restoration of the soil system can be considered as very limited or even null because of three reasons: the rotations of these artificial forest systems are too short (just 25 years ), the chosen areas are already degraded land, and after the harvesting it is common to get fire to clean. The objective of this research was to evaluate current forest management practices of these forest systems to make them more sustainable, mainly studying the effect of harvesting and waste management planting some physical - hydrological properties of the soil. This research was done in "Las Brisas", a degraded soil characterized by different planting practices of forest species, which have been harvested and, after that, burnt for taking out the residual waste. The study tried to determine the variations in the water content of the soil after fire at different depths, obtaining moisture profiles that reflect the change in soil moisture while simulating rain occurs. temperature of the fire. Several samples were taken and divided into four different experiments of management practices: some of them were dry, others were burnt, others suffered both processes and the last no process at all. Some analysis were done to determine the behavior of the main hydrological properties (ie particle size distribution, aggregate stability , hydrophobicity , infiltration ). The information collected was analyzed by the hydrologic model Hydrus -2D, to fully assess the impact of the extraction of the forest from a highly sensitive system erosive phenomena. The information obtained will be published.

Mapping Soil hydrologic features in a semi-arid irrigated area in Spain

NASA Astrophysics Data System (ADS)

Jiménez-Aguirre, M.° Teresa; Isidoro, Daniel; Usón, Asunción

2016-04-01

The lack of soil information is a managerial problem in irrigated areas in Spain. The Violada Irrigation District (VID; 5234 ha) is a gypsic, semi-arid region in the Middle Ebro River Basin, northeast Spain. VID is under irrigation since the 1940's. The implementation of the flood irrigation system gave rise to waterlogging problems, solved along the years with the installation of an artificial drainage network. Aggregated water balances have been performed in VID since the early 1980's considering average soil properties and aggregated irrigation data for the calculations (crop evapotranspiration, canal seepage, and soil drainage). In 2008-2009, 91% of the VID was modernized to sprinkler irrigation. This new system provides detailed irrigation management information that together with detailed soil information would allow for disaggregated water balances for a better understanding of the system. Our goal was to draw a semi-detailed soil map of VID presenting the main soil characteristics related to irrigation management. A second step of the work was to set up pedotransfer functions (PTF) to estimate the water content and saturated hydraulic conductivity (Ks) from easily measurable parameters. Thirty four pits were opened, described and sampled for chemical and physical properties. Thirty three additional auger holes were sampled for water holding capacity (WHC; down to 60 cm), helping to draw the soil units boundaries. And 15 Ks tests (inverse auger hole method) were made. The WHC was determined as the difference between the field capacity (FC) and wilting point (WP) measured in samples dried at 40°C during 5 days. The comparison with old values dried at 105°C for 2 days highlighted the importance of the method when gypsum is present in order to avoid water removal from gypsum molecules. The soil map was drawn down to family level. Thirteen soil units were defined by the combination of five subgroups [Typic Calcixerept (A), Petrocalcic Calcixerept (B), Gypsic Haploxerept (C), Typic Xerorthent (D), and Typic Xerofluvent (E)] and six particle size families [Fine (1), Fine-silty (2), Fine-loamy (3), Coarse-loamy (4), Loamy Superficial (5) and Loamy-skeletal (6)]. Two great soil zones were defined: the more calcic glacis (A and B subgroups) dominated by coarse textures (4-6); and the more gypsic, fine textured valley floors (C, D and E) (1-2-3) with the exception of the superficial gypsic high lands (D5). In all the soils in VID Calcium Carbonate Equivalent (CCE) was high (though lower in the valleys) and silt was the main textural fraction. The coarser textured glacis had low Gypsum Content (GC), lower WHC and higher Ks while the valley bottoms had high GC, fine textures and lower Ks. The soil water retention properties (FC and WP) could be calculated from textural properties (clay, and fine silt fractions) and the Ks could be related to sand and GC by means of meaningful PTF's. The use of disaggregated soil information (combined with distributed irrigation data) may lead to improved water balance calculations and suggest management options for a better water use in VID.

Pedotransfer Functions in Earth System Science: Challenges and Perspectives: PTFs in Earth system science perspective

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

Van Looy, Kris; Bouma, Johan; Herbst, Michael

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. Here in this article, 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 upscalingmore » 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.« less

Pedotransfer Functions in Earth System Science: Challenges and Perspectives: PTFs in Earth system science perspective

DOE PAGES

Van Looy, Kris; Bouma, Johan; Herbst, Michael; ...

2017-12-28

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. Here in this article, 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 upscalingmore » 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.« less

Permeability of soils in Mississippi

USGS Publications Warehouse

O'Hara, Charles G.

1994-01-01

The permeability of soils in Mississippi was determined and mapped using a geographic information system (GIS). Soil permeabilities in Mississippi were determined to range in value from nearly 0.0 to values exceeding 5.0 inches per hour. The U.S. Soil Conservation Service's State Soil Geographic Data Base (STATSGO) was used as the primary source of data for the determination of area-weighted soil permeability. STATSGO provides soil layer properties that are spatially referenced to mapped areas. These mapped areas are referred to as polygons in the GIS. The polygons arc boundaries of soils mapped as a group and are given unique Map Unit Identifiers (MUIDs). The data describing the physical characteristics of the soils within each polygon are stored in a tabular data base format and are referred to as attributes. The U.S. Soil Conservation Service developed STATSGO to be primarily used as a guide for regional resource planning, management, and monitoring. STATSGO was designed so that soil information could be extracted from properties tables at the layer level, combined by component, and statistically expanded to cover the entire map unit. The results of this study provide a mapped value for permeability which is representative of the vertical permeability of soils in that area. The resultant permeability map provides a representative vertical soil permeability for a given area sufficient for county, multi- county, and area planning, and will be used as the soil permeability data component in the evaluation of the susceptibility of major aquifers to contami- nation in Mississippi.

Spatial discretization of large watersheds and its influence on the estimation of hillslope sediment yield

USDA-ARS?s Scientific Manuscript database

The combined use of water erosion models and geographic information systems (GIS) has facilitated soil loss estimation at the watershed scale. Tools such as the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP) model provide a convenient spatially distributed soil loss estimat...

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.

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

The Characteristics of Electrical and Physical Properties of Peat Soil in Rasau Village, West Kalimantan

NASA Astrophysics Data System (ADS)

Aminudin, A.; Hasanah, T. R.; Iryati, M.

2018-05-01

The Electrical and physical properties can be used as indicators for measuring soil conditions. One of the methods developed in agricultural systems to obtain information on soil conditions is through measuring of electrical conductivity. Peat soil is one of the natural resources that exist in Indonesia. This study aims to determine the characteristics of peat soil in Rasau village, West Kalimantan. This research was conducted by the properties of electrical conductivity and water content using 5TE Water Contents and EC Sensor equipment, but also to know the change of physical nature of peat soil covering peat soil and peat type. The results showed that the electrical conductivity value of 1-4 samples was 0.02 -0.29 dS/m and the volume water content value (VWC) was 0.255-0.548 m3/m3 and the physical characteristics obtained were peat colour brown to dark brown that allegedly the soil still has a very high content of organic material derived from weathering plants and there are discovery of wood chips, wood powder and leaf powder on the ground. Knowing the information is expected to identify the land needs to be developed to be considered for future peat soil utilization.

Spatial heterogeneity distribution of soil total nitrogen and total phosphorus in the Yaoxiang watershed in a hilly area of northern China based on geographic information system and geostatistics.

PubMed

Liu, Yu; Gao, Peng; Zhang, Liyong; Niu, Xiang; Wang, Bing

2016-10-01

Soil total nitrogen (STN) and total phosphorus (STP) are important indicators of soil nutrients and the important indexes of soil fertility and soil quality evaluation. Using geographic information system (GIS) and geostatistics, the spatial heterogeneity distribution of STN and STP in the Yaoxiang watershed in a hilly area of northern China was studied. The results showed that: (1) The STN and STP contents showed a declining trend with the increase in soil depth; the variation coefficients ( C v ) of STN and STP in the 0- to 10-cm soil layer (42.25% and 14.77%, respectively) were higher than in the 10- to 30-cm soil layer (28.77% and 11.60%, respectively). Moreover, the C v of STN was higher than that of STP. (2) The maximum C 0 /( C 0  +  C 1 ) of STN and STP in the soil layers was less than 25%, this indicated that a strong spatial distribution autocorrelation existed for STN and STP; and the STP showed higher intensity and more stable variation than the STN. (3) From the correlation analysis, we concluded that the topographic indexes such as elevation and slope direction all influenced the spatial distribution of STN and STP (correlation coefficients were 0.688 and 0.518, respectively). (4) The overall distribution of STN and STP in the Yaoxiang watershed decreased from the northwest to the southeast. This variation trend was similar to the watershed DEM trend and was significantly influenced by vegetation and topographic factors. These results revealed the spatial heterogeneity distribution of STN and STP, and addressed the influences of forest vegetation coverage, elevation, and other topographic factors on the spatial distribution of STN and STP at the watershed scale.

Seeing the soil through the net: an eye-opener on the soil map of the Flemish region (Belgium)

NASA Astrophysics Data System (ADS)

Dondeyne, Stefaan; Vanierschot, Laura; Langohr, Roger; Van Ranst, Eric; Deckers, Jozef; Oorts, Katrien

2017-04-01

A systematic soil survey of Belgium was conducted from 1948 to 1991. Field surveys were done at the detailed scale of 1:5000 with the final maps published at a 1:20,000 scale. The legend of these detailed soil maps (scale 1:20,000) has been converted to the 3rd edition of the international soil classification system 'World Reference Base for Soil Resources' (WRB). Over the last years, the government of the Flemish region made great efforts to make these maps, along with other environmental data, available to the general audience through the internet. The soil maps are widely used and consulted by researchers, teachers, land-use planners, environmental consultancy agencies and archaeologists. The maps can be downloaded and consulted in the viewer 'Visual Soil Explorer' ('Bodemverkenner'). To increase the legibility of the maps, we assembled a collection of photographs from soil profiles representing 923 soil types and 413 photos of related landscape settings. By clicking on a specific location in the 'Visual Soil Explorer', pictures of the corresponding soil type and landscape appear in a pop-up window, with a brief explanation about the soil properties. The collection of photographs of soil profiles cover almost 80% of the total area of the Flemish region, and include the 100 most common soil types. Our own teaching experience shows that these information layers are particular valuable for teaching soil geography and earth sciences in general. Overall, such visual information layers should contribute to a better interpretation of the soil maps and legacy soil data by serving as an eye-opener on the soil map to the wider community.

Water content determination of soil surface in an intensive apple orchard

NASA Astrophysics Data System (ADS)

Riczu, Péter; Nagy, Gábor; Tamás, János

2015-04-01

Currently in Hungary, less than 100,000 hectares of orchards can be found, from which cultivation of apple is one of the most dominant ones. Production of marketable horticulture products can be difficult without employing advanced and high quality horticulture practices, which, in turn, depends on appropriate management and irrigation systems, basically. The got out water amount depend on climatic, edafic factors and the water demand of plants as well. The soil water content can be determined by traditional and modern methods. In order to define soil moisture content, gravimetry measurement is one of the most accurate methods, but it is time consuming and sometimes soil sampling and given results are in different times. Today, IT provides the farmers such tools, like global positioning system (GPS), geographic information system (GIS) and remote sensing (RS). These tools develop in a great integration rapidly. RS methods are ideal to survey larger area quick and accurate. Laser scanning is a novel technique which analyses a real-world or object environment to collect structural and spectral data. In order to obtain soil moisture information, the Leica ScanStation C10 terrestrial 3D laser scanner was used on an intensive apple orchard on the Study and Regional Research Farm of the University of Debrecen, near Pallag. Previously, soil samples from the study area with different moisture content were used as reference points. Based on the return intensity values of the laser scanner can be distinguished the different moisture content areas of soil surface. Nevertheless, the error of laser distance echo were examined and statistically evaluated. This research was realized in the frames of TÁMOP 4.2.4. A/2-11-1-2012-0001 "National Excellence Program - Elaborating and operating an inland student and researcher personal support system". The project was subsidized by the European Union and co-financed by the European Social Fund.

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.

A Novel Growing Device Inspired by Plant Root Soil Penetration Behaviors

PubMed Central

Sadeghi, Ali; Tonazzini, Alice; Popova, Liyana; Mazzolai, Barbara

2014-01-01

Moving in an unstructured environment such as soil requires approaches that are constrained by the physics of this complex medium and can ensure energy efficiency and minimize friction while exploring and searching. Among living organisms, plants are the most efficient at soil exploration, and their roots show remarkable abilities that can be exploited in artificial systems. Energy efficiency and friction reduction are assured by a growth process wherein new cells are added at the root apex by mitosis while mature cells of the root remain stationary and in contact with the soil. We propose a new concept of root-like growing robots that is inspired by these plant root features. The device penetrates soil and develops its own structure using an additive layering technique: each layer of new material is deposited adjacent to the tip of the device. This deposition produces both a motive force at the tip and a hollow tubular structure that extends to the surface of the soil and is strongly anchored to the soil. The addition of material at the tip area facilitates soil penetration by omitting peripheral friction and thus decreasing the energy consumption down to 70% comparing with penetration by pushing into the soil from the base of the penetration system. The tubular structure provides a path for delivering materials and energy to the tip of the system and for collecting information for exploratory tasks. PMID:24587244

Record of Decision for the First Active Duty F-35A Operational Base

DTIC Science & Technology

2013-12-02

trucks or sprinkler systems to keep all areas of vehicle movement damp enough to prevent dust from leaving the construction area. - Temporary wind...synergy between the operational and logistics communities in managing a new, highly complex weapon system . ACC’s existing F-16 squadrons at Hill AFB...Share information with local fire departments on F-35A crash response procedures. Soils and Water • Sequence construction activities to limit the soil

Pathogens and fecal indicators in waste stabilization pond systems with direct reuse for irrigation: Fate and transport in water, soil and crops.

PubMed

Verbyla, M E; Iriarte, M M; Mercado Guzmán, A; Coronado, O; Almanza, M; Mihelcic, J R

2016-05-01

Wastewater use for irrigation is expanding globally, and information about the fate and transport of pathogens in wastewater systems is needed to complete microbial risk assessments and develop policies to protect public health. The lack of maintenance for wastewater treatment facilities in low-income areas and developing countries results in sludge accumulation and compromised performance over time, creating uncertainty about the contamination of soil and crops. The fate and transport of pathogens and fecal indicators was evaluated in waste stabilization ponds with direct reuse for irrigation, using two systems in Bolivia as case studies. Results were compared with models from the literature that have been recommended for design. The removal of Escherichia coli in both systems was adequately predicted by a previously-published dispersed flow model, despite more than 10years of sludge accumulation. However, a design equation for helminth egg removal overestimated the observed removal, suggesting that this equation may not be appropriate for systems with accumulated sludge. To assess the contamination of soil and crops, ratios were calculated of the pathogen and fecal indicator concentrations in soil or on crops to their respective concentrations in irrigation water (termed soil-water and crop-water ratios). Ratios were similar within each group of microorganisms but differed between microorganism groups, and were generally below 0.1mLg(-1) for coliphage, between 1 and 100mLg(-1) for Giardia and Cryptosporidium, and between 100 and 1000mLg(-1) for helminth eggs. This information can be used for microbial risk assessments to develop safe water reuse policies in support of the United Nations' 2030 Sustainable Development Agenda. Copyright © 2016 Elsevier B.V. All rights reserved.

Integrated Approach to Inform the New York City Water Supply System Coupling SAR Remote Sensing Observations and the SWAT Watershed Model

NASA Astrophysics Data System (ADS)

Tesser, D.; Hoang, L.; McDonald, K. C.

2017-12-01

Efforts to improve municipal water supply systems increasingly rely on an ability to elucidate variables that drive hydrologic dynamics within large watersheds. However, fundamental model variables such as precipitation, soil moisture, evapotranspiration, and soil freeze/thaw state remain difficult to measure empirically across large, heterogeneous watersheds. Satellite remote sensing presents a method to validate these spatially and temporally dynamic variables as well as better inform the watershed models that monitor the water supply for many of the planet's most populous urban centers. PALSAR 2 L-band, Sentinel 1 C-band, and SMAP L-band scenes covering the Cannonsville branch of the New York City (NYC) water supply watershed were obtained for the period of March 2015 - October 2017. The SAR data provides information on soil moisture, free/thaw state, seasonal surface inundation, and variable source areas within the study site. Integrating the remote sensing products with watershed model outputs and ground survey data improves the representation of related processes in the Soil and Water Assessment Tool (SWAT) utilized to monitor the NYC water supply. PALSAR 2 supports accurate mapping of the extent of variable source areas while Sentinel 1 presents a method to model the timing and magnitude of snowmelt runoff events. SMAP Active Radar soil moisture product directly validates SWAT outputs at the subbasin level. This blended approach verifies the distribution of soil wetness classes within the watershed that delineate Hydrologic Response Units (HRUs) in the modified SWAT-Hillslope. The research expands the ability to model the NYC water supply source beyond a subset of the watershed while also providing high resolution information across a larger spatial scale. The global availability of these remote sensing products provides a method to capture fundamental hydrology variables in regions where current modeling efforts and in situ data remain limited.

Spatial distribution of pH and organic matter in urban soils and its implications on site-specific land uses in Xuzhou, China.

PubMed

Mao, Yingming; Sang, Shuxun; Liu, Shiqi; Jia, Jinlong

2014-05-01

The spatial variation of soil pH and soil organic matter (SOM) in the urban area of Xuzhou, China, was investigated in this study. Conventional statistics, geostatistics, and a geographical information system (GIS) were used to produce spatial distribution maps and to provide information about land use types. A total of 172 soil samples were collected based on grid method in the study area. Soil pH ranged from 6.47 to 8.48, with an average of 7.62. SOM content was very variable, ranging from 3.51 g/kg to 17.12 g/kg, with an average of 8.26 g/kg. Soil pH followed a normal distribution, while SOM followed a log-normal distribution. The results of semi-variograms indicated that soil pH and SOM had strong (21%) and moderate (44%) spatial dependence, respectively. The variogram model was spherical for soil pH and exponential for SOM. The spatial distribution maps were achieved using kriging interpolation. The high pH and high SOM tended to occur in the mixed forest land cover areas such as those in the southwestern part of the urban area, while the low values were found in the eastern and the northern parts, probably due to the effect of industrial and human activities. In the central urban area, the soil pH was low, but the SOM content was high, which is mainly attributed to the disturbance of regional resident activities and urban transportation. Furthermore, anthropogenic organic particles are possible sources of organic matter after entering the soil ecosystem in urban areas. These maps provide useful information for urban planning and environmental management. Copyright © 2014 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Investigation of an anthrax outbreak in Alberta in 1999 using a geographic information system

PubMed Central

Parkinson, Robert; Rajic, Andrijana; Jenson, Chris

2003-01-01

A Geographic Information System was used to document an anthrax outbreak in Alberta in 1999 and to describe the physical and environmental conditions of the area. The majority of infected farms were located on poorly drained organic soils. Regulatory agencies should consider adopting this tool for animal disease outbreak investigations. PMID:12715984

Integrating geospatial data and cropping system simulation within a geographic information system to analyze spatial seed cotton yield, water use, and irrigation requirements

USDA-ARS?s Scientific Manuscript database

The development of sensors that provide geospatial information on crop and soil conditions has been a primary success for precision agriculture. However, further developments are needed to integrate geospatial data into computer algorithms that spatially optimize crop production while considering po...

SMAP Data Assimilation at NASA SPoRT

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

2016-01-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center maintains a near-real- time run of the Noah Land Surface Model within the Land Information System (LIS) at 3-km resolution. Soil moisture products from this model are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. We have implemented assimilation of soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active/ Passive (SMAP) satellites, and are now evaluating the SMAP assimilation. The SMAP-enhanced LIS product is planned for public release by October 2016.

Development of an Integrated Moisture Index for predicting species composition

Treesearch

Louis R. Iverson; Charles T. Scott; Martin E. Dale; Anantha Prasad

1996-01-01

A geographic information system (GIS) approach was used to develop an Integrated Moisture Index (IMI), which was used to predict species composition for Ohio forests. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and the water-holding capacity of the soil) were derived from elevation and soils...

Determination of soil erosion risk in the Mustafakemalpasa River Basin, Turkey, using the revised universal soil loss equation, geographic information system, and remote sensing.

PubMed

Ozsoy, Gokhan; Aksoy, Ertugrul; Dirim, M Sabri; Tumsavas, Zeynal

2012-10-01

Sediment transport from steep slopes and agricultural lands into the Uluabat Lake (a RAMSAR site) by the Mustafakemalpasa (MKP) River is a serious problem within the river basin. Predictive erosion models are useful tools for evaluating soil erosion and establishing soil erosion management plans. The Revised Universal Soil Loss Equation (RUSLE) function is a commonly used erosion model for this purpose in Turkey and the rest of the world. This research integrates the RUSLE within a geographic information system environment to investigate the spatial distribution of annual soil loss potential in the MKP River Basin. The rainfall erosivity factor was developed from local annual precipitation data using a modified Fournier index: The topographic factor was developed from a digital elevation model; the K factor was determined from a combination of the soil map and the geological map; and the land cover factor was generated from Landsat-7 Enhanced Thematic Mapper (ETM) images. According to the model, the total soil loss potential of the MKP River Basin from erosion by water was 11,296,063 Mg year(-1) with an average soil loss of 11.2 Mg year(-1). The RUSLE produces only local erosion values and cannot be used to estimate the sediment yield for a watershed. To estimate the sediment yield, sediment-delivery ratio equations were used and compared with the sediment-monitoring reports of the Dolluk stream gauging station on the MKP River, which collected data for >41 years (1964-2005). This station observes the overall efficiency of the sediment yield coming from the Orhaneli and Emet Rivers. The measured sediment in the Emet and Orhaneli sub-basins is 1,082,010 Mg year(-1) and was estimated to be 1,640,947 Mg year(-1) for the same two sub-basins. The measured sediment yield of the gauge station is 127.6 Mg km(-2) year(-1) but was estimated to be 170.2 Mg km(-2) year(-1). The close match between the sediment amounts estimated using the RUSLE-geographic information system (GIS) combination and the measured values from the Dolluk sediment gauge station shows that the potential soil erosion risk of the MKP River Basin can be estimated correctly and reliably using the RUSLE function generated in a GIS environment.

Microbial community structure and diversity in the soil spatial profile of 5-year-old Robinia pseudoacacia 'Idaho,' determined by 454 sequencing of the 16S RNA gene.

PubMed

Chang, Yanping; Bu, Xiangpan; Niu, Weibo; Xiu, Yu; Wang, Huafang

2013-01-01

Relatively little information is available regarding the variability of microbial communities inhabiting deeper soil layers. We investigated the distribution of soil microbial communities down to 1.2 m in 5-year-old Robinia pseudoacacia 'Idaho' soil by 454 sequencing of the 16S RNA gene. The average number of sequences per sample was 12,802. The Shannon and Chao 1 indices revealed various relative microbial abundances and even distribution of microbial diversity for all evaluated sample depths. The predicted diversity in the topsoil exceeded that of the corresponding subsoil. The changes in the relative abundance of the major soil bacterial phyla showed decreasing, increasing, or no consistent trends with respect to sampling depth. Despite their novelty, members of the new candidate phyla OD1 and TM7 were widespread. Environmental variables affecting the bacterial community within the environment appeared to differ from those reported previously, especially the lack of detectable effect from pH. Overall, we found that the overall relative abundance fluctuated with the physical and chemical properties of the soil, root system, and sampling depth. Such information may facilitate forest soil management.

Machine-assisted analysis of Landsat data in the study of crop-soils relationships

USGS Publications Warehouse

Draeger, William C.

1976-01-01

To date, relatively few studies have dealt with crop-soil interactions as they affect the appearance of agricultural areas on Landsat imagery, and hence crop and soil classification or the analysis of agricultural land use.The Image 100, a computer-based data analysis system which allows an interpreter to interact directly and rapidly with Landsat computer compatible tape data, provided a tool to assist in the evaluation of the extent and significance of these interactions. Used with timely and accurate ground data, the system made possible a determination of the variability in crop spectral appearance, from soil type to soil type, as recorded on Landsat data. Information was provided in the form of spectral distribution histrograms for each crop-soil class on each Landsat band. Several crop categories in a test area in  rookings County, South Dakota, were classified using training fields that were selected to be representative of each major crop-soil class. Accuracies in each case, on a total acreage basis, were greater than 90 percent.

Selected Aspects of Soil Science History in the USA - 1980s to the 2010s

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Homburg, Jeffrey A.; Miller, Bradley A.; Fenton, Thomas E.; Doolittle, James A.; Indorante, Samuel J.

2017-04-01

The beginning of the 20th century through the 1970s were good times for soil science in the USA, with relatively strong funding and overall growth in the profession. However, the soil science discipline in the USA hit hard times in the 1980s and 1990s. Federal funding for soil survey work began to decline as did student numbers in university programs and membership in the Soil Science Society of America (SSSA). Despite this, there were still many positive advances within soil science in the USA during these two decades. There was an increased use of geophysical instrumentation, remote sensing, geographic information systems (GIS), and global positioning systems (GPS), and research began in digital soil mapping, all of which lead to better understanding of the spatial distribution and variability of soils. Many NRCS soil products were put online, making them widely available to the general public, and the use of soil knowledge was expanded into new areas such as archaeology and environmental work, and historic connections to geology were re-established. While expansion into new areas required soil science to evolve as a field, separating the discipline to an extent from its agricultural roots, it also helped reinvigorate the discipline. As we move through the early parts of the 21st century, student numbers are increasing in university soil science programs and membership in SSSA is at an all-time high. Digital soil mapping is being incorporated into the National Cooperative Soil Survey, and the impact of humans on the soil system is being fully recognized. The importance of soils is being recognized by events such as the United Nations declaration of 2015 as the "International Year of Soils". The expansion of soils into new areas and widening recognition of the importance of soils gives the field hope for a bright future in the USA.

Remote sensing and GIS based information system for sustainable resources planning at Panchayat level

NASA Astrophysics Data System (ADS)

Velmurugan, A.; Bhatt, S.; Dadhwal, V. K.

2006-12-01

Spatial databases of natural resources are very much essential to ensure enhanced productivity by conserving soil and water and to maintain ecological integrity of any region. Integration of various thematic layers prepared from high resolution data and detailed field survey would be preferred for grass root level planning (Panchayat) aimed to realize the potential of production system on a sustained basis. In this study, a detailed spatial data base was created for part of Kasaragod dist., Kerala, India. Detailed soil survey was carried out using cadastral map and registered over high resolution satellite data (IRS LISS-IV) which helped to identify problems and potentials of the area. Nearly 600 ha of land were found to be at higher erosion risk category out of ten soil series identified in the study area. Remote sensing data was used to prepare land use/land cover map and coconut (53%) followed by mixed vegetation type (16%) were found to be dominant. Soil site suitability assessment for major crops of the area was carried out and crossed with present land use to get the mismatch in land use/land utilization type. Alternate land use plan was prepared considering the potentials and problems of various available resources. Decision Support System (DSS) along with user interface is developed to support decision and extract relevant information. As organic carbon is one of the most important indicators of soil fertility C stock in the present and proposed land use was also estimated to understand the environmental significance.

Stages of weathering mantle formation from carbonate rocks in the light of rare earth elements (REE) and Sr-Nd-Pb isotopes

NASA Astrophysics Data System (ADS)

Hissler, Christophe; Stille, Peter

2015-04-01

Weathering mantles are widespread and include lateritic, sandy and kaolinite-rich saprolites and residuals of partially dissolved rocks. These old regolith systems have a complex history of formation and may present a polycyclic evolution due to successive geological and pedogenetic processes that affected the profile. Until now, only few studies highlighted the unusual high content of associated trace elements in weathering mantles originating from carbonate rocks, which have been poorly studied, compared to those developing on magmatic bedrocks. For instance, these enrichments can be up to five times the content of the underlying carbonate rocks. However, these studies also showed that the carbonate bedrock content only partially explains the soil enrichment for all the considered major and trace elements. Up to now, neither soil, nor saprolite formation has to our knowledge been geochemically elucidated. Therefore, the aim of this study was to examine more closely the soil forming dynamics and the relationship of the chemical soil composition to potential sources. REE distribution patterns and Sr-Nd-Pb isotope ratios have been used because they are particularly well suited to identify trace element migration, to recognize origin and mixing processes and, in addition, to decipher possible anthropogenic and/or "natural" atmosphere-derived contributions to the soil. Moreover, leaching experiments have been applied to identify mobile phases in the soil system and to yield information on the stability of trace elements and especially on their behaviour in these Fe-enriched carbonate systems. All these geochemical informations indicate that the cambisol developing on such a typical weathering mantle ("terra fusca") has been formed through weathering of a condensed Bajocian limestone-marl facies. This facies shows compared to average world carbonates important trace element enrichments. Their trace element distribution patterns are similar to those of the soil suggesting their close genetic relationships. Sr-Nd-Pb isotope data allow to identify four principal components in the soil: a silicate-rich pool at close to the surface, a leachable REE enriched pool at the bottom of the soil profile, the limestone facies on which the weathering profile developed and an anthropogenic, atmosphere-derived component detected in the soil leachates of the uppermost soil horizon. The leachable phases are mainly secondary carbonate-bearing REE phases such as bastnaesite. The isotope data and trace element distribution patterns indicate that at least four geological and environmental events impacted the chemical and isotopical compositions of the soil system since the Cretaceous.

Development of Rhizo-Columns for Nondestructive Root System Architecture Laboratory Measurements

NASA Astrophysics Data System (ADS)

Oostrom, M.; Johnson, T. J.; Varga, T.; Hess, N. J.; Wietsma, T. W.

2016-12-01

Numerical models for root water uptake in plant-soil systems have been developing rapidly, increasing the demand for laboratory experimental data to test and verify these models. Most of the increasingly detailed models are either compared to long-term field crop data or do not involve comparisons at all. Ideally, experiments would provide information on dynamic root system architecture (RSA) in combination with soil-pant hydraulics such as water pressures and volumetric water contents. Data obtained from emerging methods such as Spectral Induced Polarization (SIP) and x-ray computed tomography (x-ray CT) may be used to provide laboratory RSA data needed for model comparisons. Point measurements such as polymer tensiometers (PT) may provide soil moisture information over a large range of water pressures, from field capacity to the wilting point under drought conditions. In the presentation, we demonstrate a novel laboratory capability allowing for detailed RSA studies in large columns under controlled conditions using automated SIP, X-ray CT, and PT methods. Examples are shown for pea and corn root development under various moisture regimes.

Case studies: Soil mapping using multiple methods

NASA Astrophysics Data System (ADS)

Petersen, Hauke; Wunderlich, Tina; Hagrey, Said A. Al; Rabbel, Wolfgang; Stümpel, Harald

2010-05-01

Soil is a non-renewable resource with fundamental functions like filtering (e.g. water), storing (e.g. carbon), transforming (e.g. nutrients) and buffering (e.g. contamination). Degradation of soils is meanwhile not only to scientists a well known fact, also decision makers in politics have accepted this as a serious problem for several environmental aspects. National and international authorities have already worked out preservation and restoration strategies for soil degradation, though it is still work of active research how to put these strategies into real practice. But common to all strategies the description of soil state and dynamics is required as a base step. This includes collecting information from soils with methods ranging from direct soil sampling to remote applications. In an intermediate scale mobile geophysical methods are applied with the advantage of fast working progress but disadvantage of site specific calibration and interpretation issues. In the framework of the iSOIL project we present here some case studies for soil mapping performed using multiple geophysical methods. We will present examples of combined field measurements with EMI-, GPR-, magnetic and gammaspectrometric techniques carried out with the mobile multi-sensor-system of Kiel University (GER). Depending on soil type and actual environmental conditions, different methods show a different quality of information. With application of diverse methods we want to figure out, which methods or combination of methods will give the most reliable information concerning soil state and properties. To investigate the influence of varying material we performed mapping campaigns on field sites with sandy, loamy and loessy soils. Classification of measured or derived attributes show not only the lateral variability but also gives hints to a variation in the vertical distribution of soil material. For all soils of course soil water content can be a critical factor concerning a succesful application of geophysical methods, e.g. GPR on wet loessy soils will result in a high attenuation of signals. Furthermore, with this knowledge we support the development of geophysical pedo-transfer-functions, i.e. the link between geophysical to soil parameters, which is active researched in another work package of the iSOIL project. Acknowledgement: iSOIL-Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission within the RTD activities of the FP7 Thematic Priority Environment.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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.

An improved Rosetta pedotransfer function and evaluation in earth system models

NASA Astrophysics Data System (ADS)

Zhang, Y.; Schaap, M. G.

2017-12-01

Soil hydraulic parameters are often difficult and expensive to measure, leading to the pedotransfer functions (PTFs) an alternative to predict those parameters. Rosetta (Schaap et al., 2001, denoted as Rosetta1) are widely used PTFs, which is based on artificial neural network (ANN) analysis coupled with the bootstrap re-sampling method, allowing the estimation of van Genuchten water retention parameters (van Genuchten, 1980, abbreviated here as VG), saturated hydraulic conductivity (Ks), as well as their uncertainties. We present an improved hierarchical pedotransfer functions (Rosetta3) that unify the VG water retention and Ks submodels into one, thus allowing the estimation of uni-variate and bi-variate probability distributions of estimated parameters. Results show that the estimation bias of moisture content was reduced significantly. Rosetta1 and Posetta3 were implemented in the python programming language, and the source code are available online. Based on different soil water retention equations, there are diverse PTFs used in different disciplines of earth system modelings. PTFs based on Campbell [1974] or Clapp and Hornberger [1978] are frequently used in land surface models and general circulation models, while van Genuchten [1980] based PTFs are more widely used in hydrology and soil sciences. We use an independent global scale soil database to evaluate the performance of diverse PTFs used in different disciplines of earth system modelings. PTFs are evaluated based on different soil characteristics and environmental characteristics, such as soil textural data, soil organic carbon, soil pH, as well as precipitation and soil temperature. This analysis provides more quantitative estimation error information for PTF predictions in different disciplines of earth system modelings.

Building a functional, integrated GIS/remote sensing resource analysis and planning system. [Utah

NASA Technical Reports Server (NTRS)

Ridd, M. K.; Wheeler, D. J.

1985-01-01

To be an effective tool for resource analysis and planning, a geographic information system (GIS) needs to be integrated with a digital remote sensing capability. To be truly functional, the paired system must be driven by grass roots local needs. A case study couched in a Soil Conservation District in northern Utah is presented. Agency representatives determined that the most fundamental data sets to be entered into the GIS system analysis system in the first round were: land use/land cover; geomorphic/soil unit data; hydrologic unit data; and digital terrain. The least expensive and best ways to obtain these data were determined. Data were acquired and formatted to enter the state's PRIME/ARC-INFO GIS, and are being interrogated for resource management decisions related to such issues as agricultural preservation, urban expansion, soil erosion control, and dam siting.

Risk of Leaching in Soils Amended by Compost and Digestate from Municipal Solid Waste

PubMed Central

Tarquis, Ana M.; Cartagena, M. Carmen

2014-01-01

New European directives have proposed the direct application of compost and digestate produced from municipal solid wastes as organic matter sources in agricultural soils. Therefore information about phosphorus leaching from these residues when they are applied to the soil is increasingly important. Leaching experiments were conducted to determine the P mobility in compost and digestate mixtures, supplying equivalent amounts to 100 kg P ha−1 to three different types of soils. The tests were performed in accordance with CEN/TS 14405:2004 analyzing the maximum dissolved reactive P and the kinetic rate in the leachate. P biowaste fractionation indicated that digestate has a higher level of available P than compost has. In contrast, P losses in leaching experiments with soil-compost mixtures were higher than in soil-digestate mixtures. For both wastes, there was no correlation between dissolved reactive P lost and the water soluble P. The interaction between soil and biowaste, the long experimentation time, and the volume of leachate obtained caused the waste's wettability to become an influential parameter in P leaching behavior. The overall conclusion is that kinetic data analysis provides valuable information concerning the sorption mechanism that can be used for predicting the large-scale behavior of soil systems. PMID:25003139

Crop classification using multidate/multifrequency radar data. [Colby, Kansas

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Shanmugam, K. S.; Narayanan, V.; Dobson, C.

1981-01-01

Both C- and L-band radar data acquired over a test site near Colby, Kansas during the summer of 1978 were used to identify three types of vegetation cover and bare soil. The effects of frequency, polarization, and the look angle on the overall accuracy of recognizing the four types of ground cover were analyzed. In addition, multidate data were used to study the improvement in recognition accuracy possible with the addition of temporal information. The soil moisture conditions had changed considerably during the temporal sequence of the data; hence, the effects of soil moisture on the ability to discriminate between cover types were also analyzed. The results provide useful information needed for selecting the parameters of a radar system for monitoring crops.

Hydropodelogy From the Pedon to the Landscape: Challenges and Accomplishments in the National Cooperative Soil Survey

NASA Astrophysics Data System (ADS)

Hammer, D.; Richardson, J.; Hempel, J.; Market, P.

2005-12-01

American pedology has focused on the National Cooperative Soil Survey. Primary responsibility rests with the U.S. Department of Agriculture. The primary goals, are legislatively mandated, are to map the country's soils, make interpretations, provide information to clients, maintain and market the soil survey. The first goal is near completion and focus is shifting to the other three. Concomitantly, American pedological science is being impacted by several conditions: technological advances; land use changes at unprecedented scales and magnitudes; a burgeoning population increasingly "separated" from the land; and a major emphasis in universities upon biological ("life") sciences at the DNA scale - as if soil, nutrients and water are not life essentials. Effects of the Flood of 1993 and Hurricane Katrina suggest that humans do not understand earth/climate interactions, particularly climatic extremes. Pedologists know the focus on soil classification and mapping was at the expense of understanding processes. Hydropedology is a holistic approach to understanding soil and geomorphic process in order to predict the impacts of perturbations. Water movement on and in the soil is the primary mechanism of distributing and altering sediments and chemicals (pedogenesis), and depends for its success upon understanding that the soil profile is the record of developmental history at that landscape site. Hydropedologists believe soil scientists can use pedons (point data) from appropriate locations from flownets in complex landscapes to extrapolate processes. This is the "pedotransfer function" concept. Technological advances are coupled with the existing soil survey information to create important soil-landscape interpretations at a variety of scales. Early results have been very successful. Quantification of soil systems can be classified broadly into three categories; hard data, soft data and tacit knowledge. "Hard data" are measured numbers, and include such attributes as pH, texture, cation exchange capacity and event-specific rainfall. "Soft data" include soil maps, SSURGO data and climate maps. Soft data are combinations of observations, measurements and inferences that produce maps and models at various scales. "Tacit knowledge" is human understanding that results from focused experience within a system. A skilled soil scientist with tacit knowledge specific to a particular region can combination hard and soft data to develop important and useful interpretations and predictions. Illustrations from natural and urban settings will be provided. Soils and climate are temporally and spatially variable at all scales. Soil systems respond differently to different climates and perturbations. For example, the recent pluvial period in the Prairie Pothole region is changing surface soil sodium concentrations and locations and sizes of discharge wetlands. This is a relatively short-term response to a regional climate shift. Climatic shift in Oxisol landscapes will have little effect on soil cations. To optimize soil interpretations, focus must be on quantifying region-specific "dynamic" soil, geomorphic and climatic attributes. Recognizing these needs, the National Cooperative Soil Survey will develop regional watershed projects that focus on quantifying soil-water relationships that can be used at a variety of scales.

A Biophysical Modeling Framework for Assessing the Environmental Impact of Biofuel Production

NASA Astrophysics Data System (ADS)

Zhang, X.; Izaurradle, C.; Manowitz, D.; West, T. O.; Post, W. M.; Thomson, A. M.; Nichols, J.; Bandaru, V.; Williams, J. R.

2009-12-01

Long-term sustainability of a biofuel economy necessitates environmentally friendly biofuel production systems. We describe a biophysical modeling framework developed to understand and quantify the environmental value and impact (e.g. water balance, nutrients balance, carbon balance, and soil quality) of different biomass cropping systems. This modeling framework consists of three major components: 1) a Geographic Information System (GIS) based data processing system, 2) a spatially-explicit biophysical modeling approach, and 3) a user friendly information distribution system. First, we developed a GIS to manage the large amount of geospatial data (e.g. climate, land use, soil, and hydrograhy) and extract input information for the biophysical model. Second, the Environmental Policy Integrated Climate (EPIC) biophysical model is used to predict the impact of various cropping systems and management intensities on productivity, water balance, and biogeochemical variables. Finally, a geo-database is developed to distribute the results of ecosystem service variables (e.g. net primary productivity, soil carbon balance, soil erosion, nitrogen and phosphorus losses, and N2O fluxes) simulated by EPIC for each spatial modeling unit online using PostgreSQL. We applied this framework in a Regional Intensive Management Area (RIMA) of 9 counties in Michigan. A total of 4,833 spatial units with relatively homogeneous biophysical properties were derived using SSURGO, Crop Data Layer, County, and 10-digit watershed boundaries. For each unit, EPIC was executed from 1980 to 2003 under 54 cropping scenarios (eg. corn, switchgrass, and hybrid poplar). The simulation results were compared with historical crop yields from USDA NASS. Spatial mapping of the results show high variability among different cropping scenarios in terms of the simulated ecosystem services variables. Overall, the framework developed in this study enables the incorporation of environmental factors into economic and life-cycle analysis in order to optimize biomass cropping production scenarios.

The framework of a UAS-aided flash flood modeling system for coastal regions

NASA Astrophysics Data System (ADS)

Zhang, H.; Xu, H.

2016-02-01

Flash floods cause severe economic damage and are one of the leading causes of fatalities connected with natural disasters in the Gulf Coast region. Current flash flood modeling systems rely on empirical hydrological models driven by precipitation estimates only. Although precipitation is the driving factor for flash floods, soil moisture, urban drainage system and impervious surface have been recognized to have significant impacts on the development of flash floods. We propose a new flash flooding modeling system that integrates 3-D hydrological simulation with satellite and multi-UAS observations. It will have three advantages over existing modeling systems. First, it will incorporate 1-km soil moisture data through integrating satellite images from European SMOS mission and NASA's SMAP mission. The utilization of high-resolution satellite images will provide essential information to determine antecedent soil moisture condition, which is an essential control on flood generation. Second, this system is able to adjust flood forecasting based on real-time inundation information collected by multi-UAS. A group of UAS will be deployed during storm events to capture the changing extent of flooded areas and water depth at multiple critical locations simultaneously. Such information will be transmitted to a hydrological model to validate and improve flood simulation. Third, the backbone of this system is a state-of-the-art 3-D hydrological model that assimilates the hydrological information from satellites and multi-UAS. The model is able to address surface water-groundwater interactions and reflect the effects of various infrastructures. Using Web-GIS technologies, the modeling results will be available online as interactive flood maps accessible to the public. To support the development and verification of this modeling system, surface and subsurface hydrological observations will be conducted in a number of small watersheds in the Coastal Bend region. We envision this system will provide an innovative means to benefit the forecasting, evaluation and mitigation of flash floods in costal regions.

Erosion Losses of Soils on Arable Land in the European part of Russia

NASA Astrophysics Data System (ADS)

Maltsev, K. A.; Yermolaev, O. P.

2018-01-01

The quantitative assessment of potential soil losses in arable lands of the European part of Russia is carried out in the article. The assessment was carried out using a mathematical model based on the mathematical dependencies of the universal soil loss equation and the mathematical dependencies of the State Hydrological Institute of Russia. Assessment of potential soil losses was performed using calculations in a geographic information system. To perform the calculations the database was created containing information on: the relief; properties of soils; climate and land use. The raster model of data organization was used to create the database and subsequent calculations. The assessment shows that the average amount of soil loss in the plowed land of the European territory of Russia is 11 t/ha per year. At the same time, about half of the territories are located in conditions where the soil loss value does not exceed 0.5 t/ha per year. The potential loss of soil taking into account the soil protection role of vegetation is 3.3 tons/ha per year. In addition, a spatial analysis of the distribution of soil loss by landscape zones shows that there is a consistent reduction in the potential loss of soil from the forest zone (20.92 t/ha per year) to the forest-steppe (10.84 t / ha per year), steppe (8.13 t/ha per year) and semi-desert (4.7 tons/ha per year) zone.

[Classification of Priority Area for Soil Environmental Protection Around Water Sources: Method Proposed and Case Demonstration].

PubMed

Li, Lei; Wang, Tie-yu; Wang, Xiaojun; Xiao, Rong-bo; Li, Qi-feng; Peng, Chi; Han, Cun-liang

2016-04-15

Based on comprehensive consideration of soil environmental quality, pollution status of river, environmental vulnerability and the stress of pollution sources, a technical method was established for classification of priority area of soil environmental protection around the river-style water sources. Shunde channel as an important drinking water sources of Foshan City, Guangdong province, was studied as a case, of which the classification evaluation system was set up. In detail, several evaluation factors were selected according to the local conditions of nature, society and economy, including the pollution degree of heavy metals in soil and sediment, soil characteristics, groundwater sensitivity, vegetation coverage, the type and location of pollution sources. Data information was mainly obtained by means of field survey, sampling analysis, and remote sensing interpretation. Afterwards, Analytical Hierarchy Process (AHP) was adopted to decide the weight of each factor. The basic spatial data layers were set up respectively and overlaid based on the weighted summation assessment model in Geographical Information System (GIS), resulting in a classification map of soil environmental protection level in priority area of Shunde channel. Accordingly, the area was classified to three levels named as polluted zone, risky zone and safe zone, which respectively accounted for 6.37%, 60.90% and 32.73% of the whole study area. Polluted zone and risky zone were mainly distributed in Lecong, Longjiang and Leliu towns, with pollutants mainly resulted from the long-term development of aquaculture and the industries containing furniture, plastic constructional materials and textile and clothing. In accordance with the main pollution sources of soil, targeted and differentiated strategies were put forward. The newly established evaluation method could be referenced for the protection and sustainable utilization of soil environment around the water sources.

Digital spatial soil and land information for agriculture development

NASA Astrophysics Data System (ADS)

Sharma, R. K.; Laghathe, Pankaj; Meena, Ranglal; Barman, Alok Kumar; Das, Satyendra Nath

2006-12-01

Natural resource management calls for study of natural system prevailing in the country. In India floods and droughts visit regularly, causing extensive damages of natural wealth including agriculture that are crucial for sustenance of economic growth. The Indian Sub-continent drained by many major rivers and their tributaries where watershed, the hydrological unit forms a natural system that allows management and development of land resources following natural harmony. Acquisition of various kinds and levels of soil and land characteristics using both conventional and remote sensing techniques and subsequent development of digital spatial data base are essential to evolve strategy for planning watershed development programmes, their monitoring and impact evaluation. The multi-temporal capability of remote sensing sensors helps to update the existing data base which are of dynamic in nature. The paper outlines the concept of spatial data base development, generation using remote sensing techniques, designing of data structure, standardization and integration with watershed layers and various non spatial attribute data for various applications covering watershed development planning, alternate land use planning, soil and water conservation, diversified agriculture practices, generation of soil health card, soil and land reclamation, etc. The soil and land characteristics are vital to derive various interpretative groupings or master table that helps to generate the desired level of information of various clients using the GIS platform. The digital spatial data base on soils and watersheds generated by All India Soil and Land Use Survey will act as a sub-server of the main GIS based Web Server being hoisted by the planning commission for application of spatial data for planning purposes under G2G domain. It will facilitate e-governance for natural resource management using modern technology.

A GIS-based estimation of soil erosion parameters for soil loss potential and erosion hazard in the city of Kinshasa, the Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Tshikeba Kabantu, Martin; Muamba Tshimanga, Raphael; Onema Kileshye, Jean Marie; Gumindoga, Webster; Tshimpampa Beya, Jules

2018-05-01

Soil erosion has detrimental impacts on socio economic life, thus increasing poverty. This situation is aggravated by poor planning and lack of infrastructure especially in developing countries. In these countries, efforts to planning are challenged by lack of data. Alternative approaches that use remote sensing and geographical information systems are therefore needed to provide decision makers with the so much needed information for planning purposes. This helps to curb the detrimental impacts of soil erosion, mostly emanating from varied land use conditions. This study was carried out in the city of Kinshasa, the Democratic Republic of Congo with the aim of using alternative sources of data, based on earth observation resources, to determine the spatial distribution of soil loss and erosion hazard in the city of Kinshasa. A combined approach based on remote sensing skills and rational equation of soil erosion estimation was used. Soil erosion factors, including rainfall-runoff erosivity R), soil erodibility (K), slope steepness and length (SL), crop/vegetation and management (C) were calculated for the city of Kinshasa. Results show that soil loss in Kinshasa ranges from 0 to 20 t ha-1 yr-1. Most of the south part of the urban area were prone to erosion. From the total area of Kinshasa (996 500 ha), 25 013 ha (2.3 %) is of very high ( > 15 t ha-1 yr-1) risk of soil erosion. Urban areas consist of 4.3 % of the area with very high ( > 15 t ha-1 yr-1) risk of soil erosion compared to a very high risk of 2.3 % ( > 15 t ha-1 yr-1) in the rural area. The study shows that the soil loss in the study area is mostly driven by slope, elevation, and informal settlements.

Enhancing the USDA Global Crop Assessment Decision Support System Using SMAP Soil Moisture Data

NASA Astrophysics Data System (ADS)

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

2016-12-01

The Foreign Agricultural Services (FAS) is a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected crop supply and demand estimates. Knowledge of the amount of water in the root zone is an essential source of information for the crop analysts as it governs the crop development and crop growth, which in turn determine the end-of-season yields. USDA FAS currently relies on root zone soil moisture (RZSM) estimates generated using the modified two-layer Palmer Model (PM). PM is a simple water-balance hydrologic model that is driven by daily precipitation observations and minimum and maximum temperature data. These forcing data are based on ground meteorological station measurements from the World Meteorological Organization (WMO), and gridded weather data from the former U.S. Air Force Weather Agency (AFWA), currently called U.S. Air Force 557th Weather Wing. The PM was extended by adding a data assimilation (DA) unit that provides the opportunity to routinely ingest satellite-based soil moisture observations. This allows us to adjust for precipitation-related inaccuracies and enhance the quality of the PM soil moisture estimates. The current operational DA system is based on a 1-D Ensample Kalman Filter approach and relies on observations obtained from the Soil Moisture Ocean Salinity Mission (SMOS). Our talk will demonstrate the value of assimilating two satellite products (i.e. a passive and active) and discuss work that is done in preparation for ingesting soil moisture observations from the Soil Moisture Active Passive (SMAP) mission.

Data Assimilation to Extract Soil Moisture Information From SMAP Observations

NASA Technical Reports Server (NTRS)

Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.

2017-01-01

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, they can be used to reduce the need for localized bias correction techniques typically implemented in data assimilation (DA) systems that tend to remove some of the independent information provided by satellite observations. Here, we use a statistical neural network (NN) algorithm to retrieve SMAP (Soil Moisture Active Passive) surface soil moisture estimates in the climatology of the NASA Catchment land surface model. Assimilating these estimates without additional bias correction is found to significantly reduce the model error and increase the temporal correlation against SMAP CalVal in situ observations over the contiguous United States. A comparison with assimilation experiments using traditional bias correction techniques shows that the NN approach better retains the independent information provided by the SMAP observations and thus leads to larger model skill improvements during the assimilation. A comparison with the SMAP Level 4 product shows that the NN approach is able to provide comparable skill improvements and thus represents a viable assimilation approach.

Oxygen isotopes and P cycle in the soil/plant system: where are we heading?

NASA Astrophysics Data System (ADS)

Tamburini, Federica; Pfahler, Verena; von Sperber, Christian; Bernasconi, Stefano; Frossard, Emmanuel

2014-05-01

Phosphorus (P) is a major nutrient for all living organisms. In the terrestrial environment, P is a double-edged sword. For this reason, a better understanding of P cycling in the soil/plant system and the processes influencing its transfers and transformations is needed to provide agricultural and environmental managers with better concepts for P use. In fact, whereas the effect of abiotic reactions on the P concentration in the soil solution are well understood, we still know too little about the forms of soil organic P, and about the importance of soil biological processes (e.g. on organic matter mineralization-immobilization, or on the role of microorganisms) in controlling P availability. Together with more traditional and routine analysis for P, in the last 20 years researchers have started using the ratio of stable oxygen isotopes in phosphate (δ18O-P) to investigate P cycle in the soil/plant system. The scientific community interested in using this isotopic tracer is expanding because δ18O-P has proven to provide important information on biological processes. A large part of the published studies has shown how δ18O-P can be used to track P in the environment, providing information on P transfer from one pool and/or sink to the other. The other part has used this tool as a tracer of biological activity, clarifying how P is cycled through the microbial biomass or by plants. Together with a short review of the most relevant published results, we will discuss whether, and under which conditions, the δ18O-P can be applied to study P cycling and transformations from the process to the ecosystem level.

A comparison between probability and information measures of uncertainty in a simulated soil map and the economic value of imperfect soil information.

NASA Astrophysics Data System (ADS)

Lark, R. Murray

2014-05-01

Conventionally the uncertainty of a conventional soil map has been expressed in terms of the mean purity of its map units: the probability that the soil profile class examined at a site would be found to correspond to the eponymous class of the simple map unit that is delineated there (Burrough et al, 1971). This measure of uncertainty has an intuitive meaning and is used for quality control in soil survey contracts (Western, 1978). However, it may be of limited value to the manager or policy maker who wants to decide whether the map provides a basis for decision making, and whether the cost of producing a better map would be justified. In this study I extend a published analysis of the economic implications of uncertainty in a soil map (Giasson et al., 2000). A decision analysis was developed to assess the economic value of imperfect soil map information for agricultural land use planning. Random error matrices for the soil map units were then generated, subject to constraints which ensure consistency with fixed frequencies of the different soil classes. For each error matrix the mean map unit purity was computed, and the value of the implied imperfect soil information was computed by the decision analysis. An alternative measure of the uncertainty in a soil map was considered. This is the mean soil map information which is the difference between the information content of a soil observation, at a random location in the region, and the information content of a soil observation given that the map unit is known. I examined the relationship between the value of imperfect soil information and the purity and information measures of map uncertainty. In both cases there was considerable variation in the economic value of possible maps with fixed values of the uncertainty measure. However, the correlation was somewhat stronger with the information measure, and there was a clear upper bound on the value of an imperfect soil map when the mean information takes some particular value. This suggests that the information measure may be a useful one for general communication of the value of soil and similar thematic data. Burrough, P.A., Beckett, P.H.T., Jarvis, M.G., 1971. The relation between cost and utility in soil survey. J. Soil Sci. 22, 359-394. Giasson, E., van Es, C, van Wambeke, A., Bryant, R.B. 2000. Assessing the economic value of soil information using decision analysis techniques. Soil Science 165, 971-978 Western, S., 1978. Soil survey contracts and quality control. Oxford Univ. Press, Oxford.

Application of GPS Technology to Monitor Traffic Intensity and Soil Impacts in a Forest Harvest Operation

Treesearch

Emily A. Carter; Timothy P. McDonald; John L. Torbert

1999-01-01

A study was initiated in the Winter of 1998 to examine the utility of employing Global Positioning Systems (GPS) to monitor harvest traffic throughout a loblolly pine plantation and utilize traffic intensity information to assess impacts of select soil physical properties. Traffic maps prepared from GPS positional data indicated the highest concentration of traffic...

Effect of soil composition, temperature, indigenous microflora, and environmental conditions on the survival of Escherichia coli O157:H7.

PubMed

Vidovic, Sinisa; Block, Hushton C; Korber, Darren R

2007-07-01

The survival of Escherichia coli O157:H7 in replicate soil microcosms was quantified in 2 types of silty clay loam soil (high carbon and low carbon) under either sterile or nonsterile conditions. Microcosms were held at -21, 4, and 22 degrees C under constant soil moisture content. Differences existed (P < 0.05) in survival of E. coli O157:H7 in low- and high-carbon soil at all temperatures, indicating an important role of soil composition on the survival of this pathogen. The highest death rate of E. coli O157:H7 in sterile soil occurred in the low-carbon soil at 4 degrees C, whereas in nonsterile soil the highest death rate was observed in the low-carbon soil at 22 degrees C. These results suggest that the most lethal effects on E. coli O157:H7 in the sterile system occurred via the synergy of nutrient limitation and cold stress, whereas in the nonsterile system lethality was owing to inhibition by indigenous soil microorganisms and starvation. Results obtained from an in situ field survival experiment demonstrated the apparent sensitivity of E. coli O157:H7 cells to dehydration, information that may be used to reduce environmental spread of this pathogen as well as formulate appropriate waste management strategies.

Role of soil microbial processes in integrated pest management

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

Francis, A.J.

1987-01-01

Soil microorganisms play a significant role in the carbon, nitrogen, phosphorus, and sulfur cycles in nature and are critical to the functioning of ecosystems. Microorganisms affect plant growth directly by regulating the availability of plant nutrients in soil, or indirectly by affecting the population dynamics of plant pathogens in soil. Any adverse effect on soil microorganisms or on the microbial processes will affect the soil fertility, availability of plant nutrients and the overall biogeochemical cycling of elements in nature. Soil microorganisms are responsible for the degradation and detoxification of pesticides; they control many insect pests, nematodes, and other plant pathogenicmore » microorganisms by parasitism, competition, production of antibiotics and other toxic substances. Also, they regulate the availability of major and minor nutrients as well as essential elements. The long-term effects of continuous and, in some instances, excessive application of pesticides on soil fertility is not fully understood. Although much information is available on the integrated pest management (IPM) system, we have very little understanding of the extent of soil microbial processes which modulate the overall effectiveness of various strategies employed in IPM. The purpose of this paper is to review briefly the key microbial processes and their relationship to the IPM system.« less

Measuring Wildfires From Aircraft And Satellites

NASA Technical Reports Server (NTRS)

Brass, J. A.; Arvesen, J. C.; Ambrosia, V. G.; Riggan, P. J.; Meyers, J. S.

1991-01-01

Aircraft and satellite systems yield wide-area views, providing total coverage of affected areas. System developed for use aboard aircraft includes digital scanner that records data in 12 channels. Transmits data to ground station for immediate use in fighting fires. Enables researchers to estimate gaseous and particulate emissions from fires. Provides information on temperatures of flame fronts and soils, intensities and rate of spread of fires, characteristics of fuels and smoke plumes, energy-release rates, and concentrations and movements of trace gases. Data relates to heating and cooling of soils, loss of nutrients, and effects on atmospheric, terrestrial, and aquatic systems.

SUPERFUND TREATABILITY CLEARINGHOUSE: FINAL ...

EPA Pesticide Factsheets

During the period of July 8 - July 12, 1985, the Shirco Infrared Systems Portable Pilot Test Unit was in operation at the Times Beach Dioxin Research Facility to demonstrate the capability of Shirco's infrared technology to decontaminate silty soil laden with 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) at a concentration range of 156 to 306 ppb. Emissions sampling and final analysis was performed by Environmental Research & Technology, Inc. (ERT), while laboratory analysis of the emissions and soil samples was performed by Roy F. Weston Inc. Shirco Infrared Systems prepared the testing procedure protocol and operated the furnace system. publish information

Using Vegetation Maps to Provide Information on Soil Distribution

NASA Astrophysics Data System (ADS)

José Ibáñez, Juan; Pérez-Gómez, Rufino; Brevik, Eric C.; Cerdà, Artemi

2016-04-01

Many different types of maps (geology, hydrology, soil, vegetation, etc.) are created to inventory natural resources. Each of these resources is mapped using a unique set of criteria, including scales and taxonomies. Past research has indicated that comparing the results of different but related maps (e.g., soil and geology maps) may aid in identifying deficiencies in those maps. Therefore, this study was undertaken in the Almería Province (Andalusia, Spain) to (i) compare the underlying map structures of soil and vegetation maps and (ii) to investigate if a vegetation map can provide useful soil information that was not shown on a soil map. To accomplish this soil and vegetation maps were imported into ArcGIS 10.1 for spatial analysis. Results of the spatial analysis were exported to Microsoft Excel worksheets for statistical analyses to evaluate fits to linear and power law regression models. Vegetative units were grouped according to the driving forces that determined their presence or absence (P/A): (i) climatophilous (climate is the only determinant of P/A) (ii); lithologic-climate (climate and parent material determine PNV P/A); and (iii) edaphophylous (soil features determine PNV P/A). The rank abundance plots for both the soil and vegetation maps conformed to Willis or Hollow Curves, meaning the underlying structures of both maps were the same. Edaphophylous map units, which represent 58.5% of the vegetation units in the study area, did not show a good correlation with the soil map. Further investigation revealed that 87% of the edaphohygrophylous units (which demand more soil water than is supplied by other soil types in the surrounding landscape) were found in ramblas, ephemeral riverbeds that are not typically classified and mapped as soils in modern systems, even though they meet the definition of soil given by the most commonly used and most modern soil taxonomic systems. Furthermore, these edaphophylous map units tend to be islands of biodiversity that are threatened by anthropogenic activity in the region. Therefore, this study revealed areas in Almería Province that need to be revisited and studied pedologically. The vegetation mapped in these areas and the soils that support it are key components of the earth's critical zone that must be studied, understood, and preserved.

SWB-A modified Thornthwaite-Mather Soil-Water-Balance code for estimating groundwater recharge

USGS Publications Warehouse

Westenbroek, S.M.; Kelson, V.A.; Dripps, W.R.; Hunt, R.J.; Bradbury, K.R.

2010-01-01

A Soil-Water-Balance (SWB) computer code has been developed to calculate spatial and temporal variations in groundwater recharge. The SWB model calculates recharge by use of commonly available geographic information system (GIS) data layers in combination with tabular climatological data. The code is based on a modified Thornthwaite-Mather soil-water-balance approach, with components of the soil-water balance calculated at a daily timestep. Recharge calculations are made on a rectangular grid of computational elements that may be easily imported into a regional groundwater-flow model. Recharge estimates calculated by the code may be output as daily, monthly, or annual values.

Some Research into Wetting in Natural Systems

NASA Astrophysics Data System (ADS)

Shirtcliffe, Neil; Struck, Alexander; Albiez, Vera; Walker, Shani-Nini

2017-04-01

We have been investigating some natural systems that turn out to have some interesting similarities to soil. Our recent focus has been on the wings of insects, in particular locally available butterfly, dragonfly and damselfly species. These can be shown to repel water highly efficiently under some conditions and to become less repellent or even sticky under others. Although we have not fully characterized the system yet, it shows a time delay similar to that observed on water repellent soils and seems to be related in some ways. We are also beginning to investigate how soils, or more particularly composts behave when electrically stimulated at different frequencies. We hope to be able to extract information about the liquid in the soils from this technique and therefore to be able to rapidly characterize samples. Significant parameters being the liquid fraction and the distribution of particles. This technique typically gives considerably more and more robust data than single frequency or D.C. measurements.

Development of a fiber optic pavement subgrade strain measurement system

NASA Astrophysics Data System (ADS)

Miller, Craig Emerson

2000-11-01

This dissertation describes the development of a fiber optic sensing system to measure strains within the soil subgrade of highway pavements resulting from traffic loads. The motivation to develop such a device include improvements to: (1)all phases of pavement design, (2)theoretical models used to predict pavement performance, and (3)pavement rehabilitation. The design of the sensing system encompasses selecting an appropriate transducer design as well as the development of optimal optical and demodulation systems. The first is spring based, which attempts to match its spring stiffness to that of the soil-data indicate it is not an optimal transducer design. The second transducer implements anchoring plates attached to two telescoping tubes which allows the soil to be compacted to a desired density between the plates to dictate the transducer's behavior. Both transducers include an extrinsic Fabry- Perot cavity to impose the soil strains onto a phase change of the optical signal propagating through the cavity. The optical system includes a low coherence source and allows phase modulation via path length stretching by adding a second interferometer in series with the transducer, resulting in a path matched differential interferometer. A digitally implemented synthetic heterodyne demodulator based on a four step phase stepping algorithm is used to obtain unambiguous soil strain information from the displacement of the Fabry-Perot cavity. The demodulator is calibrated and characterized by illuminating the transducer with a second long coherence source of different wavelength. The transducer using anchoring plates is embedded within cylindrical soil specimens of varying soil types and soil moisture contents. Loads are applied to the specimen and resulting strains are measured using the embedded fiber optic gage and LVDTs attached to the surface of the specimen. This experimental verification is substantiated using a finite element analysis to predict any differences between interior and surface strains in the specimens. The experimental data indicate 2-inch diameter anchoring plates embedded in soil close to its optimum moisture content allow for very accurate soil strain measurements.

Developing SoilML as a global standard for the collation and transfer of soil data and information.

NASA Astrophysics Data System (ADS)

Montanarella, Luca; Wilson, Peter; Cox, Simon; McBratney, Alex; Ahamed, Sonya; McMillan, Bob; Jacquier, David; Fortner, Jim

2010-05-01

There is an increasing need to collect, collate and share soil data and information within countries, across regions and globally. Timely access to consistent and authoritative data and information is critical to issues related to food production, climate change, water management, energy production and biodiversityl. Soil data and information is managed by numerous agencies and organisations using a plethora of processes, scales and standards. A number of national and international activities and projects are currently dealing with the issues associated with collation of disparate data sets. Standards are being developed for data storage, transfer and collation like, for example, in the GobalSoilMap.net project, e-SOTER and the EU Inspire GS-SOIL. Individually these will not provide a single internationally recognised and adopted standard for soil data and information exchange. A recent GlobalSoilMap.net meeting held in Wageningen, The Netherlands, discussed the needs of a harmonized information model for collation of a global 90 metre grid of key soil attributes (organic carbon, soil texture, pH, depth to bedrock/impeding layer, and predictions of bulk density and available water capacity) at six specified depth increments. The meeting considered a number of existing data base implementations (such as ASRIS, NASIS, WISE, SOTER) as well as emerging abstract information models that are being expressed in UML (such as e-SOTER). It examined related information models, such as GeoSciML and the lessons learnt in developing and implementing such community agreed models, features and vocabularies. There is a need to develop a global soil information standard, to be called SoilML, that would allow access and use of data across a broad range of international initiatives (such as GEOSS and INSPIRE) as well as supporting national, regional and local data interoperability and integration. The meeting agreed to adopt the interoperability approaches of formalising the information model in UML with XML encoding for data transfer as well as re-using existing features and patterns where appropriate such as those found in GeoSciML and Observations and Measurements. It has been proposed to establish a formal Working Group on Soil Information Standards under the International Union of Soil Science to give the SoilML information model both scientific credibility and international standing. A number of meetings and workshops are being planned to progress the draft SoilML information model

Greenhouse irrigation control system design based on ZigBee and fuzzy PID technology

NASA Astrophysics Data System (ADS)

Zhou, Bing; Yang, Qiliang; Liu, Kenan; Li, Peiqing; Zhang, Jing; Wang, Qijian

In order to achieve the water demand information accurately detect of the greenhouse crop and its precision irrigation automatic control, this article has designed a set of the irrigated control system based on ZigBee and fuzzy PID technology, which composed by the soil water potential sensor, CC2530F256 wireless microprocessor, IAR Embedded Workbench software development platform. And the time of Irrigation as the output .while the amount of soil water potential and crop growth cycle as the input. The article depended on Greenhouse-grown Jatropha to verify the object, the results show that the system can irrigate timely and appropriately according to the soil water potential and water demend of the different stages of Jatropha growth , which basically meet the design requirements. Therefore, the system has broad application prospects in the amount of greenhouse crop of fine control irrigation.

Irrigation effects on soil attributes and grapevine performance in a 'Godello' vineyard of NW Spain

NASA Astrophysics Data System (ADS)

Fandiño, María; Trigo-Córdoba, Emiliano; Martínez, Emma M.; Bouzas-Cid, Yolanda; Rey, Benjamín J.; Cancela, Javier J.; Mirás-Avalos, Jose M.

2014-05-01

Irrigation systems are increasingly being used in Galician vineyards. However, a lack of information about irrigation management can cause a bad use of these systems and, consequently, reductions in berry quality and loss of water resources. In this context, experiences with Galician cultivars may provide useful information. A field experiment was carried out over two seasons (2012-2013) on Vitis vinifera (L.) cv. 'Godello' in order to assess the effects of irrigation on soil attributes, grapevine performance and berry composition. The field site was a commercial vineyard located in A Rúa (Ourense-NW Spain). Rain-fed vines (R) were compared with two irrigation systems: surface drip irrigation (DI) and subsurface drip irrigation (SDI). Physical and chemical characteristics of soil were analyzed after installing irrigation systems at the beginning of each season, in order to assess the effects that irrigation might have on soil attributes. Soil water content, leaf and stem water potentials and stomatal conductance were periodically measured over the two seasons. Yield components including number of clusters, yield per plant and cluster average weight were taken. Soluble solids, pH, total acidity and amino acids contents were measured on the grapes at harvest. Pruning weight was also recorded. Soil attributes did not significantly vary due to the irrigation treatments. Stem water potentials were significantly lower for R plants on certain dates through the season, whereas stomatal conductance was similar for the three treatments in 2013, while in 2012 SDI plants showed greater stomatal conductance values. SDI plants yielded more than those R due to both a greater number of clusters per plant and to heavier clusters. Pruning weight was significantly higher in SI plants. Berry composition was similar for the three treatments except for the amino acids content, which was higher under SDI conditions. These results may be helpful for a sustainable management of irrigation in Galician vineyards.

Soil Fertility Evaluation and Land Management of Dryland Farming at Tegallalang Sub-District, Gianyar Regency, Bali, Indonesia

NASA Astrophysics Data System (ADS)

Sardiana, I. K.; Susila, D.; Supadma, A. A.; Saifulloh, M.

2017-12-01

The landuse of Tegallalang Subdistrict is dominated by dryland farming. The practice of cultivation on agricultural dryland that ignores the carrying capacity of the environment can lead to land degradation that makes the land vulnerable to the deterioration of soil fertility. Soil fertility evaluation and land management of dryland farming in Tegallalang Sub-district, Gianyar Regency were aimed at (1) identifying the soil fertility and it’s respective limiting factors, (2) mapping the soil fertility using Geographic Information Systems (GIS) and (3) developing land management for dryland farming in Tegallalang Sub-district. This research implementing explora-tory method which followed by laboratory analysis. Soil samples were taken on each homogene-ous land units which developed by overlay of slope, soil type, and land use maps. The following soil fertility were measured, such as CEC, base saturation, P2O5, K- Total and C-Organic. The values of soil fertility were mapping using QGIS 2.18.7 and refer to land management evaluation. The results showed that the soil fertility in the research area considered high, and low level. The High soil fertility presents on land units at the flat to undulating slope with different land management systems (fertilizer, without fertilizer, soil tillage and without soil tillage). The low soil fertility includes land units that present on steep slope, and without land managements. The limiting factors of soil fertility were texture, C-Organic, CEC, P2O5, and K- total. It was recommended to applying organic fertilizer, Phonska, and dolomite on the farming area.

Can diversity in root architecture explain plant water use efficiency? A modeling study

PubMed Central

Tron, Stefania; Bodner, Gernot; Laio, Francesco; Ridolfi, Luca; Leitner, Daniel

2015-01-01

Drought stress is a dominant constraint to crop production. Breeding crops with adapted root systems for effective uptake of water represents a novel strategy to increase crop drought resistance. Due to complex interaction between root traits and high diversity of hydrological conditions, modeling provides important information for trait based selection. In this work we use a root architecture model combined with a soil-hydrological model to analyze whether there is a root system ideotype of general adaptation to drought or water uptake efficiency of root systems is a function of specific hydrological conditions. This was done by modeling transpiration of 48 root architectures in 16 drought scenarios with distinct soil textures, rainfall distributions, and initial soil moisture availability. We find that the efficiency in water uptake of root architecture is strictly dependent on the hydrological scenario. Even dense and deep root systems are not superior in water uptake under all hydrological scenarios. Our results demonstrate that mere architectural description is insufficient to find root systems of optimum functionality. We find that in environments with sufficient rainfall before the growing season, root depth represents the key trait for the exploration of stored water, especially in fine soils. Root density, instead, especially near the soil surface, becomes the most relevant trait for exploiting soil moisture when plant water supply is mainly provided by rainfall events during the root system development. We therefore concluded that trait based root breeding has to consider root systems with specific adaptation to the hydrology of the target environment. PMID:26412932

Can diversity in root architecture explain plant water use efficiency? A modeling study.

PubMed

Tron, Stefania; Bodner, Gernot; Laio, Francesco; Ridolfi, Luca; Leitner, Daniel

2015-09-24

Drought stress is a dominant constraint to crop production. Breeding crops with adapted root systems for effective uptake of water represents a novel strategy to increase crop drought resistance. Due to complex interaction between root traits and high diversity of hydrological conditions, modeling provides important information for trait based selection. In this work we use a root architecture model combined with a soil-hydrological model to analyze whether there is a root system ideotype of general adaptation to drought or water uptake efficiency of root systems is a function of specific hydrological conditions. This was done by modeling transpiration of 48 root architectures in 16 drought scenarios with distinct soil textures, rainfall distributions, and initial soil moisture availability. We find that the efficiency in water uptake of root architecture is strictly dependent on the hydrological scenario. Even dense and deep root systems are not superior in water uptake under all hydrological scenarios. Our results demonstrate that mere architectural description is insufficient to find root systems of optimum functionality. We find that in environments with sufficient rainfall before the growing season, root depth represents the key trait for the exploration of stored water, especially in fine soils. Root density, instead, especially near the soil surface, becomes the most relevant trait for exploiting soil moisture when plant water supply is mainly provided by rainfall events during the root system development. We therefore concluded that trait based root breeding has to consider root systems with specific adaptation to the hydrology of the target environment.

Hygrothermal Material Properties for Soils in Building Science

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

Kehrer, Manfred; Pallin, Simon B.

2017-01-01

Hygrothermal performance of soils coupled to buildings is complicated because of the dearth of information on soil properties. However they are important when numerical simulation of coupled heat and moisture transport for below-grade building components are performed as their temperature and moisture content has an influence on the durability of the below-grade building component. Soils can be classified by soil texture. According to the Unified Soil Classification System (USCA), 12 different soils can be defined on the basis of three soil components: clay, sand, and silt. This study shows how existing material properties for typical American soils can be transferredmore » and used for the calculation of the coupled heat and moisture transport of building components in contact with soil. Furthermore a thermal validation with field measurements under known boundary conditions is part of this study, too. Field measurements for soil temperature and moisture content for two specified soils are carried out right now under known boundary conditions. As these field measurements are not finished yet, the full hygrothermal validation is still missing« less

Soil organic carbon sequestration and tillage systems in Mediterranean environments

NASA Astrophysics Data System (ADS)

Francaviglia, Rosa; Di Bene, Claudia; Marchetti, Alessandro; Farina, Roberta

2016-04-01

Soil carbon sequestration is of special interest in Mediterranean areas, where rainfed cropping systems are prevalent, inputs of organic matter to soils are low and mostly rely on crop residues, while losses are high due to climatic and anthropic factors such as intensive and non-conservative farming practices. The adoption of reduced or no tillage systems, characterized by a lower soil disturbance in comparison with conventional tillage, has proved to be positively effective on soil organic carbon (SOC) conservation and other physical and chemical processes, parameters or functions, e.g. erosion, compaction, ion retention and exchange, buffering capacity, water retention and aggregate stability. Moreover, soil biological and biochemical processes are usually improved by the reduction of tillage intensity. The work deals with some results available in the scientific literature, and related to field experiment on arable crops performed in Italy, Greece, Morocco and Spain. Data were organized in a dataset containing the main environmental parameters (altitude, temperature, rainfall), soil tillage system information (conventional, minimum and no-tillage), soil parameters (bulk density, pH, particle size distribution and texture), crop type, rotation, management and length of the experiment in years, initial SOCi and final SOCf stocks. Sampling sites are located between 33° 00' and 43° 32' latitude N, 2-860 m a.s.l., with mean annual temperature and rainfall in the range 10.9-19.6° C and 355-900 mm. SOC data, expressed in t C ha-1, have been evaluated both in terms of Carbon Sequestration Rate, given by [(SOCf-SOCi)/length in years], and as percentage change in comparison with the initial value [(SOCf-SOCi)/SOCi*100]. Data variability due to the different environmental, soil and crop management conditions that influence SOC sequestration and losses will be examined.

Global changes in soil stocks of carbon, nitrogen, phosphorus, and sulphur as influenced by long-term agricultural production.

PubMed

Kopittke, Peter M; Dalal, Ram C; Finn, Damien; Menzies, Neal W

2017-06-01

Quantifying changes in stocks of C, N, P, and S in agricultural soils is important not only for managing these soils sustainably as required to feed a growing human population, but for C and N, they are also important for understanding fluxes of greenhouse gases from the soil environment. In a global meta-analysis, 102 studies were examined to investigate changes in soil stocks of organic C, total N, total P, and total S associated with long-term land-use changes. Conversion of native vegetation to cropping resulted in substantial losses of C (-1.6 kg m -2 , -43%), N (-0.15 kg m -2 , -42%), P (-0.029 kg m -2 , -27%), and S (-0.015 kg m -2 , -33%). The subsequent conversion of conventional cropping systems to no-till, organic agriculture, or organic amendment systems subsequently increased stocks, but the magnitude of this increase (average of +0.47 kg m -2 for C and +0.051 kg m -2 for N) was small relative to the initial decrease. We also examined the conversion of native vegetation to pasture, with changes in C (-11%), N (+4.1%), and P (+25%) generally being modest relative to changes caused by conversion to cropping. The C:N ratio remained relatively constant irrespective of changes in land use, whilst in contrast, the C:S ratio decreased by 21% in soils converted to cropping - this suggesting that biochemical mineralization is of importance for S. The data presented here will assist in the assessment of different agricultural production systems on soil stocks of C, N, P, and S - this information assisting not only in quantifying the effects of existing agricultural production on these stocks, but also allowing for informed decision-making regarding the potential effects of future land-use changes. © 2016 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

PubMed Central

Rellán-Álvarez, Rubén; Lobet, Guillaume; Lindner, Heike; Pradier, Pierre-Luc; Sebastian, Jose; Yee, Muh-Ching; Geng, Yu; Trontin, Charlotte; LaRue, Therese; Schrager-Lavelle, Amanda; Haney, Cara H; Nieu, Rita; Maloof, Julin; Vogel, John P; Dinneny, José R

2015-01-01

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes. DOI: http://dx.doi.org/10.7554/eLife.07597.001 PMID:26287479

GLO-Roots: An imaging platform enabling multidimensional characterization of soil-grown root systems

DOE PAGES

Rellan-Alvarez, Ruben; Lobet, Guillaume; Lindner, Heike; ...

2015-08-19

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow themore » spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.« less

Scientific support, soil information and education provided by the Austrian Soil Science Society

NASA Astrophysics Data System (ADS)

Huber, Sigbert; Baumgarten, Andreas; Birli, Barbara; Englisch, Michael; Tulipan, Monika; Zechmeister-Boltenstern, Sophie

2015-04-01

The Austrian Soil Science Society (ASSS), founded in 1954, is a non-profit organisation aiming at furthering all branches of soil science in Austria. The ASSS provides information on the current state of soil research in Austria and abroad. It organizes annual conferences for scientists from soil and related sciences to exchange their recent studies and offers a journal for scientific publications. Annually, ASSS awards the Kubiena Research Prize for excellent scientific studies provided by young scientists. In order to conserve and improve soil science in the field, excursions are organized, also in cooperation with other scientific organisations. Due to well-established contacts with soil scientists and soil science societies in many countries, the ASSS is able to provide its members with information about the most recent developments in the field of soil science. This contributes to a broadening of the current scientific knowledge on soils. The ASSS also co-operates in the organisation of excursions and meetings with neighbouring countries. Several members of the ASSS teach soil science at various Austrian universities. More detail on said conferences, excursions, publications and awards will be given in the presentation. Beside its own scientific journal, published once or twice a year, and special editions such as guidebooks for soil classification, the ASSS runs a website providing information on the Society, its activities, meetings, publications, awards and projects. Together with the Environment Agency Austria the ASSS runs a soil platform on the internet. It is accessible for the public and thus informs society about soil issues. This platform offers a calendar with national and international soil events, contacts of soil related organisations and networks, information on national projects and publications. The society has access to products, information material and information on educational courses. Last but not least information on specific soil themes as well as a photo gallery of the Austrian soil types is available. Selected content from the website and the internet platform will be presented. During the past years the ASSS has perceived a growing need to educate pupils on soil issues and started projects to develop concepts and materials for education. In one project a soil workshop for secondary schools was developed. The workshop comprises four stations which allow the children to see, feel and understand soil by doing simple experiments, looking for soil biota or drawing examples of soil functions. The project was awarded by the Austrian UNESCO Commission as a project of the UN decade of education for sustainable development. In addition to that project an overview of nearly 100 programmes introducing children to the topic of soils in Austria was made available as report on the ASSS website. Results of the project and information on its implementation in schools will be provided.

Orbiting passive microwave sensor simulation applied to soil moisture estimation

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator); Clark, B. V.; Pitchford, W. M.; Paris, J. F.

1979-01-01

A sensor/scene simulation program was developed and used to determine the effects of scene heterogeneity, resolution, frequency, look angle, and surface and temperature relations on the performance of a spaceborne passive microwave system designed to estimate soil water information. The ground scene is based on classified LANDSAT images which provide realistic ground classes, as well as geometries. It was determined that the average sensitivity of antenna temperature to soil moisture improves as the antenna footprint size increased. Also, the precision (or variability) of the sensitivity changes as a function of resolution.

Soil Fumigant Labels - Dazomet

EPA Pesticide Factsheets

Updated labels include new safety requirements for buffer zones and related measures. Find information from the Pesticide Product Labeling System (PPLS) for products such as Basamid G, manufactured by Amvac.

Assessing the Importance of Incorporating Spatial and Temporal Variability of Soil and Plant Parameters into Local Water Balance Models for Precision Agriculture: Investigations within a California Vineyard

NASA Astrophysics Data System (ADS)

Hubbard, S.; Pierce, L.; Grote, K.; Rubin, Y.

2003-12-01

Due Due to the high cash crop nature of premium winegrapes, recent research has focused on developing a better understanding of the factors that influence winegrape spatial and temporal variability. Precision grapevine irrigation schemes require consideration of the factors that regulate vineyard water use such as (1) plant parameters, (2) climatic conditions, and (3) water availability in the soil as a function of soil texture. The inability to sample soil and plant parameters accurately, at a dense enough resolution, and over large enough areas has limited previous investigations focused on understanding the influences of soil water and vegetation on water balance at the local field scale. We have acquired several novel field data sets to describe the small scale (decimeters to a hundred meters) spatial variability of soil and plant parameters within a 4 acre field study site at the Robert Mondavi Winery in Napa County, California. At this site, we investigated the potential of ground penetrating radar data (GPR) for providing estimates of near surface water content. Calibration of grids of 900 MHz GPR groundwave data with conventional soil moisture measurements revealed that the GPR volumetric water content estimation approach was valid to within 1 percent accuracy, and that the data grids provided unparalleled density of soil water content over the field site as a function of season. High-resolution airborne multispectral remote sensing data was also collected at the study site, which was converted to normalized difference vegetation index (NDVI) and correlated to leaf area index (LAI) using plant-based measurements within a parallel study. Meteorological information was available from a weather station of the California Irrigation management Information System, located less than a mile from our study area. The measurements were used within a 2-D Vineyard Soil Irrigation Model (VSIM), which can incorporate the spatially variable, high-resolution soil and plant-based information. VSIM, which is based on the concept that equilibrium exists between climate, soils, and LAI, was used to simulate vine water stress, water use, and irrigation requirements during a single year for the site. Using the simple water-balance model with the dense characterization data, we will discuss: (1) the ability to predict vineyard soil water content at the small scales of soil heterogeneity that are observed in nature at the local-scale, (2) the relative importance of plant, climate, and soil information to predictions of the soil water balance at the site, (3) the influence of crop cover in the water balance predictions.

Soil Management Plan for the Oak Ridge Y-12 National Security Complex Oak Ridge, Tennessee

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

None

2005-03-02

This Soil Management Plan applies to all activities conducted under the auspices of the National Nuclear Security Administration (NNSA) Oak Ridge Y-12 National Security Complex (Y-12) that involve soil disturbance and potential management of waste soil. The plan was prepared under the direction of the Y-12 Environmental Compliance Department of the Environment, Safety, and Health Division. Soil disturbances related to maintenance activities, utility and building construction projects, or demolition projects fall within the purview of the plan. This Soil Management Plan represents an integrated, visually oriented, planning and information resource tool for decision making involving excavation or disturbance of soilmore » at Y-12. This Soil Management Plan addresses three primary elements. (1) Regulatory and programmatic requirements for management of soil based on the location of a soil disturbance project and/or the regulatory classification of any contaminants that may be present (Chap. 2). Five general regulatory or programmatic classifications of soil are recognized to be potentially present at Y-12; soil may fall under one or more these classifications: (a) Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) pursuant to the Oak Ridge Reservation (ORR) Federal Facilities Agreement; (b) Resource Conservation and Recovery Act (RCRA); (c) RCRA 3004(u) solid waste managements units pursuant to the RCRA Hazardous and Solid Waste Amendments Act of 1984 permit for the ORR; (d) Toxic Substances and Control Act-regulated soil containing polychlorinated biphenyls; and (e) Radiologically contaminated soil regulated under the Atomic Energy Act review process. (2) Information for project planners on current and future planned remedial actions (RAs), as prescribed by CERCLA decision documents (including the scope of the actions and remedial goals), land use controls implemented to support or maintain RAs, RCRA post-closure regulatory requirements for former waste management units, legacy contamination source areas and distribution of contamination in soils, and environmental infrastructure (e.g., caps, monitoring systems, etc.) that is in place or planned in association with RAs. (3) Regulatory considerations and processes for management and disposition of waste soil upon generation, including regulatory drivers, best management practices (BMPs), waste determination protocols, waste acceptance criteria, and existing waste management procedures and BMPs for Y-12. This Soil Management Plan provides information to project planners to better coordinate their activities with other organizations and programs with a vested interest in soil disturbance activities at Y-12. The information allows project managers and maintenance personnel to evaluate and anticipate potential contaminant levels that may be present at a proposed soil disturbance site prior to commencement of activities and allows a more accurate assessment of potential waste management requirements.« less

Passive Microwave Remote Sensing of Soil Moisture

NASA Technical Reports Server (NTRS)

Njoku, Eni G.; Entekhabi, Dara

1996-01-01

Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive Microwave soil moisture sensors currently considered for space operation are in the range 10-20 km. The most useful frequency range for soil moisture sensing is 1-5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations.

GIS-technologies application for calculation of potential soil loss of Marha River basin (Republic of Saha)

NASA Astrophysics Data System (ADS)

Shynbergenov, Y.; Maltsev, K.; Sihanova, N.

2018-01-01

In the article the presentation of estimation methods of potential soil loss in the conditions of Siberia with application of geographical information systems is resulted. For the reference area of the Marha river basin, which is a part of the Lena river catchment, there was created a specialized geographic information database of potential soil erosion, with scale of 1: 1,000,000. Digital elevation model “GMTED2010” and the hydroset layer corresponding to the scale of 1: 1,000,000 are taken to calculate the soil loss values. The formation of the geobase data is considered in detail being constructed on the basis of the multiplicative structure which reflects the main parameters of the relief (slope steepness, exposition, slope length, erosion potential of the relief), soil, climatic characteristics and modern types of land cover. At the quantitative level with sufficiently high degree of spatial detail results were obtained for calculating the potential erosion of soils. The average value of potential soil loss in the basin without taking into account the factor of land cover types, was 12.6 t/ha/yr. The calculations carried out, taking into account the types of land cover obtained from remote sensing data from outer space resulted in an appreciable reduction of the soil loss values (0.04 t/ha/yr.).

Collaboration support system for "Phobos-Soil" space mission.

NASA Astrophysics Data System (ADS)

Nazarov, V.; Nazirov, R.; Zakharov, A.

2009-04-01

Rapid development of communication facilities leads growth of interactions done via electronic means. However we can see some paradox in this segment in last times: Extending of communication facilities increases collaboration chaos. And it is very sensitive for space missions in general and scientific space mission particularly because effective decision of this task provides successful realization of the missions and promises increasing the ratio of functional characteristic and cost of mission at all. Resolving of this problem may be found by using respective modern technologies and methods which widely used in different branches and not in the space researches only. Such approaches as Social Networking, Web 2.0 and Enterprise 2.0 look most prospective in this context. The primary goal of the "Phobos-Soil" mission is an investigation of the Phobos which is the Martian moon and particularly its regolith, internal structure, peculiarities of the orbital and proper motion, as well as a number of different scientific measurements and experiments for investigation of the Martian environment. A lot of investigators involved in the mission. Effective collaboration system is key facility for information support of the mission therefore. Further to main goal: communication between users of the system, modern approaches allows using such capabilities as self-organizing community, user generated content, centralized and federative control of the system. Also it may have one unique possibility - knowledge management which is very important for space mission realization. Therefore collaboration support system for "Phobos-Soil" mission designed on the base of multilayer model which includes such levels as Communications, Announcement and Information, Data sharing and Knowledge management. The collaboration support system for "Phobos-Soil" mission will be used as prototype for prospective Russian scientific space missions and the presentation describes its architecture, methodological and technical aspects of its design.

Reinforced soil structures. Volume II, Summary of research and systems information

DOT National Transportation Integrated Search

1989-11-01

Volume II was essentially prepared as an Appendix of supporting information for Volume I. This volume contains much of the supporting theory and a summary of the research used to verify the design approach contained in Volume I, as well as general in...

Application of Remote Sensing Data to Improve the Water and Soil Resource Management of Rwanda

NASA Astrophysics Data System (ADS)

Csorba, Ádám; Bukombe, Benjamin; Naramabuye, Francois Xavier; Szegi, Tamás; Vekerdy, Zoltán; Michéli, Erika

2017-04-01

The Rwandan agriculture strongly relies in the dry seasons on the water stored in artificial reservoirs of various sizes for irrigation purposes. Furthermore, the success of irrigation depends on a wide range of soil properties which directly affect the moisture regime of the growing medium. By integrating remote sensing and auxiliary data the objectives of our study are to monitor the water level fluctuation in the reservoirs, estimate the volume of water available for irrigation and to combine this information with soil property maps to support the decision making for sustainable irrigation water management in a study area in Southern Rwanda. For water level and volume estimation a series of Sentinel-1 (product type: GRD, acquisition mode: IW, polarizations HH and VH) data were obtained covering the study area and spanning over a period of two years. To map the extent of water bodies the Radar-Based Water Body Mapping module of the Water Observation and Information System (WOIS) was used. High-resolution optical data (Sentinel-2) were used for validation in cloud-free periods. To estimate the volume changes in the reservoirs, we combined the information derived from the water body mapping procedure and digital elevation models. For sustainable irrigation water management, digital soil property maps were developed by the application of wide range of environmental covariates related to soil forming factors. To develop covariates which represent the land use a time series analysis of the 2 years of Sentinel-1 data was performed. As auxiliary soil data, the ISRIC-WISE harmonized soil profile database was used. The developed digital soil mapping approach is integrated into a new WOIS workflow.

Biogeochemical Research Priorities for Sustainable Biofuel and Bioenergy Feedstock Production in the Americas.

PubMed

Gollany, Hero T; Titus, Brian D; Scott, D Andrew; Asbjornsen, Heidi; Resh, Sigrid C; Chimner, Rodney A; Kaczmarek, Donald J; Leite, Luiz F C; Ferreira, Ana C C; Rod, Kenton A; Hilbert, Jorge; Galdos, Marcelo V; Cisz, Michelle E

2015-12-01

Rapid expansion in biomass production for biofuels and bioenergy in the Americas is increasing demand on the ecosystem resources required to sustain soil and site productivity. We review the current state of knowledge and highlight gaps in research on biogeochemical processes and ecosystem sustainability related to biomass production. Biomass production systems incrementally remove greater quantities of organic matter, which in turn affects soil organic matter and associated carbon and nutrient storage (and hence long-term soil productivity) and off-site impacts. While these consequences have been extensively studied for some crops and sites, the ongoing and impending impacts of biomass removal require management strategies for ensuring that soil properties and functions are sustained for all combinations of crops, soils, sites, climates, and management systems, and that impacts of biomass management (including off-site impacts) are environmentally acceptable. In a changing global environment, knowledge of cumulative impacts will also become increasingly important. Long-term experiments are essential for key crops, soils, and management systems because short-term results do not necessarily reflect long-term impacts, although improved modeling capability may help to predict these impacts. Identification and validation of soil sustainability indicators for both site prescriptions and spatial applications would better inform commercial and policy decisions. In an increasingly inter-related but constrained global context, researchers should engage across inter-disciplinary, inter-agency, and international lines to better ensure the long-term soil productivity across a range of scales, from site to landscape.

A Drought Cyberinfrastructure System for Improving Water Resource Management and Policy Making

NASA Astrophysics Data System (ADS)

AghaKouchak, Amir

2015-04-01

Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness, management, and response decision making. This presentation provides an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using both remote sensing observations and model simulations. Designed as a cyberinfrastructure system, GIDMaPS provides drought information based on a wide range of model simulations and satellite observations from different space agencies. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts, and better management and distribution of water resources among and across different users. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is designed to provide drought information for water resource management, and short-term decision making. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The presentation will highlight how this drought cyberinfrastructure system can be used to improve water resource management in California. Furthermore, the presentation provides an overview of the information farmers need for better decision making and how GIDMaPS can be used to improve decision making and reducing drought impacts. Further Reading Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1. Momtaz F., Nakhjiri N., AghaKouchak A., 2014, Toward a Drought Cyberinfrastructure System, Eos, Transactions American Geophysical Union, 95(22), 182-183, doi:10.1002/2014EO220002. AghaKouchak A., 2014, A Baseline Probabilistic Drought Forecasting Framework Using Standardized Soil Moisture Index: Application to the 2012 United States Drought, Hydrology and Earth System Sciences, 18, 2485-2492, doi: 10.5194/hess-18-2485-2014.

The spatial relationship between human activities and C, N, P, S in soil based on landscape geochemical interpretation.

PubMed

Yu, Huan; He, Zheng-Wei; Kong, Bo; Weng, Zhong-Yin; Shi, Ze-Ming

2016-04-01

The development and formation of chemical elements in soil are affected not only by parent material, climate, biology, and topology factors, but also by human activities. As the main elements supporting life on earth system, the C, N, P, S cycles in soil have been altered by human activity through land-use change, agricultural intensification, and use of fossil fuels. The present study attempts to analyze whether and how a connection can be made between macroscopical control and microcosmic analysis, to estimate the impacts of human activities on C, N, P, S elements in soil, and to determine a way to describe the spatial relationship between C, N, P, S in soil and human activities, by means of landscape geochemical theories and methods. In addition, the disturbances of human activities on C, N, P, S are explored through the analysis of the spatial relationship between human disturbed landscapes and element anomalies, thereby determining the diversified rules of the effects. The study results show that the rules of different landscapes influencing C, N, P, S elements are diversified, and that the C element is closely related to city landscapes; furthermore, the elements N, P, and S are shown to be closely related to river landscapes; the relationships between mine landscapes and the elements C, N, P, S are apparent; the relationships between the elements C, N, P, S and road landscapes are quite close, which shows that road landscapes have significant effects on these elements. Therefore, the conclusion is drawn that the response mechanism analysis of human disturbance and soil chemical element aggregation is feasible, based on the landscape geochemical theories and methods. The spatial information techniques, such as remote sensing and geographic information systems, are effective for research on soil element migration.

Improved Lower Mekong River Basin Hydrological Decision Making Using NASA Satellite-based Earth Observation Systems

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Mohammed, I. N.; Srinivasan, R.; Lakshmi, V.

2017-12-01

Better understanding of the hydrological cycle of the Lower Mekong River Basin (LMRB) and addressing the value-added information of using remote sensing data on the spatial variability of soil moisture over the Mekong Basin is the objective of this work. In this work, we present the development and assessment of the LMRB (drainage area of 495,000 km2) Soil and Water Assessment Tool (SWAT). The coupled model framework presented is part of SERVIR, a joint capacity building venture between NASA and the U.S. Agency for International Development, providing state-of-the-art, satellite-based earth monitoring, imaging and mapping data, geospatial information, predictive models, and science applications to improve environmental decision-making among multiple developing nations. The developed LMRB SWAT model enables the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil texture, and land cover and land use data to drive SWAT model simulations over the Lower Mekong River Basin. The LMRB SWAT model driven by remote sensing climate data was calibrated and verified with observed runoff data at the watershed outlet as well as at multiple sites along the main river course. Another LMRB SWAT model set driven by in-situ climate observations was also calibrated and verified to streamflow data. Simulated soil moisture estimates from the two models were then examined and compared to a downscaled Soil Moisture Active Passive Sensor (SMAP) 36 km radiometer products. Results from this work present a framework for improving SWAT performance by utilizing a downscaled SMAP soil moisture products used for model calibration and validation. Index Terms: 1622: Earth system modeling; 1631: Land/atmosphere interactions; 1800: Hydrology; 1836 Hydrological cycles and budgets; 1840 Hydrometeorology; 1855: Remote sensing; 1866: Soil moisture; 6334: Regional Planning

SMOS Soil Moisture Data Assimilation in the NASA Land Information System: Impact on LSM Initialization and NWP Forecasts

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Bradley

2015-01-01

Land surface models are important components of numerical weather prediction (NWP) models, partitioning incoming energy into latent and sensitive heat fluxes that affect boundary layer growth and destabilization. During warm-season months, diurnal heating and convective initiation depend strongly on evapotranspiration and available boundary layer moisture, which are substantially affected by soil moisture content. Therefore, to properly simulate warm-season processes in NWP models, an accurate initialization of the land surface state is important for accurately depicting the exchange of heat and moisture between the surface and boundary layer. In this study, soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) satellite radiometer are assimilated into the Noah Land Surface Model via an Ensemble Kalman Filter embedded within the NASA Land Information System (LIS) software framework. The output from LIS-Noah is subsequently used to initialize runs of the Weather Research and Forecasting (WRF) NWP model. The impact of assimilating SMOS retrievals is assessed by initializing the WRF model with LIS-Noah output obtained with and without SMOS data assimilation. The southeastern United States is used as the domain for a preliminary case study. During the summer months, there is extensive irrigation in the lower Mississippi Valley for rice and other crops. The irrigation is not represented in the meteorological forcing used to drive the LIS-Noah integration, but the irrigated areas show up clearly in the SMOS soil moisture retrievals, resulting in a case with a large difference in initial soil moisture conditions. The impact of SMOS data assimilation on both Noah soil moisture fields and on short-term (0-48 hour) WRF weather forecasts will be presented.

Spatial Variability of Grapevine Bud Burst Percentage and Its Association with Soil Properties at Field Scale

PubMed Central

Li, Tao; Hao, Xinmei; Kang, Shaozhong

2016-01-01

There is a growing interest in precision viticulture with the development of global positioning system and geographical information system technologies. Limited information is available on spatial variation of bud behavior and its possible association with soil properties. The objective of this study was to investigate spatial variability of bud burst percentage and its association with soil properties based on 2-year experiments at a vineyard of arid northwest China. Geostatistical approach was used to describe the spatial variation in bud burst percentage within the vineyard. Partial least square regressions (PLSRs) of bud burst percentage with soil properties were used to evaluate the contribution of soil properties to overall spatial variability in bud burst percentage for the high, medium and low bud burst percentage groups. Within the vineyard, the coefficient of variation (CV) of bud burst percentage was 20% and 15% for 2012 and 2013 respectively. Bud burst percentage within the vineyard showed moderate spatial variability, and the overall spatial pattern of bud burst percentage was similar between the two years. Soil properties alone explained 31% and 37% of the total spatial variation respectively for the low group of 2012 and 2013, and 16% and 24% for the high group of 2012 and 2013 respectively. For the low group, the fraction of variations explained by soil properties was found similar between the two years, while there was substantial difference for the high group. The findings are expected to lay a good foundation for developing remedy measures in the areas with low bud burst percentage, thus in turn improving the overall grape yield and quality. PMID:27798692

Isotope Tracing of Long-Term Cadmium Fluxes in an Agricultural Soil.

PubMed

Salmanzadeh, Mahdiyeh; Hartland, Adam; Stirling, Claudine H; Balks, Megan R; Schipper, Louis A; Joshi, Chaitanya; George, Ejin

2017-07-05

Globally widespread phosphate fertilizer applications have resulted in long-term increases in the concentration of cadmium (Cd) in soils. The accumulation of this biotoxic, and bioaccumulative metal presents problems for the management of soil-plant-animal systems, because the magnitude and direction of removal fluxes (e.g., crop uptake, leaching) have been difficult to estimate. Here, Cd isotopic compositions (δ 114/110 Cd) of archived fertilizer and soil samples from a 66 year-long agricultural field trial in Winchmore, New Zealand, were used to constrain the Cd soil mass balance between 1959 and 2015 AD, informing future soil Cd accumulation trajectories. The isotopic partitioning of soil Cd sources in this system was aided by a change in phosphate source rocks in 1998 AD, and a corresponding shift in fertilizer isotope composition. The dominant influence of mixing between isotopically distinct Cd end-members was confirmed by a Bayesian modeling approach. Furthermore, isotope mass balance modeling revealed that Cd removal processes most likely increased in magnitude substantially between 2000 and 2015 AD, implying an increase in Cd bioaccumulation and/or leaching over that interval. Natural-abundance stable isotopes are introduced here as a powerful tool for tracing the fate of Cd in agricultural soils, and potentially the wider environment.

[Extracting black soil border in Heilongjiang province based on spectral angle match method].

PubMed

Zhang, Xin-Le; Zhang, Shu-Wen; Li, Ying; Liu, Huan-Jun

2009-04-01

As soils are generally covered by vegetation most time of a year, the spectral reflectance collected by remote sensing technique is from the mixture of soil and vegetation, so the classification precision based on remote sensing (RS) technique is unsatisfied. Under RS and geographic information systems (GIS) environment and with the help of buffer and overlay analysis methods, land use and soil maps were used to derive regions of interest (ROI) for RS supervised classification, which plus MODIS reflectance products were chosen to extract black soil border, with methods including spectral single match. The results showed that the black soil border in Heilongjiang province can be extracted with soil remote sensing method based on MODIS reflectance products, especially in the north part of black soil zone; the classification precision of spectral angel mapping method is the highest, but the classifying accuracy of other soils can not meet the need, because of vegetation covering and similar spectral characteristics; even for the same soil, black soil, the classifying accuracy has obvious spatial heterogeneity, in the north part of black soil zone in Heilongjiang province it is higher than in the south, which is because of spectral differences; as soil uncovering period in Northeastern China is relatively longer, high temporal resolution make MODIS images get the advantage over soil remote sensing classification; with the help of GIS, extracting ROIs by making the best of auxiliary data can improve the precision of soil classification; with the help of auxiliary information, such as topography and climate, the classification accuracy was enhanced significantly. As there are five main factors determining soil classes, much data of different types, such as DEM, terrain factors, climate (temperature, precipitation, etc.), parent material, vegetation map, and remote sensing images, were introduced to classify soils, so how to choose some of the data and quantify the weights of different data layers needs further study.

Soil and crop management experiments in the Laboratory Biosphere: An analogue system for the Mars on Earth ® facility

NASA Astrophysics Data System (ADS)

Silverstone, S.; Nelson, M.; Alling, A.; Allen, J. P.

During the years 2002 and 2003, three closed system experiments were carried out in the "Laboratory Biosphere" facility located in Santa Fe, New Mexico. The program involved experimentation of "Hoyt" Soy Beans, (experiment #1) USU Apogee Wheat (experiment #2) and TU-82-155 sweet potato (experiment #3) using a 5.37 m 2 soil planting bed which was 30 cm deep. The soil texture, 40% clay, 31% sand and 28% silt (a clay loam), was collected from an organic farm in New Mexico to avoid chemical residues. Soil management practices involved minimal tillage, mulching, returning crop residues to the soil after each experiment and increasing soil biota by introducing worms, soil bacteria and mycorrhizae fungi. High soil pH of the original soil appeared to be a factor affecting the first two experiments. Hence, between experiments #2 and #3, the top 15 cm of the soil was amended using a mix of peat moss, green sand, humates and pumice to improve soil texture, lower soil pH and increase nutrient availability. This resulted in lowering the initial pH of 8.0-6.7 at the start of experiment #3. At the end of the experiment, the pH was 7.6. Soil nitrogen and phosphorus has been adequate, but some chlorosis was evident in the first two experiments. Aphid infestation was the only crop pest problem during the three experiments and was handled using an introduction of Hyppodamia convergens. Experimentation showed there were environmental differences even in this 1200 cubic foot ecological system facility, such as temperature and humidity gradients because of ventilation and airflow patterns which resulted in consequent variations in plant growth and yield. Additional humidifiers were added to counteract low humidity and helped optimize conditions for the sweet potato experiment. The experience and information gained from these experiments are being applied to the future design of the Mars On Earth ® facility (Silverstone et al., Development and research program for a soil-based bioregenerative agriculture system to feed a four person crew at a Mars base, Advances in Space Research 31(1) (2003) 69-75; Allen and Alling, The design approach for Mars On Earth ®, a biospheric closed system testing facility for long-term space habitation, American Institute of Aeronautics and Astronautics Inc., IAC-02-IAA.8.2.02, 2002).

Non-invasive analysis of root-soil interaction using three complementary imaging approaches

NASA Astrophysics Data System (ADS)

Haber-Pohlmeier, Sabina; Tötzke, Christian; Pohlmeier, Andreas; Rudolph-Mohr, Nicole; Kardjilov, Nikolay; Lehmann, Eberhard; Oswald, Sascha E.

2016-04-01

Plant roots are known to modify physical, chemical and biological properties of the rhizosphere, thereby, altering conditions for water and nutrient uptake. We aim for capturing the dynamic processes occurring at the soil-root interface in situ. A combination of neutron (NI), magnetic resonance (MRI) and micro-focus X-ray tomography (CT) is applied to monitor the rhizosphere of young plants grown in sandy soil in cylindrical containers (diameter 3 cm). A novel transportable low field MRI system is operated directly at the neutron facility allowing for combined measurements of the very same sample capturing the same hydro-physiological state. The combination of NI, MRI and CT provides three-dimensional access to the root system in respect to structure and hydraulics of the rhizosphere and the transport of dissolved marker substances. The high spatial resolution of neutron imaging and its sensitivity for water can be exploited for the 3D analysis of the root morphology and detailed mapping of three-dimensional water content at the root soil interface and the surrounding soil. MRI has the potential to yield complementary information about the mobility of water, which can be bound in small pores or in the polymeric network of root exudates (mucilage layer). We inject combined tracers (GdDPTA or D2O) to study water fluxes through soil, rhizosphere and roots. Additional CT measurements reveal mechanical impacts of roots on the local microstructure of soil, e.g. showing soil compaction or the formation of cracks. We co-register the NT, MRI and CT data to integrate the complementary information into an aligned 3D data set. This allows, e.g., for co-localization of compacted soil regions or cracks with the specific local soil hydraulics, which is needed to distinguish the contribution of root exudation from mechanical impacts when interpreting altered hydraulic properties of the rhizosphere. Differences between rhizosphere and bulk soil can be detected and interpreted in terms of root growth, root exudation, and root water uptake. Thus, we demonstrate that such a multi-imaging approach can be used as powerful tool contributing to a more comprehensive picture of the rhizosphere.

Application of a geographical information system approach for risk analysis of fascioliasis in southern Espírito Santo state, Brazil.

PubMed

Martins, Isabella Vilhena Freire; de Avelar, Barbara Rauta; Pereira, Maria Julia Salim; da Fonseca, Adevair Henrique

2012-09-01

A model based on geographical information systems for mapping the risk of fascioliasis was developed for the southern part of Espírito Santo state, Brazil. The determinants investigated were precipitation, temperature, elevation, slope, soil type and land use. Weightings and grades were assigned to determinants and their categories according to their relevance with respect to fascioliasis. Theme maps depicting the spatial distribution of risk areas indicate that over 50% of southern Espírito Santo is either at high or at very high risk for fascioliasis. These areas were found to be characterized by comparatively high temperature but relatively low slope, low precipitation and low elevation corresponding to periodically flooded grasslands or soils that promote water retention.

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.

Spatial distribution and risk assessment of radionuclides in soils around a coal-fired power plant: A case study from the city of Baoji, China

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

Dai Lijun; Wei Haiyan; Wang Lingqing

2007-06-15

Coal burning may enhance human exposure to the natural radionuclides that occur around coal-fired power plants (CFPP). In this study, the spatial distribution and hazard assessment of radionuclides found in soils around a CFPP were investigated using statistics, geostatistics, and geographic information system (GIS) techniques. The concentrations of {sup 226}Ra, {sup 232}Th, and {sup 40}K in soils range from 12.54 to 40.18, 38.02 to 72.55, and 498.02 to 1126.98 Bq kg{sup -1}, respectively. Ordinary kriging was carried out to map the spatial patterns of radionuclides, and disjunctive kriging was used to quantify the probability of radium equivalent activity (Ra{sub eq})more » higher than the threshold. The maps show that the spatial variability of the natural radionuclide concentrations in soils was apparent. The results of this study could provide valuable information for risk assessment of environmental pollution and decision support.« less

Spatial distribution and risk assessment of radionuclides in soils around a coal-fired power plant: A case study from the city of Baoji, China

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

Dai, L.J.; Wei, H.Y.; Wang, L.Q.

2007-06-15

Coal burning may enhance human exposure to the natural radionuclides that occur around coal-fired power plants (CFPP). In this study, the spatial distribution and hazard assessment of radionuclides found in soils around a CFPP were investigated using statistics, geostatistics, and geographic information system (GIS) techniques. The concentrations of Ra-226, Th-232, and K-40 in soils range from 12.54 to 40.18, 38.02 to 72.55, and 498.02 to 1126.98 Bq kg{sup -1}, respectively. Ordinary kriging was carried out to map the spatial patterns of radionuclides, and disjunctive kriging was used to quantify the probability of radium equivalent activity (Ra{sub eq}) higher than themore » threshold. The maps show that the spatial variability of the natural radionuclide concentrations in soils was apparent. The results of this study could provide valuable information for risk assessment of environmental pollution and decision support.« less

GIS environmental information analysis of the Darro River basin as the key for the management and hydrological forest restoration.

PubMed

Fernandez, Paz; Delgado, Expectación; Lopez-Alonso, Mónica; Poyatos, José Manuel

2018-02-01

This article presents analyses of soil and environmental information for the Darro River basin (Granada-Spain) preliminary to its hydrological and forestry restoration. These analyses were carried out using a geographical information system (GIS) and employing a new procedure that adapts hydrological forest-restoration methods. The complete analysis encompasses morphological conditions, soil and climate characteristics as well as vegetation and land use. The study investigates soil erosion in the basin by using Universal Soil Loss Equation (USLE) and by mapping erosion fragility units. The results are presented in a set of maps and their analysis, providing the starting point for river basin management and the hydrological and forestry-restoration project that was approved at the end of 2015. The presence of soft substrates (e.g. gravel and sand) indicates that the area is susceptible to erosion, particularly the areas that are dominated by human activity and have little soil protection. Finally, land use and vegetation cover were identified as key factors in the soil erosion in the basin. According to the results, river authorities have included several measures in the restoration project aimed at reducing the erosion and helping to recover the environmental value of this river basin and to include it in recreation possibilities for the community of Granada. The presented analytical approach, designed by the authors, would be useful as a tool for environmental restoration in other small Mediterranean river basins. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatially distributed modeling of soil organic carbon across China with improved accuracy

NASA Astrophysics Data System (ADS)

Li, Qi-quan; Zhang, Hao; Jiang, Xin-ye; Luo, Youlin; Wang, Chang-quan; Yue, Tian-xiang; Li, Bing; Gao, Xue-song

2017-06-01

There is a need for more detailed spatial information on soil organic carbon (SOC) for the accurate estimation of SOC stock and earth system models. As it is effective to use environmental factors as auxiliary variables to improve the prediction accuracy of spatially distributed modeling, a combined method (HASM_EF) was developed to predict the spatial pattern of SOC across China using high accuracy surface modeling (HASM), artificial neural network (ANN), and principal component analysis (PCA) to introduce land uses, soil types, climatic factors, topographic attributes, and vegetation cover as predictors. The performance of HASM_EF was compared with ordinary kriging (OK), OK, and HASM combined, respectively, with land uses and soil types (OK_LS and HASM_LS), and regression kriging combined with land uses and soil types (RK_LS). Results showed that HASM_EF obtained the lowest prediction errors and the ratio of performance to deviation (RPD) presented the relative improvements of 89.91%, 63.77%, 55.86%, and 42.14%, respectively, compared to the other four methods. Furthermore, HASM_EF generated more details and more realistic spatial information on SOC. The improved performance of HASM_EF can be attributed to the introduction of more environmental factors, to explicit consideration of the multicollinearity of selected factors and the spatial nonstationarity and nonlinearity of relationships between SOC and selected factors, and to the performance of HASM and ANN. This method may play a useful tool in providing more precise spatial information on soil parameters for global modeling across large areas.

Oxygen isotopes as a tracer of phosphate sources and cycling in aquatic systems (Invited)

NASA Astrophysics Data System (ADS)

Young, M. B.; Kendall, C.; Paytan, A.

2013-12-01

The oxygen isotopic composition of phosphate can provide valuable information about sources and processes affecting phosphorus as it moves through hydrologic systems. Applications of this technique in soil and water have become more common in recent years due to improvements in extraction methods and instrument capabilities, and studies in multiple aquatic environments have demonstrated that some phosphorus sources may have distinct isotopic compositions within a given system. Under normal environmental conditions, the oxygen-phosphorus bonds in dissolved inorganic phosphate (DIP) can only be broken by enzymatic activity. Biological cycling of DIP will bring the phosphate oxygen into a temperature-dependent equilibrium with the surrounding water, overprinting any existing isotopic source signals. However, studies conducted in a wide range of estuarine, freshwater, and groundwater systems have found that the phosphate oxygen is often out of biological equilibrium with the water, suggesting that it is common for at least a partial isotopic source signal to be retained in aquatic systems. Oxygen isotope analysis on various potential phosphate sources such as synthetic and organic fertilizers, animal waste, detergents, and septic/wastewater treatment plant effluents show that these sources span a wide range of isotopic compositions, and although there is considerable overlap between the source groups, sources may be isotopically distinct within a given study area. Recent soil studies have shown that isotopic analysis of phosphate oxygen is also useful for understanding microbial cycling across different phosphorus pools, and may provide insights into controls on phosphorus leaching. Combining stable isotope information from soil and water studies will greatly improve our understanding of complex phosphate cycling, and the increasing use of this isotopic technique across different environments will provide new information regarding anthropogenic phosphate inputs and controls on biological cycling within hydrologic systems.

Characterization of wet aggregate stability of soils by ¹H-NMR relaxometry.

PubMed

Buchmann, C; Meyer, M; Schaumann, G E

2015-09-01

For the assessment of soil structural stability against hydraulic stress, wet sieving or constant head permeability tests are typically used but rather limited in their intrinsic information value. The multiple applications of several tests is the only possibility to assess important processes and mechanisms during soil aggregate breakdown, e.g. the influences of soil fragment release or differential swelling on the porous systems of soils or soil aggregate columns. Consequently, the development of new techniques for a faster and more detailed wet aggregate stability assessment is required. (1)H nuclear magnetic resonance relaxometry ((1)H-NMR relaxometry) might provide these requirements because it has already been successfully applied on soils. We evaluated the potential of (1)H-NMR relaxometry for the assessment of wet aggregate stability of soils, with more detailed information on occurring mechanisms at the same time. Therefore, we conducted single wet sieving and constant head permeability tests on untreated and 1% polyacrylic acid-treated soil aggregates of different textures and organic matter contents, subsequently measured by (1)H-NMR relaxometry after percolation. The stability of the soil aggregates were mainly depending on their organic matter contents and the type of aggregate stabilization, whereby additional effects of clay swelling on the measured wet aggregate stability were identified by the transverse relaxation time (T2) distributions. Regression analyses showed that only the percentage of water stable aggregates could be determined accurately from percolated soil aggregate columns by (1)H-NMR relaxometry measurements. (1)H-NMR relaxometry seems a promising technique for wet aggregate stability measurements but should be further developed for nonpercolated aggregate columns and real soil samples. Copyright © 2014 John Wiley & Sons, Ltd.

7 CFR 658.5 - Criteria.

Code of Federal Regulations, 2011 CFR

2011-01-01

... information from several sources including national cooperative soil surveys or other acceptable soil surveys, NRCS field office technical guides, soil potential ratings or soil productivity ratings, land capability classifications, and important farmland determinations. Based on this information, groups of soils...

7 CFR 658.5 - Criteria.

Code of Federal Regulations, 2010 CFR

2010-01-01

... information from several sources including national cooperative soil surveys or other acceptable soil surveys, NRCS field office technical guides, soil potential ratings or soil productivity ratings, land capability classifications, and important farmland determinations. Based on this information, groups of soils...

Principles of soil mapping of a megalopolis with St. Petersburg as an example

NASA Astrophysics Data System (ADS)

Aparin, B. F.; Sukhacheva, E. Yu.

2014-07-01

For the first time, a soil map of St. Petersburg has been developed on a scale of 1 : 50000 using MicroStation V8i software. The legend to this map contains more than 60 mapping units. The classification of urban soils and information on the soil cover patterns are principally new elements of this legend. New concepts of the urbanized soil space and urbopedocombinations have been suggested for soil mapping of urban territories. The typification of urbopedocombinations in St. Petersburg has been performed on the basis of data on the geometry and composition of the polygons of soils and nonsoil formations. The ratio between the areas of soils and nonsoil formations and their spatial distribution patterns have been used to distinguish between six types of the urbanized soil space. The principles of classification of the soils of urban territories have been specified, and a separate order of pedo-allochthonous soils has been suggested for inclusion into the Classification and Diagnostic System of Russian Soils (2004). Six types of pedo-allochthonous soils have been distinguished on the basis of data on their humus and organic horizons and the character of the underlying mineral substrate.

Evolution of 2016 drought in the Southeastern United States from a Land surface modeling perspective

NASA Astrophysics Data System (ADS)

Case, Jonathan L.; Zavodsky, Bradley T.

2018-03-01

The Southeastern United States (SEUS) climate region experienced a marked transition from excessively wet conditions early in 2016 to an exceptional drought during the Autumn. The unusually warm and dry conditions led to numerous wildfires, including the devastating Gatlinburg, Tennessee (TN) firestorm on 28-29 November. The evolution of soil wetness anomalies are highlighted through soil moisture percentiles derived from an instance of NASA's Land Information System (LIS). A 33-year soil moisture climatology simulation combined with daily, real-time county-based distributions illustrate how soil moisture began above the 96th percentile early in 2016, and declined to below the 2nd percentile in many locales by late November.

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.

Macroscopic behavior and fluctuation-dissipation response of stochastic ecohydrological systems

NASA Astrophysics Data System (ADS)

Porporato, A. M.

2017-12-01

The coupled dynamics of water, carbon and nutrient cycles in ecohydrological systems is forced by unpredictable and intermittent hydroclimatic fluctuations at different time scales. While modeling and long-term prediction of these complex interactions often requires a probabilistic approach, the resulting stochastic equations however are only solvable in special cases. To obtain information on the behavior of the system one typically has to resort to approximation methods. Here we discuss macroscopic equations for the averages and fluctuation-dissipation estimates for the general correlations between the forcing and the ecohydrological response for the soil moisture-plant biomass interaction and the problem of primary salinization and nitrogen retention in soils.

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.

Using SMAP data to improve drought early warning over the US Great Plains

NASA Astrophysics Data System (ADS)

Fu, R.; Fernando, N.; Tang, W.

2015-12-01

A drought prone region such as the Great Plains of the United States (US GP) requires credible and actionable drought early warning. Such information cannot simply be extracted from available climate forecasts because of their large uncertainties at regional scales, and unclear connections to the needs of the decision makers. In particular, current dynamic seasonal predictions and climate projections, such as those produced by the NOAA North American Multi-Model Ensemble experiment (NMME) are much more reliable for winter and spring than for the summer season for the US GP. To mitigate the weaknesses of dynamic prediction/projections, we have identified three key processes behind the spring-to-summer dry memory through observational studies, as the scientific basis for a statistical drought early warning system. This system uses percentile soil moisture anomalies in spring as a key input to provide a probabilistic summer drought early warning. The latter outperforms the dynamic prediction over the US Southern Plains and has been used by the Texas state water agency to support state drought preparedness. A main source of uncertainty for this drought early warning system is the soil moisture input obtained from the NOAA Climate Forecasting System (CFS). We are testing use of the beta version of NASA Soil Moisture Active Passive (SMAP) soil moisture data, along with the Soil Moisture and Ocean Salinity (SMOS), and the long-term Essential Climate Variable Soil Moisture (ECV-SM) soil moisture data, to reduce this uncertainty. Preliminary results based on ECV-SM suggests satellite based soil moisture data could improve early warning of rainfall anomalies over the western US GP with less dense vegetation. The skill degrades over the eastern US GP where denser vegetation is found. We evaluate our SMAP-based drought early warning for 2015 summer against observations.

Trace element biogeochemistry in the soil-water-plant system of a temperate agricultural soil amended with different biochars.

PubMed

Kloss, Stefanie; Zehetner, Franz; Buecker, Jannis; Oburger, Eva; Wenzel, Walter W; Enders, Akio; Lehmann, Johannes; Soja, Gerhard

2015-03-01

Various biochar (BC) types have been investigated as soil amendment; however, information on their effects on trace element (TE) biogeochemistry in the soil-water-plant system is still scarce. In the present study, we determined aqua-regia (AR) and water-extractable TEs of four BC types (woodchips (WC), wheat straw (WS), vineyard pruning (VP), pyrolyzed at 525 °C, of which VP was also pyrolyzed at 400 °C) and studied their effects on TE concentrations in leachates and mustard (Sinapis alba L.) tissue in a greenhouse pot experiment. We used an acidic, sandy agricultural soil and a BC application rate of 3% (w/w). Our results show that contents and extractability of TEs in the BCs and effectuated changes of TE biogeochemistry in the soil-water-plant system strongly varied among the different BC types. High AR-digestable Cu was found in VP and high B contents in WC. WS had the highest impact on TEs in leachates showing increased concentrations of As, Cd, Mo, and Se, whereas WC application resulted in enhanced leaching of B. All BC types increased Mo and decreased Cu concentrations in the plant tissue; however, they showed diverging effects on Cu in the leachates with decreased concentrations for WC and WS, but increased concentrations for both VPs. Our results demonstrate that BCs may release TEs into the soil-water-plant system. A BC-induced liming effect in acidic soils may lead to decreased plant uptake of cationic TEs, including Pb and Cd, but may enhance the mobility of anionic TEs like Mo and As. We also found that BCs with high salt contents (e.g., straw-based BCs) may lead to increased mobility of both anionic and cationic TEs in the short term.

Uncertainty indication in soil function maps - transparent and easy-to-use information to support sustainable use of soil resources

NASA Astrophysics Data System (ADS)

Greiner, Lucie; Nussbaum, Madlene; Papritz, Andreas; Zimmermann, Stephan; Gubler, Andreas; Grêt-Regamey, Adrienne; Keller, Armin

2018-05-01

Spatial information on soil function fulfillment (SFF) is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1) indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM) that are used for soil function assessment (SFA) and (2) showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil resources.

Comparison of microclimate in various land-use systems in Sumatra, Indonesia

NASA Astrophysics Data System (ADS)

Shekhar Badu, Chandra; Meijide, Ana; Gunawan, Dodo; Knohl, Alexander

2017-04-01

Deforestation and land-use changes are ongoing problems for rain forests in Indonesia. The conversion of forests to monocultures of rubber and oil palm plantations reduces not only biodiversity and carbon pools but also affects canopy structure, which is an important determinant of microclimate. There is, however, a lack of quantitative information characterizing the effect of land transformation on microclimate with a systematic experimental design. Here, we report observations microclimatic conditions (air temperature, relative humidity, soil moisture and soil temperature) on a daily, weekly and seasonal basis across four land-use systems (rain forest, jungle rubber, rubber plantation, oil palm plantation) in two near-by landscapes. The data set covers a period of approximately three years from April 2013 to March 2016 and includes one of the strongest El Nino-Southern Oscillation (ENSO) of the last decades. Mean air temperature, soil temperature, relative humidity, and vapour pressure deficit differed significantly between the four land-use systems whereas the mean soil moisture differed significantly between two landscapes. Air temperature, vapour pressure deficit and soil temperature were highest in oil palm and rubber plantations whereas lowest in forest and jungle rubber. Canopy openness was the most dominant control of microclimatic differences across the land-use systems. During the ENSO 2015, a significant increase in mean air temperature, soil temperature and vapour pressure deficit but a decrease in relative air humidity and soil moisture in all four land-use systems was found. The relative effect of ENSO was highest in forest and jungle rubber compared to rubber and oil palm plantations. In conclusion, conversion of forest to rubber and oil palm plantations has led to substantially warmer and drier microclimatic conditions than before.

An approach for land suitability evaluation using geostatistics, remote sensing, and geographic information system in arid and semiarid ecosystems.

PubMed

Emadi, Mostafa; Baghernejad, Majid; Pakparvar, Mojtaba; Kowsar, Sayyed Ahang

2010-05-01

This study was undertaken to incorporate geostatistics, remote sensing, and geographic information system (GIS) technologies to improve the qualitative land suitability assessment in arid and semiarid ecosystems of Arsanjan plain, southern Iran. The primary data were obtained from 85 soil samples collected from tree depths (0-30, 30-60, and 60-90 cm); the secondary information was acquired from the remotely sensed data from the linear imaging self-scanner (LISS-III) receiver of the IRS-P6 satellite. Ordinary kriging and simple kriging with varying local means (SKVLM) methods were used to identify the spatial dependency of soil important parameters. It was observed that using the data collected from the spectral values of band 1 of the LISS-III receiver as the secondary variable applying the SKVLM method resulted in the lowest mean square error for mapping the pH and electrical conductivity (ECe) in the 0-30-cm depth. On the other hand, the ordinary kriging method resulted in a reliable accuracy for the other soil properties with moderate to strong spatial dependency in the study area for interpolation in the unstamped points. The parametric land suitability evaluation method was applied on the density points (150 x 150 m(2)) instead of applying on the limited representative profiles conventionally, which were obtained by the kriging or SKVLM methods. Overlaying the information layers of the data was used with the GIS for preparing the final land suitability evaluation. Therefore, changes in land characteristics could be identified in the same soil uniform mapping units over a very short distance. In general, this new method can easily present the squares and limitation factors of the different land suitability classes with considerable accuracy in arbitrary land indices.

Improvements of soil quality for increased food production in Norway

NASA Astrophysics Data System (ADS)

Øygarden, Lillian; Klakegg, Ove; Børresen, Trond; Krogstad, Tore; Kjersti Uhlen, Anne

2016-04-01

Since the 1990ties, agricultural land in use in Norway has diminished and yields per hectare for cereals and forages have stagnated. An expert panel appointed to advice on how to increase Norwegian grain production emphasizes low profitability and poor soil quality as limiting factors. A White Paper from the Norwegian Government, Report No.9 (2011-2012), stated that the main goal for the agricultural sector is to increase food production proportional to the expected increase in population (20 % by 2030) in order to maintain self-sufficiency at the present level. This is the background for the interdisciplinary project AGROPRO "Agronomy for increased food production - Challenges and solutions" (2013 - 2017)" financed by the Norwegian research council. A mail goal is seeking possibilities for improvements in agronomic practices for increased and sustainable food production and to identify drivers and challenges for their implementation. Are the key to higher yields hidden in the soil? The paper present an overview of the research activities in the project and some results of the improvements of soil quality to minimize yield gap in cereal and forage production. Detailed new soil maps provide soil information on field scale of soil quality and the suitability for growing different crops like cereal production or vegetables. The detailed soil information is also beeing used for development and adaptation of the planning tool «Terranimo» to reduce risk of soil compaction.The farmer get available soil information for each field, provide information about the maschinery in use- tractors and equipment, tyres, pressure. The decision tool evaluate when the soil is suitable for tillage, calculate the risk of compaction for dry, moist and wet soil. New research data for compaction on Norwegian clay and silt soil are included. Climate change with wetter conditions gives challenges for growing cereals. The project is testing genetic variation in cereals for tolerance to water logging and soil compaction. Several hundred different varieties for barley, oat and wheat are being waterlogged and resulting effects studied, also illustrating the need and benefit of cooperation between soil science and plant science (plant physiology). Field studies of functional root depth and root development is performed for studies of nutrient use efficiency of nitrogen and phosporus. Isotopic studies (15N) and DGT(diffuse gradients in thin films) are performed in long term experiments. Different rooting depths are studied in relation to effect of cutting regime of grasland, trafficking. The project perform new measurements of (N2O) emissions from long term cropping system experiments with different crop rotations, cultivation practice and fertilizing strategy. This can give better understanding of agronomic practices, nitrogen use efficiency and (N2O) emissions. The environmental effects of agricultural production is also dependent on the microbiological soil conditions.

Landmarks of History of Soil Science in Sri Lanka

NASA Astrophysics Data System (ADS)

Mapa, R.

2012-04-01

Sri Lanka is a tropical Island in the Southern tip of Indian subcontinent positioned at 50 55' to 90 50' N latitude and 790 42' to 810 53' E longitude surrounded by the Indian Ocean. It is an island 435 km in length and 224 km width consisting of a land are of 6.56 million ha with a population of 20 million. In area wise it is ranked as 118th in the world, where at present ranked as 47 in population wise and ranked 19th in population density. The country was under colonial rule under Portuguese, Dutch and British from 1505 to 1948. The majority of the people in the past and present earn their living from activities based on land, which indicates the important of the soil resource. The objective of this paper is to describe the landmarks of the history of Soil Science to highlight the achievements and failures, which is useful to enrich our present understanding of Sri Lankan soils. The landmarks of the history of Soil Science in Sri Lanka can be divided to three phases namely, the early period (prior to 1956), the middle period (1956 to 1972) and the present period (from 1972 onwards). During the early period, detailed analytical studies of coffee and tea soils were compiled, and these gave mainly information on up-country soils which led to fertilizer recommendations based on field trials. In addition, rice and forest soils were also studied in less detail. The first classification of Sri Lankan soils and a provisional soil map based on parent material was published by Joachim in 1945 which is a major landmark of history of Soil Science in Sri Lanka. In 1959 Ponnamperuma proposed a soil classification system for wetland rice soils. From 1963 to 1968 valuable information on the land resource was collected and documented by aerial resource surveys funded by Canada-Ceylon Colombo plan aid project. This covered 18 major river basins and about 1/4th of Sri Lanka, which resulted in producing excellent soil maps and information of the areas called the Kelani Aruvi Ara and Walawe basins. The provisional soil map was updated by many other workers as Moorman and Panabokke in 1961 and 1972 using this information. The soil map produced by De Alwis and Panabokke in 1972 at a scale of 1:500,000 was the soil maps mostly used during the past years During the present era, the need for classification of Soils of Sri Lanka according to international methods was felt. A major leap forward in Soil Survey, Classification leading to development of a soil data base was initiated in 1995 with the commencement of the "SRICANSOL" project which was a twining project between the Soil Science Societies of Sri Lanka and Canada. This project is now completed with detail soil maps at a scale of 1:250,000 and soil classified according to international methods for the Wet, Intermediate and Dry zones of Sri Lanka. A digital database consisting of soil profile description and physical and chemical data is under preparation for 28, 40 and 51 benchmark sites of the Wet, Intermediate and Dry zones respectively. The emphases on studies on Soil Science in the country at present is more towards environmental conservation related to soil erosion control, reducing of pollution of soil and water bodies from nitrates, pesticide residues and heavy metal accumulation. Key words: Sri Lanka, Provisional soil map

Incorporation of Monitoring Systems to Model Irrigated Cotton at a Landscape Level

USDA-ARS?s Scientific Manuscript database

Advances in computer speed, industry IT core capabilities, and available soils and weather information have resulted in the need for “cropping system models” that address in detail the spatial and temporal water, energy and carbon balance of the system at a landscape scale. Many of these models have...

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.

Envirotyping for deciphering environmental impacts on crop plants.

PubMed

Xu, Yunbi

2016-04-01

Global climate change imposes increasing impacts on our environments and crop production. To decipher environmental impacts on crop plants, the concept "envirotyping" is proposed, as a third "typing" technology, complementing with genotyping and phenotyping. Environmental factors can be collected through multiple environmental trials, geographic and soil information systems, measurement of soil and canopy properties, and evaluation of companion organisms. Envirotyping contributes to crop modeling and phenotype prediction through its functional components, including genotype-by-environment interaction (GEI), genes responsive to environmental signals, biotic and abiotic stresses, and integrative phenotyping. Envirotyping, driven by information and support systems, has a wide range of applications, including environmental characterization, GEI analysis, phenotype prediction, near-iso-environment construction, agronomic genomics, precision agriculture and breeding, and development of a four-dimensional profile of crop science involving genotype (G), phenotype (P), envirotype (E) and time (T) (developmental stage). In the future, envirotyping needs to zoom into specific experimental plots and individual plants, along with the development of high-throughput and precision envirotyping platforms, to integrate genotypic, phenotypic and envirotypic information for establishing a high-efficient precision breeding and sustainable crop production system based on deciphered environmental impacts.

Decision Support Systems To Manage Water Resources At Irrigation District Level In Southern Italy Using Remote Sensing Information. An Integrated Project (AQUATER)

NASA Astrophysics Data System (ADS)

Rinaldi, M.; Castrignanò, A.; Mastrorilli, M.; Rana, G.; Ventrella, D.; Acutis, M.; D'Urso, G.; Mattia, F.

2006-08-01

An efficient management of water resources is crucial point for Italy and in particular for southern areas characterized by Mediterranean climate in order to improve the economical and environmental sustainability of the agricultural activity. A three-year Project (2005-2008) has been funded by the Italian Ministry of Agriculture and Forestry Policies; it involves four Italian research institutions: the Agricultural Research Council (ISA, Bari), the National Research Council (ISSIA, Bari) and two Universities (Federico II-Naples and Milan). It is focused on the remote sensing, the plant and the climate and, for interdisciplinary relationships, the project working group consists of agronomists, engineers and physicists. The aims of the Project are: a) to produce a Decision Support System (DSS) combining remote sensing information, spatial data and simulation models to manage water resources in irrigation districts; b) to simulate irrigation scenarios to evaluate the effects of water stress on crop yield using agro-ecological indicators; c) to identify the most sensitive areas to drought risk in Southern Italy. The tools used in this Project will be: 1. Remote sensing images, topographic maps, soil and land use maps; 2. Geographic Information Systems; 3. Geostatistic methodologies; 4. Ground truth measurements (land use, canopy and soil temperatures, soil and plant water status, Normalized Difference Vegetation Index, Crop Water Stress Index, Leaf Area Index, actual evapotranspiration, crop coefficients, crop yield, agro-ecological indicators); 5. Crop simulation models. The Project is structured in four work packages with specific objectives, high degree of interaction and information exchange: 1) Remote Sensing and Image Analysis; 2) Cropping Systems; 3) Modelling and Softwares Development; 4) Stakeholders. The final product will be a DSS with the purpose of integrating remote sensing images, to estimate crop and soil variables related to drought, to assimilate these variables into a simulation model at district scale and, finally, to estimate evapotranspiration, plant water status and drought indicators. A project Web home page, a technical course about DSS for the employers of irrigation authorities and dissemination of results (meetings, publications, reports), are also planned.

Measures of Microbial Biomass for Soil Carbon Decomposition Models

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Development, description, and application of a geographic information system data base for water resources in Karst Terrane in Greene County, Missouri. Water resources investigation

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

Waite, L.A.; Thomson, K.C.

1993-12-31

A geographic information system data base was developed for Greene County, Missouri, to provide data for use in the planning for the protection of water resources. The data base contains the following map layers: geology, cave entrances and passages, county and quadrangle boundary, dye traces, faults, geographic names, hypsography, hydrography, lineaments. Ozark aquifer potentiometric surface, public land survey system, sinkholes, soils, springs, and transportation.

Research on the Effects of Drying Temperature on Nitrogen Detection of Different Soil Types by Near Infrared Sensors.

PubMed

Nie, Pengcheng; Dong, Tao; He, Yong; Xiao, Shupei

2018-01-29

Soil is a complicated system whose components and mechanisms are complex and difficult to be fully excavated and comprehended. Nitrogen is the key parameter supporting plant growth and development, and is the material basis of plant growth as well. An accurate grasp of soil nitrogen information is the premise of scientific fertilization in precision agriculture, where near infrared sensors are widely used for rapid detection of nutrients in soil. However, soil texture, soil moisture content and drying temperature all affect soil nitrogen detection using near infrared sensors. In order to investigate the effects of drying temperature on the nitrogen detection in black soil, loess and calcium soil, three kinds of soils were detected by near infrared sensors after 25 °C placement (ambient temperature), 50 °C drying (medium temperature), 80 °C drying (medium-high temperature) and 95 °C drying (high temperature). The successive projections algorithm based on multiple linear regression (SPA-MLR), partial least squares (PLS) and competitive adaptive reweighted squares (CARS) were used to model and analyze the spectral information of different soil types. The predictive abilities were assessed using the prediction correlation coefficients (R P ), the root mean squared error of prediction (RMSEP), and the residual predictive deviation (RPD). The results showed that the loess (R P = 0.9721, RMSEP = 0.067 g/kg, RPD = 4.34) and calcium soil (R P = 0.9588, RMSEP = 0.094 g/kg, RPD = 3.89) obtained the best prediction accuracy after 95 °C drying. The detection results of black soil (R P = 0.9486, RMSEP = 0.22 g/kg, RPD = 2.82) after 80 °C drying were the optimum. In conclusion, drying temperature does have an obvious influence on the detection of soil nitrogen by near infrared sensors, and the suitable drying temperature for different soil types was of great significance in enhancing the detection accuracy.

Estimating of Soil Texture Using Landsat Imagery: a Case Study in Thatta Tehsil, Sindh

NASA Astrophysics Data System (ADS)

Khalil, Zahid

2016-07-01

Soil texture is considered as an important environment factor for agricultural growth. It is the most essential part for soil classification in large scale. Today the precise soil information in large scale is of great demand from various stakeholders including soil scientists, environmental managers, land use planners and traditional agricultural users. With the increasing demand of soil properties in fine scale spatial resolution made the traditional laboratory methods inadequate. In addition the costs of soil analysis with precision agriculture systems are more expensive than traditional methods. In this regard, the application of geo-spatial techniques can be used as an alternative for examining soil analysis. This study aims to examine the ability of Geo-spatial techniques in identifying the spatial patterns of soil attributes in fine scale. Around 28 samples of soil were collected from the different areas of Thatta Tehsil, Sindh, Pakistan for analyzing soil texture. An Ordinary Least Square (OLS) regression analysis was used to relate the reflectance values of Landsat8 OLI imagery with the soil variables. The analysis showed there was a significant relationship (p<0.05) of band 2 and 5 with silt% (R2 = 0.52), and band 4 and 6 with clay% (R2 =0.40). The equation derived from OLS analysis was then used for the whole study area for deriving soil attributes. The USDA textural classification triangle was implementing for the derivation of soil texture map in GIS environment. The outcome revealed that the 'sandy loam' was in great quantity followed by loam, sandy clay loam and clay loam. The outcome shows that the Geo-spatial techniques could be used efficiently for mapping soil texture of a larger area in fine scale. This technology helped in decreasing cost, time and increase detailed information by reducing field work to a considerable level.

A user need study and system plan for an Arizona Natural Resources Information System report to the Arizona state legislature

NASA Technical Reports Server (NTRS)

1980-01-01

A survey instrument was developed and implemented in order to evaluate the current needs for natural resource information in Arizona and to determine which state agencies have information systems capable of coordinating, accessing and analyzing the data. Data and format requirements were determined for the following categories: air quality, animals, cultural resources, geology, land use, soils, water, vegetation, ownership, and social and economic aspects. Hardware and software capabilities were assessed and a data processing plan was developed. Possible future applications with the next generation LANDSAT were also identified.

Particle-size distribution models for the conversion of Chinese data to FAO/USDA system.

PubMed

Shangguan, Wei; Dai, YongJiu; García-Gutiérrez, Carlos; Yuan, Hua

2014-01-01

We investigated eleven particle-size distribution (PSD) models to determine the appropriate models for describing the PSDs of 16349 Chinese soil samples. These data are based on three soil texture classification schemes, including one ISSS (International Society of Soil Science) scheme with four data points and two Katschinski's schemes with five and six data points, respectively. The adjusted coefficient of determination r (2), Akaike's information criterion (AIC), and geometric mean error ratio (GMER) were used to evaluate the model performance. The soil data were converted to the USDA (United States Department of Agriculture) standard using PSD models and the fractal concept. The performance of PSD models was affected by soil texture and classification of fraction schemes. The performance of PSD models also varied with clay content of soils. The Anderson, Fredlund, modified logistic growth, Skaggs, and Weilbull models were the best.

Characterizing Mediterranean Land Surfaces as Component of the Regional Climate System by Remote Sensing

NASA Technical Reports Server (NTRS)

Bolle, H.-J.; Koslowsky, D.; Menenti, M.; Nerry, F.; Otterman, Joseph; Starr, D.

1998-01-01

Extensive areas in the Mediterranean region are subject to land degradation and desertification. The high variability of the coupling between the surface and the atmosphere affects the regional climate. Relevant surface characteristics, such as spectral reflectance, surface emissivity in the thermal-infrared region, and vegetation indices, serve as "primary" level indicators for the state of the surface. Their spatial, seasonal and interannual variability can be monitored from satellites. Using relationships between these primary data and combining them with prior information about the land surfaces (such as topography, dominant soil type, land use, collateral ground measurements and models), a second layer of information is built up which specifies the land surfaces as a component of the regional climate system. To this category of parameters which are directly involved in the exchange of energy, momentum and mass between the surface and the atmosphere, belong broadband albedo, thermodynamic surface temperature, vegetation types, vegetation cover density, soil top moisture, and soil heat flux. Information about these parameters finally leads to the computation of sensible and latent heat fluxes. The methodology was tested with pilot data sets. Full resolution, properly calibrated and normalized NOAA-AVHRR multi-annual primary data sets are presently compiled for the whole Mediterranean area, to study interannual variability and longer term trends.

Spatial structure of soil properties at different scales of Mt. Kilimanjaro, Tanzania

NASA Astrophysics Data System (ADS)

Kühnel, Anna; Huwe, Bernd

2013-04-01

Soils of tropical mountain ecosystems provide important ecosystem services like water and carbon storage, water filtration and erosion control. As these ecosystems are threatened by global warming and the conversion of natural to human-modified landscapes, it is important to understand the implications of these changes. Within the DFG Research Unit "Kilimanjaro ecosystems under global change: Linking biodiversity, biotic interactions and biogeochemical ecosystem processes", we study the spatial heterogeneity of soils and the available water capacity for different land use systems. In the savannah zone of Mt. Kilimanjaro, maize fields are compared to natural savannah ecosystems. In the lower montane forest zone, coffee plantations, traditional home gardens, grasslands and natural forests are studied. We characterize the soils with respect to soil hydrology, emphasizing on the spatial variability of soil texture and bulk density at different scales. Furthermore soil organic carbon and nitrogen, cation exchange capacity and the pH-value are measured. Vis/Nir-Spectroscopy is used to detect small scale physical and chemical heterogeneity within soil profiles, as well as to get information of soil properties on a larger scale. We aim to build a spectral database for these soil properties for the Kilimanjaro region in order to get rapid information for geostatistical analysis. Partial least square regression with leave one out cross validation is used for model calibration. Results for silt and clay content, as well as carbon and nitrogen content are promising, with adjusted R² ranging from 0.70 for silt to 0.86 for nitrogen. Furthermore models for other nutrients, cation exchange capacity and available water capacity will be calibrated. We compare heterogeneity within and across the different ecosystems and state that spatial structure characteristics and complexity patterns in soil parameters can be quantitatively related to biodiversity and functional diversity parameters.

ESA's Soil Moisture dnd Ocean Salinity Mission - Contributing to Water Resource Management

NASA Astrophysics Data System (ADS)

Mecklenburg, S.; Kerr, Y. H.

2015-12-01

The Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which affects large-scale processes of the Earth's climate system. The focus of this paper will be on SMOS's contribution to support water resource management: SMOS surface soil moisture provides the input to derive root-zone soil moisture, which in turn provides the input for the drought index, an important monitoring prediction tool for plant available water. In addition to surface soil moisture, SMOS also provides observations on vegetation optical depth. Both parameters aid agricultural applications such as crop growth, yield forecasting and drought monitoring, and provide input for carbon and land surface modelling. SMOS data products are used in data assimilation and forecasting systems. Over land, assimilating SMOS derived information has shown to have a positive impact on applications such as NWP, stream flow forecasting and the analysis of net ecosystem exchange. Over ocean, both sea surface salinity and severe wind speed have the potential to increase the predictive skill on the seasonal and short- to medium-range forecast range. Operational users in particular in Numerical Weather Prediction and operational hydrology have put forward a requirement for soil moisture data to be available in near-real time (NRT). This has been addressed by developing a fast retrieval for a NRT level 2 soil moisture product based on Neural Networks, which will be available by autumn 2015. This paper will focus on presenting the above applications and used SMOS data products.

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.

Better to Be Active (Rather Than Passive) When Considering How Soil Moisture Can Help Decision Makers

NASA Astrophysics Data System (ADS)

Mace, R.

2016-12-01

As recent events have shown, Texas is a land of drought and flood. Texas experienced the worst one-year drought of record in 2011; the second worst statewide drought of record between 2010 and 2015; and record-breaking floods in the spring of 2015, fall of 2015, and spring of 2016 (with flash droughts occurring during the summers of 2015 and 2016). Soil moisture is one factor that links drought and flood in addressing key policy and management questions: When will soil moisture be high enough to allow groundwater recharge and runoff into reservoirs? When will soil moisture be high enough to cause flash floods with excessive rainfall? After tragic floods in Wimberley in the spring of 2015, Texas is expanding its stream-flow monitoring capabilities and is starting a statewide mesonet called TexMesonet to provide more detailed weather information to flood forecasters but also to provide baseline information on soil moisture for flood, drought, and water conservation purposes. Our hope is that the TexMesonet will help ground-truth SMAP and other remote sensing systems, help improve the National Water Model (a next generation tool for flood forecasting), and spark research into sub-basin soil moisture predictors of runoff which break water-supply droughts or lead to major floods.

Satellite Based Soil Moisture Product Validation Using NOAA-CREST Ground and L-Band Observations

NASA Astrophysics Data System (ADS)

Norouzi, H.; Campo, C.; Temimi, M.; Lakhankar, T.; Khanbilvardi, R.

2015-12-01

Soil moisture content is among most important physical parameters in hydrology, climate, and environmental studies. Many microwave-based satellite observations have been utilized to estimate this parameter. The Advanced Microwave Scanning Radiometer 2 (AMSR2) is one of many remotely sensors that collects daily information of land surface soil moisture. However, many factors such as ancillary data and vegetation scattering can affect the signal and the estimation. Therefore, this information needs to be validated against some "ground-truth" observations. NOAA - Cooperative Remote Sensing and Technology (CREST) center at the City University of New York has a site located at Millbrook, NY with several insitu soil moisture probes and an L-Band radiometer similar to Soil Moisture Passive and Active (SMAP) one. This site is among SMAP Cal/Val sites. Soil moisture information was measured at seven different locations from 2012 to 2015. Hydra probes are used to measure six of these locations. This study utilizes the observations from insitu data and the L-Band radiometer close to ground (at 3 meters height) to validate and to compare soil moisture estimates from AMSR2. Analysis of the measurements and AMSR2 indicated a weak correlation with the hydra probes and a moderate correlation with Cosmic-ray Soil Moisture Observing System (COSMOS probes). Several differences including the differences between pixel size and point measurements can cause these discrepancies. Some interpolation techniques are used to expand point measurements from 6 locations to AMSR2 footprint. Finally, the effect of penetration depth in microwave signal and inconsistencies with other ancillary data such as skin temperature is investigated to provide a better understanding in the analysis. The results show that the retrieval algorithm of AMSR2 is appropriate under certain circumstances. This validation algorithm and similar study will be conducted for SMAP mission. Keywords: Remote Sensing, Soil Moisture, AMSR2, SMAP, L-Band.

Impacts of Repeated Glyphosate Use on Wheat-Associated Bacteria Are Small and Depend on Glyphosate Use History

PubMed Central

Schlatter, Daniel C.; Yin, Chuntao; Hulbert, Scot; Burke, Ian

2017-01-01

ABSTRACT Glyphosate is the most widely used herbicide worldwide and a critical tool for weed control in no-till cropping systems. However, there are concerns about the nontarget impacts of long-term glyphosate use on soil microbial communities. We investigated the impacts of repeated glyphosate treatments on bacterial communities in the soil and rhizosphere of wheat in soils with and without long-term history of glyphosate use. We cycled wheat in the greenhouse using soils from 4 paired fields under no-till (20+-year history of glyphosate) or no history of use. At each cycle, we terminated plants with glyphosate (2× the field rate) or by removing the crowns, and soil and rhizosphere bacterial communities were characterized. Location, cropping history, year, and proximity to the roots had much stronger effects on bacterial communities than did glyphosate, which only explained 2 to 5% of the variation. Less than 1% of all taxa were impacted by glyphosate, more in soils with a long history of use, and more increased than decreased in relative abundance. Glyphosate had minimal impacts on soil and rhizosphere bacteria of wheat, although dying roots after glyphosate application may provide a “greenbridge” favoring some copiotrophic taxa. IMPORTANCE Glyphosate (Roundup) is the most widely used herbicide in the world and the foundation of Roundup Ready soybeans, corn, and the no-till cropping system. However, there have been recent concerns about nontarget impacts of glyphosate on soil microbes. Using next-generation sequencing methods and glyphosate treatments of wheat plants, we described the bacterial communities in the soil and rhizosphere of wheat grown in Pacific Northwest soils across multiple years, different locations, and soils with different histories of glyphosate use. The effects of glyphosate were subtle and much less than those of drivers such as location and cropping systems. Only a small percentage of the bacterial groups were influenced by glyphosate, and most of those were stimulated, probably because of the dying roots. This study provides important information for the future of this important tool for no-till systems and the environmental benefits of reducing soil erosion and fossil fuel inputs. PMID:28864656

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.

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Crow, Wade T.; Thorp, Kelly R.; Moran, Mary S.; Reichle, Rolf H.; Gupta, Hoshin V.

2012-01-01

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Quantitative mapping of solute accumulation in a soil-root system by magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Haber-Pohlmeier, S.; Vanderborght, J.; Pohlmeier, A.

2017-08-01

Differential uptake of water and solutes by plant roots generates heterogeneous concentration distributions in soils. Noninvasive observations of root system architecture and concentration patterns therefore provide information about root water and solute uptake. We present the application of magnetic resonance imaging (MRI) to image and monitor root architecture and the distribution of a tracer, GdDTPA2- (Gadolinium-diethylenetriaminepentacetate) noninvasively during an infiltration experiment in a soil column planted with white lupin. We show that inversion recovery preparation within the MRI imaging sequence can quantitatively map concentrations of a tracer in a complex root-soil system. Instead of a simple T1 weighting, the procedure is extended by a wide range of inversion times to precisely map T1 and subsequently to cover a much broader concentration range of the solute. The derived concentrations patterns were consistent with mass balances and showed that the GdDTPA2- tracer represents a solute that is excluded by roots. Monitoring and imaging the accumulation of the tracer in the root zone therefore offers the potential to determine where and by which roots water is taken up.

Measurement and Quantification of Heterogeneity, Flow, and Mass Transfer in Porous Media Using NMR Low-Field Techiques

NASA Astrophysics Data System (ADS)

Paciok, E.; Olaru, A. M.; Haber, A.; van Landeghem, M.; Haber-Pohlmeier, S.; Sucre, O. E.; Perlo, J.; Casanova, F.; Blümich, B.; RWTH Aachen Mobile Low-Field NMR

2011-12-01

Nuclear magnetic resonance (NMR) is renowned for its unique potential to both reveal and correlate spectroscopic, relaxometric, spatial and dynamic properties in a large variety of organic and inorganic systems. NMR has no restrictions regarding sample opacity and is an entirely non-invasive method, which makes it the ideal tool for the investigation of porous media. However, for years NMR research of soils was limited by the use of high-field NMR devices, which necessitated elaborate NMR experiments and were not applicable to bulky samples or on-site field measurements. The evolution of low-field NMR devices during the past 20 years has brought forth portable, small-scale NMR systems with open and closed magnet arrangements specialized to specific NMR applications. In combination with recent advances in 2D-NMR Laplace methodology [1], low-field NMR has opened up the possibility to study real-life microporous systems ranging from granular media to natural soils and oil well boreholes. Thus, information becomes available, which before has not been accessible with high-field NMR. In this work, we present our recent progress in mobile low-field NMR probe design for field measurements of natural soils: a slim-line logging tool, which can be rammed into the soil of interest on-site. The performance of the device is demonstrated in measurements of moisture profiles of model soils [2] and field measurements of relaxometric properties and moisture profiles of natural soils [3]. Moreover, an improved concept of the slim-line logging tool is shown, with a higher excitation volume and a better signal-to-noise due to an improved coil design. Furthermore, we present our recent results in 2D exchange relaxometry and simulation. These include relaxation-relaxation experiments on natural soils with varying degree of moisture saturation, where we could draw a connection between the relaxometric properties of the soil to its pore size-related diffusivity and to its clay content. Also models, simulations and possibilities are discussed to derive from the so obtained information a "characteristic pore shape" that can be used to characterize and to fingerprint natural soils. [1] L. Venkataramanan et al., IEEE Trans. Signal Process. 2002, 50, 1017-26. [2] O. Sucre et al., Open Magn. Reson. J. 2010, 3, 63-68. [3] B. Blümich et al., New J. Phys. 2011, 13, 015003.

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Remote sensing of physiographic soil units of Bennett County, South Dakota

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Gropper, J. L.; Westin, F. C.

1973-01-01

A study was conducted in Bennett County, South Dakota, to establish a rangeland test site for evaluating the usefulness of ERTS data for mapping soil resources in rangeland areas. Photographic imagery obtained in October, 1970, was analyzed to determine which type of imagery is best for mapping drainage and land use patterns. Imagery of scales ranging from 1:1,000,000 to 1.20,000 was used to delineate soil-vegetative physiographic units. The photo characteristics used to define physiographic units were texture, drainage pattern, tone pattern, land use pattern and tone. These units will be used as test data for evaluating ERTS data. The physiographic units were categorized into a land classification system. The various categories which were delineated at the different scales of imagery were designed to be useful for different levels of land use planning. The land systems are adequate only for planning of large areas for general uses. The lowest category separated was the facet. The facets have a definite soil composition and represent different soil landscapes. These units are thought to be useful for providing natural resource information needed for local planning.

Soil Structure - A Neglected Component of Land-Surface Models

NASA Astrophysics Data System (ADS)

Fatichi, S.; Or, D.; Walko, R. L.; Vereecken, H.; Kollet, S. J.; Young, M.; Ghezzehei, T. A.; Hengl, T.; Agam, N.; Avissar, R.

2017-12-01

Soil structure is largely absent in most standard sampling and measurements and in the subsequent parameterization of soil hydraulic properties deduced from soil maps and used in Earth System Models. The apparent omission propagates into the pedotransfer functions that deduce parameters of soil hydraulic properties primarily from soil textural information. Such simple parameterization is an essential ingredient in the practical application of any land surface model. Despite the critical role of soil structure (biopores formed by decaying roots, aggregates, etc.) in defining soil hydraulic functions, only a few studies have attempted to incorporate soil structure into models. They mostly looked at the effects on preferential flow and solute transport pathways at the soil profile scale; yet, the role of soil structure in mediating large-scale fluxes remains understudied. Here, we focus on rectifying this gap and demonstrating potential impacts on surface and subsurface fluxes and system wide eco-hydrologic responses. The study proposes a systematic way for correcting the soil water retention and hydraulic conductivity functions—accounting for soil-structure—with major implications for near saturated hydraulic conductivity. Modification to the basic soil hydraulic parameterization is assumed as a function of biological activity summarized by Gross Primary Production. A land-surface model with dynamic vegetation is used to carry out numerical simulations with and without the role of soil-structure for 20 locations characterized by different climates and biomes across the globe. Including soil structure affects considerably the partition between infiltration and runoff and consequently leakage at the base of the soil profile (recharge). In several locations characterized by wet climates, a few hundreds of mm per year of surface runoff become deep-recharge accounting for soil-structure. Changes in energy fluxes, total evapotranspiration and vegetation productivity are less significant but they can reach up to 10% in specific locations. Significance for land-surface and hydrological modeling and implications for distributed domains are discussed.

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

The International year of soils: thoughts on future directions for experiments in soil erosion research

NASA Astrophysics Data System (ADS)

Kuhn, Nikolaus J.

2015-04-01

The 2015 UN Year of Soils (IYS), implemented by the FAO, aims to increase awareness and understanding of the importance of soil for food security and essential ecosystem functions. The IYS has six specific objectives, ranging from raising the awareness among civil society and decision makers about the profound importance of soils, to the development of policies supporting the sustainable use of the non-renewable soil resource. For scientists and academic teachers using experiments to study soil erosion processes, two objectives appear of particular relevance. First is need for the rapid capacity enhancement for soil information collection and monitoring at all levels (global, regional and national). While at first glance, this objective appears to relate mostly to traditional mapping, sampling and monitoring, the threat of large-scale soil loss, at least with regards to their ecosystem services, illustrates the need for approaches of studying soils that avoids such irreversible destruction. Relying on often limited data and their extrapolation does not cover this need for soil information because rapid change of the drivers of change itself carry the risk of unprecedented soil reactions not covered by existing data sets. Experiments, on the other hand, offer the possibility to simulate and analyze future soil change in great detail. Furthermore, carefully designed experiments may also limit the actual effort involved in collecting the specific required information, e.g. by applying tests designed to study soil system behavior under controlled conditions, compared to field monitoring. For rainfall simulation, experiments should therefore involve the detailed study of erosion processes and include detailed recording and reporting of soil and rainfall properties. The development of a set of standardised rainfall simulations would widen the use data collected by such experiments. A second major area for rainfall simulation lies in the the education of the public about the crucial role soil plays in food security, climate change adaptation and mitigation, essential ecosystem services, poverty alleviation and sustainable development. While erosion monitoring and modeling, as well as erosion risk assessment maps provide a solid foundation for decision makers, the attention of the public for "dirt" is often much easier to achieve by setting up a rainfall simulation experiment that illustrates the connection between a process, such as rainfall and runoff observed in daily life, and its causes and consequences. Exploring the potential of rainfall simulation experiments as an outreach tool should therefore be part of the soil science, geomorphology and hydrology community during the IYS 2015 and beyond.

Soil and Crop management: Lessons from the laboratory biosphere 2002-2004

NASA Astrophysics Data System (ADS)

Silverstone, S.; Nelson, M.; Alling, A.; Allen, J.

During the years 2002 and 2003, three closed system experiments were carried out in the "Laboratory Biosphere" facility located in Santa Fe, New Mexico. The program involved experimentation with "Hoyt" Soy Beans, USU Apogee Wheat and TU-82-155 sweet potato using a 5.37 m2 soil planting bed which was 30 cm deep. The soil texture, 40% clay, 31% sand and 28% silt (a clay loam), was collected from an organic farm in New Mexico to avoid chemical residues. Soil management practices involved minimal tillage, mulching and returning crop residues to the soil after each experiment. Between experiment #2 and #3, the top 15 cm of the soil was amended using a mix of peat moss, green sand, humates and pumice to improve soil texture, lower soil pH and increase nutrient availability. Soil analyses for all three experiments are presented to show how the soils have changed with time and how the changes relate to crop selection and rotation, soil selection and management, water management and pest control. The experience and information gained from these experiments are being applied to the future design of the Mars On Earth facility.

Ground penetrating radar for asparagus detection

NASA Astrophysics Data System (ADS)

Seyfried, Daniel; Schoebel, Joerg

2016-03-01

Ground penetrating radar is a promising technique for detection of buried objects. Recently, radar has more and more been identified to provide benefits for a plurality of applications, where it can increase efficiency of operation. One of these fields is the industrial automatic harvesting process of asparagus, which is performed so far by cutting the soil ridge at a certain height including all the asparagus spears and subsequently sieving the latter out of the soil. However, the height where the soil is cut is a critical parameter, since a wrong value leads to either damage of the roots of the asparagus plants or to a reduced crop yield as a consequence of too much biomass remaining in the soil. In this paper we present a new approach which utilizes ground penetrating radar for non-invasive sensing in order to obtain information on the optimal height for cutting the soil. Hence, asparagus spears of maximal length can be obtained, while keeping the roots at the same time undamaged. We describe our radar system as well as the subsequent digital signal processing steps utilized for extracting the information required from the recorded radar data, which then can be fed into some harvesting unit for setting up the optimal cutting height.

Mapping soil erosion risk in Serra de Grândola (Portugal)

NASA Astrophysics Data System (ADS)

Neto Paixão, H. M.; Granja Martins, F. M.; Zavala, L. M.; Jordán, A.; Bellinfante, N.

2012-04-01

Geomorphological processes can pose environmental risks to people and economical activities. Information and a better knowledge of the genesis of these processes is important for environmental planning, since it allows to model, quantify and classify risks, what can mitigate the threats. The objective of this research is to assess the soil erosion risk in Serra de Grândola, which is a north-south oriented mountain ridge with an altitude of 383 m, located in southwest of Alentejo (southern Portugal). The study area is 675 km2, including the councils of Grândola, Santiago do Cacém and Sines. The process for mapping of erosive status was based on the guidelines for measuring and mapping the processes of erosion of coastal areas of the Mediterranean proposed by PAP/RAC (1997), developed and later modified by other authors in different areas. This method is based on the application of a geographic information system that integrates different types of spatial information inserted into a digital terrain model and in their derivative models. Erosive status are classified using information from soil erodibility, slope, land use and vegetation cover. The rainfall erosivity map was obtained using the modified Fournier index, calculated from the mean monthly rainfall, as recorded in 30 meteorological stations with influence in the study area. Finally, the soil erosion risk map was designed by ovelaying the erosive status map and the rainfall erosivity map.

Comparisons among a new soil index and other two- and four-dimensional vegetation indices

NASA Technical Reports Server (NTRS)

Wiegand, C. L.; Richardson, A. J. (Principal Investigator)

1982-01-01

The 2-D difference vegetation index (DVI) and perpendicular vegetation index (PVI), and the 4-D green vegetation index (GVI) are compared in LANDSAT MSS data from grain sorghum (Sorghum bicolor, L. Moench) fields for the years 1973 to 1977. PVI and DVI were more closely related to LAI than was GVI. A new 2-D soil line index (SLI), the vector distance from the soil line origin to the point of intersection of PVI with the soil line, is defined and compared with the 4-D soil brightness index, SBI. SLI (based on MSS and MSS7) and SL16 (based on MSS 5 and MSS 6) were smaller in magnitude than SBI but contained similar information about the soil background. These findings indicate that vegetation and soil indices calculated from the single visible and reflective infrared band sensor systems, such as the AVHRR of the TIROS-N polar orbiting series of satellites, will be meaningful for synoptic monitoring of renewable vegetation.

[Environmental behavior and effect of biomass-derived black carbon in soil: a review].

PubMed

Liu, Yu-Xue; Liu, Wei; Wu, Wei-Xiang; Zhong, Zhe-Ke; Chen, Ying-Xu

2009-04-01

Biomass-derived black carbon, also named biochar, has the characteristics of high stability against decay and high capability of adsorption, and can affect the environment through its interactions with climate and geology, playing a significant role in global climate change, carbon biogeochemical cycle, and environmental system. In recent years, more and more researchers in the fields of atmospheric sciences, geology, and environmental science focused on the environmental behavior and effect of biochar. As one possible source of the components with high aromatic structure in soil humus, biochar is of great importance in increasing soil carbon storage and improving soil fertility, and in maintaining the balance of soil ecosystem. This paper offered the latest information regarding the characteristics and biotic and abiotic oxidation mechanisms of biochar, its effects on global climate change, and the environmental effect of biochar in soil. Research prospects were briefly discussed on the environmental behavior and effect of biochar in soil ecosystem.

Coupling transfer function and GIS for assessing non-point-source groundwater vulnerability at regional scale

NASA Astrophysics Data System (ADS)

Coppola, A.; Comegna, V.; de Simone, L.

2009-04-01

Non-point source (NPS) pollution in the vadose zone is a global environmental problem. The knowledge and information required to address the problem of NPS pollutants in the vadose zone cross several technological and sub disciplinary lines: spatial statistics, geographic information systems (GIS), hydrology, soil science, and remote sensing. The main issues encountered by NPS groundwater vulnerability assessment, as discussed by Stewart [2001], are the large spatial scales, the complex processes that govern fluid flow and solute transport in the unsaturated zone, the absence of unsaturated zone measurements of diffuse pesticide concentrations in 3-D regional-scale space as these are difficult, time consuming, and prohibitively costly, and the computational effort required for solving the nonlinear equations for physically-based modeling of regional scale, heterogeneous applications. As an alternative solution, here is presented an approach that is based on coupling of transfer function and GIS modeling that: a) is capable of solute concentration estimation at a depth of interest within a known error confidence class; b) uses available soil survey, climatic, and irrigation information, and requires minimal computational cost for application; c) can dynamically support decision making through thematic mapping and 3D scenarios This result was pursued through 1) the design and building of a spatial database containing environmental and physical information regarding the study area, 2) the development of the transfer function procedure for layered soils, 3) the final representation of results through digital mapping and 3D visualization. One side GIS modeled environmental data in order to characterize, at regional scale, soil profile texture and depth, land use, climatic data, water table depth, potential evapotranspiration; on the other side such information was implemented in the up-scaling procedure of the Jury's TFM resulting in a set of texture based travel time probability density functions for layered soils each describing a characteristic leaching behavior for soil profiles with similar hydraulic properties. Such behavior, in terms of solute travel time to water table, was then imported back into GIS and finally estimation groundwater vulnerability for each soil unit was represented into a map as well as visualized in 3D.

CanSIS Regional Soils Data in Vector Format

NASA Technical Reports Server (NTRS)

Monette, Bryan; Knapp, David; Hall, Forrest G. (Editor)

2000-01-01

This data set is the original vector data set received from Canada Soil Information System (CanSIS). The data include the provinces of Saskatchewan and Manitoba. Attribute tables provide the various soil data for the polygons; there is one attribute table for Saskatchewan and one for Manitoba. The data are stored in ARC/INFO export format files. Based on agreements made with Agriculture Canada, these data are available only to individuals and groups that have an official relationship with the BOREAS project. These data are not included on the BOReal Ecosystem-Atmosphere Study (BOREAS) CD-ROM set. A raster version of this data set titled 'BOREAS Regional Soils Data in Raster Format and AEAC Projection' is publicly available and is included on the BOREAS CD-ROM set.

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.

Comprehensive assessment of regional selenium resources in soils based on the analytic hierarchy process: Assessment system construction and case demonstration.

PubMed

Liang, Ruoyu; Song, Shuai; Shi, Yajing; Shi, Yajuan; Lu, Yonglong; Zheng, Xiaoqi; Xu, Xiangbo; Wang, Yurong; Han, Xuesong

2017-12-15

The redundancy or deficiency of selenium in soils can cause adverse effects on crops and even threaten human health. It was necessary to assess selenium resources with a rigorous scientific appraisal. Previous studies of selenium resource assessment were usually carried out using a single index evaluation. A multi-index evaluation method (analytic hierarchy process) was used in this study to establish a comprehensive assessment system based on consideration of selenium content, soil nutrients and soil environmental quality. The criteria for the comprehensive assessment system were classified by summing critical values in the standards with weights and a Geographical Information System was used to reflect the regional distribution of the assessment results. Boshan, a representative region for developing selenium-rich agriculture, was taken as a case area and classified into Zone I-V, which suggested priority areas for developing selenium-rich agriculture. Most parts of the North and Midlands of Boshan were relatively suitable for development of selenium-rich agriculture. Soils in south fractions were contaminated by Cd, PAHs, HCHs and DDTs, in which it was forbidden to farm. This study was expected to provide the basis for developing selenium-rich agriculture and an example for comprehensive evaluation of relevant resources in a region. Copyright © 2017 Elsevier B.V. All rights reserved.

The Effect of Five Biomass Cropping Systems on Soil-Saturated Hydraulic Conductivity Across a Topographic Gradient

Treesearch

Usman Anwar; Lisa A. Schulte; Matthew Helmers; Randall K. Kolka

2017-01-01

Understanding the environmental impact of bioenergy crops is needed to inform bioenergy policy development. We determined the effects of five biomass cropping systems—continuous maize (Zea mays), soybean (Glycine max)-triticale (Triticosecale ×)/soybean-maize, maize-switchgrass (Panicum virgatum...

Center pivot mounted infrared sensors: Retrieval of ET and interface with satellite systems

USDA-ARS?s Scientific Manuscript database

Infrared sensors mounted aboard cener pivot irrigation systems can remotely sense the surface temperatures of the crops and soils, which provides important information on crop water status. This can be used for irrigation management and irrigation automation, which can increase crop water productivi...

Soilcrust Links

Science.gov Websites

Soil Crust Home Crust 101 Advanced Gallery References CCERS Site Links updated: April 24, 2006 /soils.htm This site has information on soil crusts, as well other information about the park. Biological Soil Crusts - Webs of Life in the Desert Two page, color handout on biological soils crusts. (303k PDF

Soil information in the Strategic Environmental Assessment of Rural Development Plans

NASA Astrophysics Data System (ADS)

Costantini, Edoardo

2016-04-01

Soil information is essential for land planning at different administrative levels. Currently, in Europe there is a hierarchy of at least seven main territorial administrative entities which consider soil in their land planning policies. In this study, European, national and regional regulations that affect soil are discussed, considering themes, priorities, and focus areas. A better attention on the Strategic Environmental Assessment (SEA) of the Rural Development Plans (RDP) 2014-2020 is given, by analysing the Environmental Reports produced in the framework of the SEA of the RDP 2014-2020 of some European Regions. Both old and new soil indicators are introduced, as well as the consequences of their adoption for soil science and soil scientists. It is evident from this study that soil information is treated very variably, not only because of the different kinds of available information, but mainly as a consequence of the expertise and sensitivity to the soil issues of the authors, since they can be different kinds of public or private bodies hired by regional authorities. Therefore, despite having the same reference, the SEAs are very different. In most cases, the amount of soil information is little or negligible, even when available. The ex-ante impacts are often only qualitative, or quantified only in terms of the areal extent of applied measures. On the other hand, following the European recommendations, the ongoing and ex-post reports of the monitoring activities of RDP are expected to provide a wealth of soil information, both qualitative and quantitative. Soil scientists, soil and water conservationists, and management experts will be requested to provide more sophisticated and dynamic types of information. Therefore, the SEA of RDP and similar land planning activities will provide greater scientific and technical opportunities for soil science, provided that the public bodies in charge of evaluations, namely Member States, Regions and their auditing counterparts within the European Commission, are able to implement their own recommendations.

Detection and monitoring of volatile and semivolatile pollutants in soil through different sensing strategies

NASA Astrophysics Data System (ADS)

De Cesare, Fabrizio; Macagnano, Antonella

2013-04-01

Pollutants in environments are more and more threatening the maintenance of health of habitats and their inhabitants. A proper evaluation of the impact of contaminants from several different potential sources on soil quality and health and then on organisms living therein, and the possible and sometime probable related risk of transfer of pollutants, with their toxic effects, to organisms living in different environmental compartments, through the trophic chain up to humans is strongly required by decision makers, in order to promptly take adequate actions to prevent environmental and health damages and monitor the exposure rate of individuals to toxicants. Then, a reliable detection of pollutants in environments and the monitoring of dynamics and fate of contaminants therein are of utmost importance to achieve this goal. In soil, chemical and physical techniques to detect pollutants have been well known for decades, but can often drive to both over- and underestimations of the actual bioavailable (and then toxic) fraction of contaminants, and then of the real risk for organisms, deriving from their presence therein. The use of bioindicators (both living organisms and enzyme activities somehow derived from them) can supply more reliable information about the quantification of the bioavailable fraction of soil pollutants. In the last decades, a physicochemical technique, such as SPME (solid phase microextraction) followed by GC-MS analysis, has been demonstrated to provide similar results to those obtained from some pedofaunal populations, used as bioindicators, as concerns the bioavailable pollutant quantification in soil. More recently, we have applied a sensing technology, namely electronic nose (EN), which comprises several unspecific sensors arranged in an array and that is capable of providing more qualitative than quantitative information about complex air samples, to the study of soils contaminated with semivolatile (SVOCs) pollutants, such as polycyclic aromatic hydrocarbons (PAHs). The EN device set up on purpose involved suitable sensors and it was demonstrated to be capable of supplying information related to the whole soil environment as well as to the presence of contaminants and their dynamics, such as their biodegradation by soil microorganisms and the contemporary increase of CO2 release. These results were also somehow related to those obtained through SPME-GC/MS analyses, since a list of substances could be identified to be responsible for the different classification of contaminated and uncontaminated soil samples obtained through EN. Presently, we also have got evidences that more complex sensing devices can be used for in situ monitoring of contaminated soils. We have designed and fabricated a multi-parametric hybrid sensing system, based on the assembly of several different sensors and sensing systems (i.e. single sensors and a sensor array), some of which are commercially available, while some others were created by design in laboratory and tested for their specificity. The main target of such a hybrid sensing device was to be capable of measuring various soil parameters and volatile pollutants (VOCs) in soil, such as BTEX (benzene, toluene, ethylbenzene and xylene), in order to relate the quantification and behaviour of contaminants in soil (e.g. solubility, volatility, phase partitioning, adsorption and desorption, etc.) to the relative environmental conditions, by measuring physical (temperature and moisture) and chemical (pH) parameters, which can affect such processes. Furthermore, a suitable procedure was set up on purpose to provide VOCs quantifications actually related to the bioavailable fraction of pollutants (passive vs. active sampling). That sensing system was also set up for a wireless communication of the recorded values to a data-collecting centre. Such a tool was designed to be used as a proper probe to insert into soil for in situ monitoring of contaminated sites in order to provide semi-continuous information about soil pollution conditions and evolutions, suitable for unskilled employees, on the basis of three different levels of contaminations and alarms. That probe might be then a suitable tool for decision makers about environmental risk assessment. Finally, an EN device has also been recently applied to detect microbial activity and biomass in soil. Then, the described sensing strategies might be successfully used to both monitor the presence of pollutants and their dynamics during and after remediation processes, in order to validate the effectiveness of the specific techniques applied in contaminated sites, and evaluate the recovery of soil metabolic activities and active microbial biomass.

Effect of water content and organic carbon on remote sensing of crop residue cover

NASA Astrophysics Data System (ADS)

Serbin, G.; Hunt, E. R., Jr.; Daughtry, C. S. T.; McCarty, G. W.; Brown, D. J.; Doraiswamy, P. C.

2009-04-01

Crop residue cover is an important indicator of tillage method. Remote sensing of crop residue cover is an attractive and efficient method when compared with traditional ground-based methods, e.g., the line-point transect or windshield survey. A number of spectral indices have been devised for residue cover estimation. Of these, the most effective are those in the shortwave infrared portion of the spectrum, situated between 1950 and 2500 nm. These indices include the hyperspectral Cellulose Absorption Index (CAI), and advanced multispectral indices, i.e., the Lignin-Cellulose Absorption (LCA) index and the Shortwave Infrared Normalized Difference Residue Index (SINDRI), which were devised for the NASA Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor. Spectra of numerous soils from U.S. Corn Belt (Indiana and Iowa) were acquired under wetness conditions varying from saturation to oven-dry conditions. The behavior of soil reflectance with water content was also dependent on the soil organic carbon content (SOC) of the soils, and the location of the spectral bands relative to significant water absorptions. High-SOC soils showed the least change in spectral index values with increase in soil water content. Low-SOC soils, on the other hand, showed measurable difference. For CAI, low-SOC soils show an initial decrease in index value followed by an increase, due to the way that water content affects CAI spectral bands. Crop residue CAI values decrease with water content. For LCA, water content increases decrease crop residue index values and increase them for soils, resulting in decreased contrast. SINDRI is also affected by SOC and water content. As such, spatial information on the distribution of surface soil water content and SOC, when used in a geographic information system (GIS), will improve the accuracy of remotely-sensed crop residue cover estimates.

Soil properties, soil functions and soil security

NASA Astrophysics Data System (ADS)

Poggio, Laura; Gimona, Alessandro

2017-04-01

Soil plays a crucial role in the ecosystem functioning such as food production, capture and storage of water, carbon and nutrients and in the realisation of a number of UN Sustainable Developments Goals. In this work we present an approach to spatially and jointly assess the multiple contributions of soil to the delivery of ecosystem services within multiple land-use system. We focussed on the modelling of the impact of soil on sediment retention, carbon storage, storing and filtering of nutrients, habitat for soil organisms and water regulation, taking into account examples of land use and climate scenarios. Simplified models were used for the single components. Spatialised Bayesian Belief networks were used for the jointly assessment and mapping of soil contribution to multiple land use and ecosystem services. We integrated continuous 3D soil information derived from digital soil mapping approaches covering the whole of mainland Scotland, excluding the Northern Islands. Uncertainty was accounted for and propagated across the whole process. The Scottish test case highlights the differences in roles between mineral and organic soils and provides an example of integrated study assessing the contributions of soil. The results show the importance of the multi-functional analysis of the contribution of soils to the ecosystem service delivery and UN SDGs.

Soil and crop management experiments in the Laboratory Biosphere: an analogue system for the Mars on Earth(R) facility.

PubMed

Silverstone, S; Nelson, M; Alling, A; Allen, J P

2005-01-01

During the years 2002 and 2003, three closed system experiments were carried out in the "Laboratory Biosphere" facility located in Santa Fe, New Mexico. The program involved experimentation of "Hoyt" Soy Beans, (experiment #1) USU Apogee Wheat (experiment #2) and TU-82-155 sweet potato (experiment #3) using a 5.37 m2 soil planting bed which was 30 cm deep. The soil texture, 40% clay, 31% sand and 28% silt (a clay loam), was collected from an organic farm in New Mexico to avoid chemical residues. Soil management practices involved minimal tillage, mulching, returning crop residues to the soil after each experiment and increasing soil biota by introducing worms, soil bacteria and mycorrhizae fungi. High soil pH of the original soil appeared to be a factor affecting the first two experiments. Hence, between experiments #2 and #3, the top 15 cm of the soil was amended using a mix of peat moss, green sand, humates and pumice to improve soil texture, lower soil pH and increase nutrient availability. This resulted in lowering the initial pH of 8.0-6.7 at the start of experiment #3. At the end of the experiment, the pH was 7.6. Soil nitrogen and phosphorus has been adequate, but some chlorosis was evident in the first two experiments. Aphid infestation was the only crop pest problem during the three experiments and was handled using an introduction of Hyppodamia convergens. Experimentation showed there were environmental differences even in this 1200 cubic foot ecological system facility, such as temperature and humidity gradients because of ventilation and airflow patterns which resulted in consequent variations in plant growth and yield. Additional humidifiers were added to counteract low humidity and helped optimize conditions for the sweet potato experiment. The experience and information gained from these experiments are being applied to the future design of the Mars On Earth(R) facility (Silverstone et al., Development and research program for a soil-based bioregenerative agriculture system to feed a four person crew at a Mars base, Advances in Space Research 31(1) (2003) 69-75; Allen and Alling, The design approach for Mars On Earth(R), a biospheric closed system testing facility for long-term space habitation, American Institute of Aeronautics and Astronautics Inc., IAC-02-IAA.8.2.02, 2002). c2005 Published by Elsevier Ltd on behalf of COSPAR.

Accumulation, interaction and fractionation of fluoride and cadmium in sierozem and oilseed rape (Brassica napus L.) in northwest China.

PubMed

Li, Yepu; Wang, Shengli; Zhang, Qian; Zang, Fei; Nan, Zhongren; Sun, Huiling; Huang, Wen; Bao, Lili

2018-06-01

Soil fluoride (F) and cadmium (Cd) pollution are of great concern in recently years, due to the fact that considerable amounts of wastewater, gas and residue, containing F and Cd, have been discharged into the environment through ore smelting. Soil F and Cd contamination may result in their interaction in soil and plant, which affects their fractionation distribution in soil and accumulation in oilseed rape. Oilseed rape, which is widely planted and consumed as a popular vegetable in arid and semi-arid land of northwest China, has been believed to a hyperaccumulator for Cd. However, there is limited information about the accumulation, interaction and fractionation of F and Cd in soil-oilseed rape system under F-Cd stresses. A pot-culture experiment, with single (F or Cd) or double elements (F-Cd) being added to soil, was carried out study the accumulation, interaction and fractionation of F and Cd in sierozem and oilseed rape. We found that soil F applications increased the contents of Cd in exchangeable fraction (EX-Cd), the bound to carbonate fraction (CAB-Cd) and the bound to iron and manganese oxides fraction (FMO-Cd) in soil and also increased plant Cd accumulation. Therefore, we suggest that the permitted level of F should be confined within soil quality standards for farmland of China in order to upset the effect of high F concentration on bioavailability of soil Cd. However, soil Cd applications showed negative effects on the content of F in water soluble fraction (Water-F), hence decreased plant F accumulation. A better understanding of the accumulation, interaction and fractionation of F and Cd in sierozem-oilseed rape system are of great importance for environmental protection and for human health. The present study may serve as a basic understanding of the accumulation, interaction and fractionation of F and Cd in sierozem-oilseed rape system, and provide a suggestion for the environmental management. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Investigating Soil Moisture Feedbacks on Precipitation With Tests of Granger Causality

NASA Astrophysics Data System (ADS)

Salvucci, G. D.; Saleem, J. A.; Kaufmann, R.

2002-05-01

Granger causality (GC) is used in the econometrics literature to identify the presence of one- and two-way coupling between terms in noisy multivariate dynamical systems. Here we test for the presence of GC to identify a soil moisture (S) feedback on precipitation (P) using data from Illinois. In this framework S is said to Granger cause P if F(Pt;At-dt)does not equal F(P;(A-S)t-dt) where F denotes the conditional distribution of P at time t, At-dt represents the set of all knowledge available at time t-dt, and (A-S)t-dt represents all knowledge available at t-dt except S. Critical for land-atmosphere interaction research is that At-dt includes all past information on P as well as S. Therefore that part of the relation between past soil moisture and current precipitation which results from precipitation autocorrelation and soil water balance will be accounted for and not attributed to causality. Tests for GC usually specify all relevant variables in a coupled vector autoregressive (VAR) model and then calculate the significance level of decreased predictability as various coupling coefficients are omitted. But because the data (daily precipitation and soil moisture) are distinctly non-Gaussian, we avoid using a VAR and instead express the daily precipitation events as a Markov model. We then test whether the probability of storm occurrence, conditioned on past information on precipitation, changes with information on soil moisture. Past information on precipitation is expressed both as the occurrence of previous day precipitation (to account for storm-scale persistence) and as a simple soil moisture-like precipitation-wetness index derived solely from precipitation (to account for seasonal-scale persistence). In this way only those fluctuations in moisture not attributable to past fluctuations in precipitation (e.g., those due to temperature) can influence the outcome of the test. The null hypothesis (no moisture influence) is evaluated by comparing observed changes in storm probability to Monte-Carlo simulated differences generated with unconditional occurrence probabilities. The null hypothesis is not rejected (p>0.5) suggesting that contrary to recently published results, insufficient evidence exists to support an influence of soil moisture on precipitation in Illinois.

Effects of climate change on the delivery of soil-mediated ecosystem services within the primary sector in temperate ecosystems: a review and New Zealand case study.

PubMed

Orwin, Kate H; Stevenson, Bryan A; Smaill, Simeon J; Kirschbaum, Miko U F; Dickie, Ian A; Clothier, Brent E; Garrett, Loretta G; van der Weerden, Tony J; Beare, Michael H; Curtin, Denis; de Klein, Cecile A M; Dodd, Michael B; Gentile, Roberta; Hedley, Carolyn; Mullan, Brett; Shepherd, Mark; Wakelin, Steven A; Bell, Nigel; Bowatte, Saman; Davis, Murray R; Dominati, Estelle; O'Callaghan, Maureen; Parfitt, Roger L; Thomas, Steve M

2015-08-01

Future human well-being under climate change depends on the ongoing delivery of food, fibre and wood from the land-based primary sector. The ability to deliver these provisioning services depends on soil-based ecosystem services (e.g. carbon, nutrient and water cycling and storage), yet we lack an in-depth understanding of the likely response of soil-based ecosystem services to climate change. We review the current knowledge on this topic for temperate ecosystems, focusing on mechanisms that are likely to underpin differences in climate change responses between four primary sector systems: cropping, intensive grazing, extensive grazing and plantation forestry. We then illustrate how our findings can be applied to assess service delivery under climate change in a specific region, using New Zealand as an example system. Differences in the climate change responses of carbon and nutrient-related services between systems will largely be driven by whether they are reliant on externally added or internally cycled nutrients, the extent to which plant communities could influence responses, and variation in vulnerability to erosion. The ability of soils to regulate water under climate change will mostly be driven by changes in rainfall, but can be influenced by different primary sector systems' vulnerability to soil water repellency and differences in evapotranspiration rates. These changes in regulating services resulted in different potentials for increased biomass production across systems, with intensively managed systems being the most likely to benefit from climate change. Quantitative prediction of net effects of climate change on soil ecosystem services remains a challenge, in part due to knowledge gaps, but also due to the complex interactions between different aspects of climate change. Despite this challenge, it is critical to gain the information required to make such predictions as robust as possible given the fundamental role of soils in supporting human well-being. © 2015 John Wiley & Sons Ltd.

Pedoinformatics Approach to Soil Text Analytics

NASA Astrophysics Data System (ADS)

Furey, J.; Seiter, J.; Davis, A.

2017-12-01

The several extant schema for the classification of soils rely on differing criteria, but the major soil science taxonomies, including the United States Department of Agriculture (USDA) and the international harmonized World Reference Base for Soil Resources systems, are based principally on inferred pedogenic properties. These taxonomies largely result from compiled individual observations of soil morphologies within soil profiles, and the vast majority of this pedologic information is contained in qualitative text descriptions. We present text mining analyses of hundreds of gigabytes of parsed text and other data in the digitally available USDA soil taxonomy documentation, the Soil Survey Geographic (SSURGO) database, and the National Cooperative Soil Survey (NCSS) soil characterization database. These analyses implemented iPython calls to Gensim modules for topic modelling, with latent semantic indexing completed down to the lowest taxon level (soil series) paragraphs. Via a custom extension of the Natural Language Toolkit (NLTK), approximately one percent of the USDA soil series descriptions were used to train a classifier for the remainder of the documents, essentially by treating soil science words as comprising a novel language. While location-specific descriptors at the soil series level are amenable to geomatics methods, unsupervised clustering of the occurrence of other soil science words did not closely follow the usual hierarchy of soil taxa. We present preliminary phrasal analyses that may account for some of these effects.

Estimating the Limits of Infiltration in the Urban Appalachian Plateau

NASA Astrophysics Data System (ADS)

Lavin, S. M.; Bain, D.; Hopkins, K. G.; Pfeil-McCullough, E. K.; Copeland, E.

2014-12-01

Green infrastructure in urbanized areas commonly uses infiltration systems, such as rain gardens, swales and trenches, to convey surface runoff from impervious surfaces into surrounding soils. However, precipitation inputs can exceed soil infiltration rates, creating a limit to infiltration-based storm water management, particularly in urban areas covered by impervious surfaces. Given the limited availability and varied quality of soil infiltration rate data, we synthesized information from national databases, available field test data, and applicable literature to characterize soil infiltration rate distributions, focusing on Allegheny County, Pennsylvania as a case study. A range of impervious cover conditions was defined by sampling available GIS data (e.g., LiDAR and street edge lines) with analysis windows placed randomly across urbanization gradients. Changes in effective precipitation caused by impervious cover were calculated across these gradients and compared to infiltration rate distributions to identify thresholds in impervious coverage where these limits are exceeded. Many studies have demonstrated the effects of urbanization on infiltration, but the identification of these thresholds will clarify interactions between impervious cover and soil infiltration. These methods can help identify sections of urban areas that require augmentation of infiltration-based systems with additional infrastructural strategies, especially as green infrastructure moves beyond low impact development towards more frequent application during infilling of existing urban systems.

Role of freeze-thaw cycles and chlorpyrifos insecticide use on diffuse Cd loss and sediment accumulation

NASA Astrophysics Data System (ADS)

Wang, Fangli; Ouyang, Wei; Hao, Fanghua; Jiao, Wei; Shan, Yushu; Lin, Chunye

2016-06-01

Freeze-thaw cycles are predicted to increase in cold temperate regions. The potential influence of the interactions of freeze-thaw cycles and agrochemicals on the release of Cd into river water is unknown. In this study, the interactions of freeze-thaw cycles and chlorpyrifos (FC) on Cd mobility in soils were analysed. The spatial variability of soil Cd under long-term intensive tillage in a freeze-thaw agro-system was also identified. The temporal variation of sediment Cd was detected based on analysis of the sediment geochemistry. The results showed that FC increased soil Cd mobility, with an increase of approximately 10% in CaCl2-extractable Cd. The increased mobile fractions of water-soluble and exchangeable Cd originated from the decreased fraction of Fe-Mn-oxide-associated Cd and organic matter-bound Cd. The total Cd content in the surface soil followed the zonally decreasing trend of dry land > paddy land > natural land. The Cd concentrations and sedimentation rates of the sediment core generally increased from 1943 to 2013 due to agricultural exploration and farmland irrigation system construction, indicating an increase of the Cd input flux into water. The results provide valuable information about the soil Cd transport response to the influence of climatic and anthropogenic factors in cold intensive agro-systems.

Corrective Action Management Unit Report of Post-Closure Care Activities Calendar Year 2017.

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

Ziock, Robert; Little, Bonnie Colleen

The Corrective Action Management Unit (CAMU) at Sandia National Laboratories, New Mexico (SNL/NM) consists of a containment cell and ancillary systems that underwent regulatory closure in 2003 in accordance with the Closure Plan in Appendix D of the Class 3 Permit Modification (SNL/NM September 1997). The containment cell was closed with wastes in place. On January 27, 2015, the New Mexico Environment Department (NMED) issued the Hazardous Waste Facility Operating Permit (Permit) for Sandia National Laboratories (NMED January 2015). The Permit became effective February 26, 2015. The CAMU is undergoing post-closure care in accordance with the Permit, as revised andmore » updated. This CAMU Report of Post-Closure Care Activities documents all activities and results for Calendar Year (CY) 2017 as required by the Permit. The CAMU containment cell consists of engineered barriers including a cover system, a bottom liner with a leachate collection and removal system (LCRS), and a vadose zone monitoring system (VZMS). The VZMS provides information on soil conditions under the cell for early leak detection. The VZMS consists of three monitoring subsystems, which include the primary subliner (PSL), a vertical sensor array (VSA), and the Chemical Waste Landfill (CWL) sanitary sewer (CSS) line. The PSL, VSA, and CSS monitoring subsystems are monitored quarterly for soil moisture concentration, the VSA is monitored quarterly for soil temperature, and the VSA and CSS monitoring subsystems are monitored annually for volatile organic compound (VOC) concentrations in the soil vapor at various depths. Baseline data for the soil moisture, soil temperature, and soil vapor were established between October 2003 and September 2004.« less

Removal of a mixture of pesticides by a Streptomyces consortium: Influence of different soil systems.

PubMed

Fuentes, María S; Raimondo, Enzo E; Amoroso, María J; Benimeli, Claudia S

2017-04-01

Although the use of organochlorine pesticides (OPs) is restricted or banned in most countries, they continue posing environmental and health concerns, so it is imperative to develop methods for removing them from the environment. This work is aimed to investigate the simultaneous removal of three OPs (lindane, chlordane and methoxychlor) from diverse types of systems by employing a native Streptomyces consortium. In liquid systems, a satisfactory microbial growth was observed accompanied by removal of lindane (40.4%), methoxychlor (99.5%) and chlordane (99.8%). In sterile soil microcosms, the consortium was able to grow without significant differences in the different textured soils (clay silty loam, sandy and loam), both contaminated or not contaminated with the OPs-mixture. The Streptomyces consortium was able to remove all the OPs in sterile soil microcosm (removal order: clay silty loam > loam > sandy). So, clay silty loam soil (CSLS) was selected for next assays. In non-sterile CSLS microcosms, chlordane removal was only about 5%, nonetheless, higher rates was observed for lindane (11%) and methoxychlor (20%). In CSLS slurries, the consortium exhibited similar growth levels, in the presence of or in the absence of the OPs-mixture. Not all pesticides were removed in the same way; the order of pesticide dissipation was: methoxychlor (26%)>lindane (12.5%)>chlordane (10%). The outlines of microbial growth and pesticides removal provide information about using actinobacteria consortium as strategies for bioremediation of OPs-mixture in diverse soil systems. Texture of soils and assay conditions (sterility, slurry formulation) were determining factors influencing the removal of each pesticide of the mixture. Copyright © 2017 Elsevier Ltd. All rights reserved.

Soil spectral characterization

NASA Technical Reports Server (NTRS)

Stoner, E. R.; Baumgardner, M. F.

1981-01-01

The spectral characterization of soils is discussed with particular reference to the bidirectional reflectance factor as a quantitative measure of soil spectral properties, the role of soil color, soil parameters affecting soil reflectance, and field characteristics of soil reflectance. Comparisons between laboratory-measured soil spectra and Landsat MSS data have shown good agreement, especially in discriminating relative drainage conditions and organic matter levels in unvegetated soils. The capacity to measure both visible and infrared soil reflectance provides information on other soil characteristics and makes it possible to predict soil response to different management conditions. Field and laboratory soil spectral characterization helps define the extent to which intrinsic spectral information is available from soils as a consequence of their composition and field characteristics.

Slow reaction of soil structure to conservation agriculture practices in Veneto silty soils (North-Easter Italy)

NASA Astrophysics Data System (ADS)

Piccoli, Ilaria; Camarotto, Carlo; Lazzaro, Barbara; Furlan, Lorenzo; Morari, Francesco

2017-04-01

Soil structure plays a pivotal role in soil functioning and can inform of the degradation of the soil ecosystem. Intensive and repeated tillage operations have been known to negatively affect the soil structure characteristics while conservation agriculture (CA) practices were demonstrated to improve soil structure and related ecosystem services. The aim of this study is to evaluate the effect of conservation agriculture practices on total porosity, pore size distribution, pore architecture and morphology on silty soils of Veneto low-lying plain (North-Eastern Italy). Experimental design was established in 2010 on 4 farms in North-Eastern Italy to compare conventional intensive tillage system "IT" versus conservation agriculture "CA" (no-tillage, cover-crop and residue retention). 96 samples were collected in 2015 at four depths down to 50 cm depth, and investigated for porosity from micro to macro by coupling mercury intrusion porosimetry (MIP) (0.0074-100 µm) and x-ray computed microtomography (µCT) (>26 µm). Pore morphology and architecture were studied from 3D images analysis and MIP pore size curve. Ultramicroporosity class (0.1-5 μm) positively responded to CA after 5-yr of practices adoption while no significant effects were observed in the x-ray µCT domain (> 26 µm). Silty soils of Veneto plain showed a slow reaction to conservation agriculture because of the low soil organic carbon content and poor aggregate stability. Nevertheless the positive influence of CA on ultramicroporosity, which is strictly linked to soil organic carbon (SOC) stabilization, indicated that a virtuous cycle was initiated between SOC and porosity, hopefully leading to well-developed macropore systems and, in turn, enhanced soil functions and ecosystem services.

Applying soil property information for watershed assessment.

NASA Astrophysics Data System (ADS)

Archer, V.; Mayn, C.; Brown, S. R.

2017-12-01

The Forest Service uses a priority watershed scheme to guide where to direct watershed restoration work. Initial assessment was done across the nation following the watershed condition framework process. This assessment method uses soils information for a three step ranking across each 12 code hydrologic unit; however, the soil information used in the assessment may not provide adequate detail to guide work on the ground. Modern remote sensing information and terrain derivatives that model the environmental gradients hold promise of showing the influence of soil forming factors on watershed processes. These small scale data products enable the disaggregation of coarse scale soils mapping to show continuous soil property information across a watershed. When this information is coupled with the geomorphic and geologic information, watershed specialists can more aptly understand the controlling influences of drainage within watersheds and focus on where watershed restoration projects can have the most success. A case study on the application of this work shows where road restoration may be most effective.

An analysis of soil moisture and vegetation conditions during a period of rapid subseasonal oscillations between drought and pluvials over Texas during 2015

NASA Astrophysics Data System (ADS)

Hunt, E. D.; Otkin, J.; Zhong, Y.

2017-12-01

Flash drought, characterized by the rapid onset of abnormally warm and dry weather conditions that leads to the rapid depletion of soil moisture and rapid deteriorations in vegetation health. Flash recovery, on the other hand, is characterized by a period(s) of intense precipitation where drought conditions are quickly eradicated and may be replaced by saturated soils and flooding. Both flash drought and flash recovery are closely tied to the rapid depletion or recharge of root zone soil moisture; therefore, soil moisture observations are very useful for monitoring their evolution. However, in-situ soil moisture observations tend to be concentrated over small regions and thus other methods are needed to provide a spatially continuous depiction of soil moisture conditions. One option is to use top soil moisture retrievals from the Soil Moisture Active Passive (SMAP) sensor. SMAP provides routine coverage of surface soil moisture (0-5 cm) over most of the globe, including the timespan (2015) and region of interest (Texas) that are the focus of our study. This region had an unusual sequence of flash recovery-flash drought-flash recovery during an six-month period during 2015 that provides a valuable case study of rapid transitions between extreme soil moisture conditions. During this project, SMAP soil moisture retrievals are being used in combination with in-situ soil moisture observations and assimilated into the Land Information System (LIS) to provide information about soil moisture content. LIS also provides greenness vegetation fraction data over large regions. The relationship between soil moisture and vegetation conditions and the response of the vegetation to the rapidly changing conditions are also assessed using the satellite thermal infrared based Evaporative Stress Index (ESI) that depicts anomalies in evapotranspiration, along with other vegetation datasets (leaf area index, greenness fraction) derived using MODIS observations. Preliminary results with the Noah land surface model (inside of LIS) shows that it broadly captured the soil moisture evolution during the 2015 sequence but tended to underestimate the magnitude of soil moisture anomalies. The ESI also showed negative anomalies during the drought. These and other results will be presented at the annual meeting.

Validating modeled soil moisture with in-situ data for agricultural drought monitoring in West Africa

NASA Astrophysics Data System (ADS)

McNally, A.; Yatheendradas, S.; Jayanthi, H.; Funk, C. C.; Peters-Lidard, C. D.

2011-12-01

The declaration of famine in Somalia on July 21, 2011 highlights the need for regional hydroclimate analysis at a scale that is relevant for agropastoral drought monitoring. A particularly critical and robust component of such a drought monitoring system is a land surface model (LSM). We are currently enhancing the Famine Early Warning Systems Network (FEWS NET) monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System (FLDAS). Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following question: How can Noah be best parameterized to accurately simulate hydroclimate variables associated with crop performance? Parameter value testing and validation is done by comparing modeled soil moisture against fortuitously available in-situ soil moisture observations in the West Africa. Direct testing and application of the FLDAS over African agropastoral locations is subject to some issues: [1] In many regions that are vulnerable to food insecurity ground based measurements of precipitation, evapotranspiration and soil moisture are sparse or non-existent, [2] standard landcover classes (e.g., the University of Maryland 5 km dataset), do not include representations of specific agricultural crops with relevant parameter values, and phenologies representing their growth stages from the planting date and [3] physically based land surface models and remote sensing rain data might still need to be calibrated or bias-corrected for the regions of interest. This research aims to address these issues by focusing on sites in the West African countries of Mali, Niger, and Benin where in-situ rainfall and soil moisture measurements are available from the African Monsoon Multidisciplinary Analysis (AMMA). Preliminary results from model experiments over Southern Malawi, validated with Normalized Difference Vegetation Index (NDVI) and maize yield data, show that the ability to detect a drought signal in modeled soil moisture and actual evapotranspiration was sensitive to parameters like minimum stomatal resistance, green vegetation fraction, and minimum threshold for transpiration stress. In addition to improving our understanding and representation of the land surface physics in agropastoral drought, this study moves us closer to confidently validating LSM estimates with remotely sensed data (e.g. MODIS NDVI), essential in regions that lack ground based measurements. Ultimately, these improved information products serve to better inform decision makers about seasonal food production and anticipate the need for relief, as well as guide climate change adaptation strategies, potentially saving millions of lives.

Impact of uncertainty in soil, climatic, and chemical information in a pesticide leaching assessment

NASA Astrophysics Data System (ADS)

Loague, Keith; Green, Richard E.; Giambelluca, Thomas W.; Liang, Tony C.; Yost, Russell S.

1990-01-01

A simple mobility index, when combined with a geographic information system, can be used to generate rating maps which indicate qualitatively the potential for various organic chemicals to leach to groundwater. In this paper we investigate the magnitude of uncertainty associated with pesticide mobility estimates as a result of data uncertainties. Our example is for the Pearl Harbor Basin, Oahu, Hawaii. The two pesticides included in our analysis are atrazine (2-chloro-4-ethylamino-6-isopropylamino-s-triazine) and diuron [3-(3,4-dichlorophenyul)-1,1-dimethylarea]. The mobility index used here is known as the Attenuation Factor ( AF); it requires soil, hydrogeologic, climatic and chemical information as input data. We employ first-order uncertainty analysis to characterize the uncertainty in estimates of AF resulting from uncertainties in the various input data. Soils in the Pearl Harbor Basin are delineated at the order taxonomic category for this study. Our results show that there can be a significant amount of uncertainty in estimates of pesticide mobility for the Pearl Harbor Basin. This information needs to be considered if future decisions concerning chemical regulation are to be based on estimates of pesticide mobility determined from simple indices.

Erratum to "Impact of uncertainty in soil, climatic, and chemical information in a pesticide leaching assessment"

NASA Astrophysics Data System (ADS)

Loague, Keith; Green, Richard E.; Giambelluca, Thomas W.; Liang, Tony C.; Yost, Russell S.

2016-11-01

A simple mobility index, when combined with a geographic information system, can be used to generate rating maps which indicate qualitatively the potential for various organic chemicals to leach to groundwater. In this paper we investigate the magnitude of uncertainty associated with pesticide mobility estimates as a result of data uncertainties. Our example is for the Pearl Harbor Basin, Oahu, Hawaii. The two pesticides included in our analysis are atrazine (2-chloro-4-ethylamino-6-isopropylamino-s-triazine) and diuron [3-(3,4-dichlorophenyl)-1,1-dimethylarea]. The mobility index used here is known as the Attenuation Factor (AF); it requires soil, hydrogeologic, climatic, and chemical information as input data. We employ first-order uncertainty analysis to characterize the uncertainty in estimates of AF resulting from uncertainties in the various input data. Soils in the Pearl Harbor Basin are delineated at the order taxonomic category for this study. Our results show that there can be a significant amount of uncertainty in estimates of pesticide mobility for the Pearl Harbor Basin. This information needs to be considered if future decisions concerning chemical regulation are to be based on estimates of pesticide mobility determined from simple indices.

Moss and soil contributions to the annual net carbon flux of a maturing boreal forest

USGS Publications Warehouse

Harden, J.W.; O'Neill, K. P.; Trumbore, S.E.; Veldhuis, H.; Stocks, B.J.

1997-01-01

We used input and decomposition data from 14C studies of soils to determine rates of vertical accumulation of moss combined with carbon storage inventories on a sequence of burns to model how carbon accumulates in soils and moss after a stand-killing fire. We used soil drainage - moss associations and soil drainage maps of the old black spruce (OBS) site at the BOREAS northern study area (NSA) to areally weight the contributions of each moderately well drained, feathermoss areas; poorly drained sphagnum - feathermoss areas; and very poorly drained brown moss areas to the carbon storage and flux at the OBS NSA site. On this very old (117 years) complex of black spruce, sphagnum bog veneer, and fen systems we conclude that these systems are likely sequestering 0.01-0.03 kg C m-2 yr-' at OBS-NSA today. Soil drainage in boreal forests near Thompson, Manitoba, controls carbon storage and flux by controlling moss input and decomposition rates and by controlling through fire the amount and quality of carbon left after burning. On poorly drained soils rich in sphagnum moss, net accumulation and long-term storage of carbon is higher than on better drained soils colonized by feathermosses. The carbon flux of these contrasting ecosystems is best characterized by soil drainage class and stand age, where stands recently burned are net sources of CO2, and maturing stands become increasingly stronger sinks of atmospheric CO2. This approach to measuring carbon storage and flux presents a method of scaling to larger areas using soil drainage, moss cover, and stand age information.

Estimating Evapotranspiration with Land Data Assimilation Systems

NASA Technical Reports Server (NTRS)

Peters-Lidard, C. D.; Kumar, S. V.; Mocko, D. M.; Tian, Y.

2011-01-01

Advancements in both land surface models (LSM) and land surface data assimilation, especially over the last decade, have substantially advanced the ability of land data assimilation systems (LDAS) to estimate evapotranspiration (ET). This article provides a historical perspective on international LSM intercomparison efforts and the development of LDAS systems, both of which have improved LSM ET skill. In addition, an assessment of ET estimates for current LDAS systems is provided along with current research that demonstrates improvement in LSM ET estimates due to assimilating satellite-based soil moisture products. Using the Ensemble Kalman Filter in the Land Information System, we assimilate both NASA and Land Parameter Retrieval Model (LPRM) soil moisture products into the Noah LSM Version 3.2 with the North American LDAS phase 2 (NLDAS-2) forcing to mimic the NLDAS-2 configuration. Through comparisons with two global reference ET products, one based on interpolated flux tower data and one from a new satellite ET algorithm, over the NLDAS2 domain, we demonstrate improvement in ET estimates only when assimilating the LPRM soil moisture product.

Designation of less favorable areas by the regionalization of soil degradation on various spatial scales

NASA Astrophysics Data System (ADS)

Pásztor, L.; Szabó, J.; Bakacsi, Zs.; Laborczi, A.

2009-04-01

One of the main objectives of the EU's Common Agricultural Policy is to encourage maintaining agricultural production in less favorable areas (LFA) in order (among others) to sustain agricultural production and use natural resources, in such a way to secure both stable production and income to farmers and to protect the environment. LFA assignment has both ecological and severe economical aspects. Delimitation of LFAs can be carried out by using biophysical diagnostic criteria on low soil productivity and poor climate conditions. Identification of low-productivity areas requires regionalization of soil functions related to food and other biomass production. This process can be carried out in different scales from national to local level, but always requires map-based pedological and further environmental information with appropriate spatial resolution. For the regionalization of less productive areas in national scale a functional approach was used which integrates the knowledge on soil degradation processes in nationwide level. Specific soil threats were classified into ranked categories. Supposing (quasi)uniform distribution of vulnerability measure along these classes, we introduced a "standardized" value as a ratio of the class order to the maximum class order expressed in percentage. For the overall spatial characterization of degradation status, spatial information was integrated in a result map by summarizing the degradation specific "standardized" cell values. This map in one hand has been used for the delineation of soil degradation regions. On the other hand appropriate spatial aggregation of index values on geographical and administrative regions is suitable for their quantitative comparison thus they can be ranked and this feature can be used for the identification of less favorable areas. At the more detailed, county level the Digital Kreybig Soil Information System was used as a tool of the regionalization of soil functions related to soil productivity. Concurrent spatial analysis of the suitability of soils for agricultural use and their sensitivity to physical and chemical degradation were carried out which resulted in a so-called ecotype-based characterization of land. As a spin-off, this classification was used for the designation of low productive areas suitable for hypogenous and cap fungi plantations as landuse alternative for croplands.

Agricultural Decision Support Through Robust Assimilation of Satellite Derived Soil Moisture Estimates

NASA Astrophysics Data System (ADS)

Mishra, V.; Cruise, J.; Mecikalski, J. R.

2012-12-01

Soil Moisture is a key component in the hydrological process, affects surface and boundary layer energy fluxes and is the driving factor in agricultural production. Multiple in situ soil moisture measuring instruments such as Time-domain Reflectrometry (TDR), Nuclear Probes etc. are in use along with remote sensing methods like Active and Passive Microwave (PM) sensors. In situ measurements, despite being more accurate, can only be obtained at discrete points over small spatial scales. Remote sensing estimates, on the other hand, can be obtained over larger spatial domains with varying spatial and temporal resolutions. Soil moisture profiles derived from satellite based thermal infrared (TIR) imagery can overcome many of the problems associated with laborious in-situ observations over large spatial domains. An area where soil moisture observation and assimilation is receiving increasing attention is agricultural crop modeling. This study revolves around the use of the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to simulate corn yields under various forcing scenarios. First, the model was run and calibrated using observed precipitation and model generated soil moisture dynamics. Next, the modeled soil moisture was updated using estimates derived from satellite based TIR imagery and the Atmospheric Land Exchange Inverse (ALEXI) model. We selected three climatically different locations to test the concept. Test Locations were selected to represent varied climatology. Bell Mina, Alabama - South Eastern United States, representing humid subtropical climate. Nabb, Indiana - Mid Western United States, representing humid continental climate. Lubbok, Texas - Southern United States, representing semiarid steppe climate. A temporal (2000-2009) correlation analysis of the soil moisture values from both DSSAT and ALEXI were performed and validated against the Land Information System (LIS) soil moisture dataset. The results clearly show strong correlation (R = 73%) between ALEXI and DSSAT at Bell Mina. At Nabb and Lubbock the correlation was 50-60%. Further, multiple experiments were conducted for each location: a) a DSSAT rain-fed 10 year sequential run forced with daymet precipitation; b) a DSSAT sequential run with no precipitation data; and c) a DSSAT run forced with ALEXI soil moisture estimates alone. The preliminary results of all the experiments are quantified through soil moisture correlations and yield comparisons. In general, the preliminary results strongly suggest that DSSAT forced with ALEXI can provide significant information especially at locations where no significant precipitation data exists.

The World Soil Museum: education and advocacy on soils of the world

NASA Astrophysics Data System (ADS)

Mantel, Stephan; Land, Hiske

2013-04-01

The World Soil Museum (WSM) in Wageningen, is part of ISRIC World Soil Information and was founded in 1966 on request of the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the International Soil Science Society. The World Soil Museum has a collection of over 1100 soil profiles from more than 70 countries. This soil profiles are vertical sections and show the composition, layering and structure of the soil. The collection is unique in the world and includes a significant number of soil profiles from the Netherlands. The Dutch soil collection is important for serving broader visitor groups, as some visitors, such as secondary school classes, are specifically interested in the Dutch landscape and soils. Broadly speaking, the World Soil Museum has five functions: (i) education and courses, (ii) research, (iii) information and edutainment, (iv) social function, and (v) a real museum function (Art). The World Soil Museum (World Soil Museum) is well known in national and international circles soil and the English name has almost 1,000 references on the Internet. The World Soil Museum is visited by about 1000 people a year, mainly university and college students from Western Europe. Other visitor groups that have found their way to the museum are students from disciplines broader then soil science, such as geography and rural development. Secondary school classes visit the museum for geography classes. The uniqueness and the value of the collection of soil profiles (soil monoliths) and associated collections, such as soil samples, hand pieces, thin sections, slides, is emphasized by the fact ISRIC is the only World Data Centre for Soils (WDC-Soils) within the World Data System of the International Council of Science (ICSU). The collection provides an insight in and overview of the diversity of soils in the world, their properties and their limitations and possibilities for use. A new building is under construction for the WSM, which is expected to be ready mid-2013. The location is appropriately placed on the Wageningen University Campus, close to the students and research centres of the University. The new exposition space will provide new opportunities for serving different visitor groups. The selection of about 80 soil monoliths representing the world's soils will be maintained in the new exposition. In addition, interactive displays will support education. A circular, interactive map of the world will be placed centrally in the exposition and will serve as a portal to the soil information. The map data refer to the monoliths on the walls and vice versa. Around the central map six theme stations communicate current topics that show the relevance of soil in different fields. For the general public it will explain the principles of soil formation and it will show the relevance to actual issues like food production and climate change. High school students in their final years can come here for work assignments and orientation days. Academic students and scientists, from both the Netherlands and other (mainly) northern European countries can continue to come to the WSM for education, study and research.

Unusual Reactivity of the Martian Soil: Oxygen Release Upon Humidification

NASA Technical Reports Server (NTRS)

Yen, A. S.

2002-01-01

Recent lab results show that oxygen evolves from superoxide-coated mineral grains upon exposure to water vapor. This observation is additional support of the hypothesis that UV-generated O2 is responsible for the reactivity of the martian soil. Discussion of current NASA research opportunities, status of various programs within the Solar System Exploration Division, and employment opportunities within NASA Headquarters to support these programs. Additional information is contained in the original extended abstract.

Exchange of soil moisture between patches of wild-olive and pasture sustains evapotranspiration of a Mediterranean ecosystem in both wet and dry seasons

NASA Astrophysics Data System (ADS)

Curreli, M.; Montaldo, N.; Oren, R.

2017-12-01

Partitioning evapotranspiration in water-limited environments, such as Mediterranean ecosystems, could give information on vegetation and hydraulic dynamics. Indeed, in such ecosystems, trees may survive prolonged droughts by uptake of water by dimorphic root system: deep roots and shallower lateral roots, extending beyond the crown into inter-trees grassy areas. The water exchange between under canopy areas and treeless patches plays a crucial role on sustaining tree and grass physiological performance during droughts. The study has been performed at the Orroli site, Sardinia (Italy). The landscape is covered by patchy vegetation: wild olives trees in clumps and herbaceous species, drying to bare soil in summer. The climate is characterized by long droughts from May to October and rain events concentrated in the autumn and winter, whit a mean yearly rain of about 700 mm. A 10 m micrometeorological tower equipped with eddy-covariance system has been used for measuring water and energy surface fluxes, as well as key state variables (e.g. temperature, radiations, humidity and wind velocity). Soil moisture was measured with five soil water reflectometers (two below the olive canopy and three in the pasture). To estimate plant water use in the context of soil water dynamic, 33 Granier-type thermal dissipation probes were installed 40 cm aboveground, in representative trees over the eddy covariance footprint. Early analyses show that wild olive continue to transpire even as the soil dries and the pasture desiccates. This reveled hydraulic redistribution system through the plant and the soil, and allows to quantify the reliance of the system on horizontally and vertically differentiated soil compartments. Results shows that during light hours, until transpiration decreases in midday, shallow roots uptake deplete the shallow water content. As transpiration decreases, hydraulically redistributed water provides for both transpiration of wild olives and recharge of shallow soil layers in the inter-tree areas. This consents trees to remain physiologically active during very dry conditions and represent a mechanism of facilitation of the coexistence of tree-grass system.

Identification of Chemicals of Interest to the Department of Defense and U.S. Air Force Among the U.S. Environmental Protection Agency’s Integrated Risk Information System Chemicals that are Due for Reassessment of their Toxicity Values

DTIC Science & Technology

2010-03-16

Exceeded at ERP Soil and Groundwater Sites 86 A-2a. Identification of IRIS Chemicals of Interest on the ATSDR CERCLA Priority List of Hazardous...the Number (Bold Font) of Air Force ERP Samples in Which They Were Detected 317 A-4d. Air Force ERP Soil Samples: IRIS Chemicals of Interest...Ranked by the Number (Bold Font) of Air Force ERP Soil Samples in Which They Were Detected 333 A-4e. Air Force ERP Groundwater Samples: IRIS Chemicals of

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.

Future Carbon Dynamics of the Northern Rockies Ecoregion due to Climate Impacts and Fire Effects

NASA Astrophysics Data System (ADS)

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

2016-12-01

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.

A decision support system for map projections of small scale data

USGS Publications Warehouse

Finn, Michael P.; Usery, E. Lynn; Posch, Stephan T.; Seong, Jeong Chang

2004-01-01

The use of commercial geographic information system software to process large raster datasets of terrain elevation, population, land cover, vegetation, soils, temperature, and rainfall requires both projection from spherical coordinates to plane coordinate systems and transformation from one plane system to another. Decision support systems deliver information resulting in knowledge that assists in policies, priorities, or processes. This paper presents an approach to handling the problems of raster dataset projection and transformation through the development of a Web-enabled decision support system to aid users of transformation processes with the selection of appropriate map projections based on data type, areal extent, location, and preservation properties.

Effect of crop rotation on soil nutrient balance and weediness in soddy podzolic organic farming fields

NASA Astrophysics Data System (ADS)

Zarina, Livija; Zarina, Liga

2017-04-01

The nutrient balance in different crop rotations under organic cropping system has been investigated in Latvia at the Institute of Agricultural Resources and Economics since 2006. Latvia is located in a humid and moderate climatic region where the rainfall exceeds evaporation (soil moisture coefficient > 1) and the soil moisture regime is characteristic with percolation. The average annual precipitation is 670-850 mm. The average temperature varies from -6.7° C in January to 16.5 °C in July. The growing season is 175 - 185 days. The most widespread are podzolic soils and mainly they are present in agricultural fields in all regions of Latvia. In a wider sense the goal of the soil management in organic farming is a creation of the biologically active flora and fauna in the soil by maintaining a high level of soil organic matter which is good for crops nutrient balance. Crop rotation is a central component of organic farming systems and has many benefits, including growth of soil microbial activity, which may increase nutrient availability. The aim of the present study was to calculate nutrient balance for each crop in the rotations and average in each rotation. Taking into account that crop rotations can limit build-up of weeds, additionally within the ERA-net CORE Organic Plus transnational programs supported project PRODIVA the information required for a better utilization of crop diversification for weed management in North European organic arable cropping systems was summarized. It was found that the nutrient balance was influenced by nutrients uptake by biomass of growing crops in crop rotation. The number of weeds in the organic farming fields with crop rotation is dependent on the cultivated crops and the succession of crops in the crop rotation.

Effect of tillage system and cumulative rainfall on multifractal parameters of soil surface microrelief

NASA Astrophysics Data System (ADS)

Vidal Vázquez, E.; Miranda, J. G. V.; Mirás-Avalos, J. M.; Díaz, M. C.; Paz-Ferreiro, J.

2009-04-01

Mathematical description of the spatial characteristics of soil surface microrelief still remains a challenge. Soil surface roughness parameters are required for modelling overland flow and erosion. The objective of this work was to evaluate the potential of multifractal for analyzing the decay of initial surface roughness induced by natural rainfall under different soil tillage systems. Field experiments were performed on an Oxisol at Campinas, São Paulo State (Brazil). Six tillage treatments, namely, disc harrow, disc plow, chisel plow, disc harrow + disc level, disc plow + disc level and chisel plow + disc level were tested. In each plot soil surface microrelief was measured for times, with increasing amounts of natural rainfall using a pinmeter. The sampling scheme was a square grid with 25 x 25 mm point spacing and the plot size was 1350 x 1350 mm, so that each data set consisted of 3025 individual elevation points. Duplicated measurements were taken per treatment and date, yielding a total of 48 experimental data sets. All the investigated microrelief data sets exhibited, in general, scale properties, and the degree of multifractality showed wide differences between them. Multifractal analysis distinguishes two different patterns of soil surface microrelief, the first one has features close to monofractal spectra and the second clearly indicates multifractal behavior. Both, singularity spectra and generalized dimension spectra allow differentiating between soil tillage systems. In general, changes in values of multifractal parameters under simulated rainfall showed no or little correspondence with the evolution of the vertical microrelief component described by indices such as the standard deviation of the point height measurements. Multifractal parameters provided valuable information for chararacterizing the spatial features of soil surface microrelief as they were able to discriminate data sets with similar values for the vertical component of roughness.

Soil moisture retrieval from Sentinel-1 satellite data

NASA Astrophysics Data System (ADS)

Benninga, Harm-Jan; van der Velde, Rogier; Su, Zhongbo

2016-04-01

Reliable up-to-date information on the current water availability and models to evaluate management scenarios are indispensable for skilful water management. The Sentinel-1 radar satellite programme provides an opportunity to monitor water availability (as surface soil moisture) from space on an operational basis at unprecedented fine spatial and temporal resolutions. However, the influences of soil roughness and vegetation cover complicate the retrieval of soil moisture states from radar data. In this contribution, we investigate the sensitivity of Sentinel-1 radar backscatter to soil moisture states and vegetation conditions. The analyses are based on 105 Sentinel-1 images in the period from October 2014 to January 2016 covering the Twente region in the Netherlands. This area is almost flat and has a heterogeneous landscape, including agricultural (mainly grass, cereal and corn), forested and urban land covers. In-situ measurements at 5 cm depth collected from the Twente soil moisture monitoring network are used as reference. This network consists of twenty measurement stations (most of them at agricultural fields) distributed across an area of 50 km × 40 km. The Normalized Difference Vegetation Index (NDVI) derived from optical images is adopted as proxy to represent seasonal variability in vegetation conditions. The results from this sensitivity study provide insight into the potential capability of Sentinel-1 data for the estimation of soil moisture states and they will facilitate the further development of operational retrieval methods. An operationally applicable soil moisture retrieval method requires an algorithm that is usable without the need for area specific model calibration with detailed field information (regarding roughness and vegetation). Because it is not yet clear which method provides the most reliable soil moisture retrievals from Sentinel-1 data, multiple soil moisture retrieval methods will be studied in which the fine spatiotemporal resolution and the dual-polarized information of Sentinel-1 are utilized. Three candidate algorithms are presented at the conference, which are a data-driven algorithm, inversion of a radar scattering model and downscaling of coarser resolution soil moisture products. The research is part of the OWAS1S project (Optimizing Water Availability with Sentinel-1 Satellites), which stands for integration of the freely available global Sentinel-1 data and local knowledge on soil physical processes, to optimize water management of regional water systems and to develop value-added products for agriculture.

Ensemble learning for spatial interpolation of soil potassium content based on environmental information.

PubMed

Liu, Wei; Du, Peijun; Wang, Dongchen

2015-01-01

One important method to obtain the continuous surfaces of soil properties from point samples is spatial interpolation. In this paper, we propose a method that combines ensemble learning with ancillary environmental information for improved interpolation of soil properties (hereafter, EL-SP). First, we calculated the trend value for soil potassium contents at the Qinghai Lake region in China based on measured values. Then, based on soil types, geology types, land use types, and slope data, the remaining residual was simulated with the ensemble learning model. Next, the EL-SP method was applied to interpolate soil potassium contents at the study site. To evaluate the utility of the EL-SP method, we compared its performance with other interpolation methods including universal kriging, inverse distance weighting, ordinary kriging, and ordinary kriging combined geographic information. Results show that EL-SP had a lower mean absolute error and root mean square error than the data produced by the other models tested in this paper. Notably, the EL-SP maps can describe more locally detailed information and more accurate spatial patterns for soil potassium content than the other methods because of the combined use of different types of environmental information; these maps are capable of showing abrupt boundary information for soil potassium content. Furthermore, the EL-SP method not only reduces prediction errors, but it also compliments other environmental information, which makes the spatial interpolation of soil potassium content more reasonable and useful.

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.

Lunar base agriculture: Soils for plant growth

NASA Technical Reports Server (NTRS)

Ming, Douglas W. (Editor); Henninger, Donald L. (Editor)

1989-01-01

This work provides information on research and experimentation concerning various aspects of food production in space and particularly on the moon. Options for human settlement of the moon and Mars and strategies for a lunar base are discussed. The lunar environment, including the mineralogical and chemical properties of lunar regolith are investigated and chemical and physical considerations for a lunar-derived soil are considered. It is noted that biological considerations for such a soil include controlled-environment crop production, both hydroponic and lunar regolith-based; microorganisms and the growth of higher plants in lunar-derived soils; and the role of microbes to condition lunar regolith for plant cultivation. Current research in the controlled ecological life support system (CELSS) project is presented in detail and future research areas, such as the growth of higher research plants in CELSS are considered. Optimum plant and microbiological considerations for lunar derived soils are examined.

Drought Information Supported by Citizen Scientists (DISCS)

NASA Astrophysics Data System (ADS)

Molthan, A.; Maskey, M.; Hain, C.; Meyer, P.; Nair, U. S.; Handyside, C. T.; White, K.; Amin, M.

2017-12-01

Each year, drought impacts various regions of the United States on time scales of weeks, months, seasons, or years, which in turn leads to a need to document these impacts and inform key decisions on land management, use of water resources, and disaster response. Mapping impacts allows decision-makers to understand potential damage to agriculture and loss of production, to communicate and document drought impacts on crop yields, and to inform water management decisions. Current efforts to collect this information includes parsing of media reports, collaborations with local extension offices, and partnerships with the National Weather Service cooperative observer network. As part of a NASA Citizen Science for Earth Systems proposal award, a research and applications team from Marshall Space Flight Center, the University of Alabama in Huntsville, and collaborators within the NWS have developed a prototype smartphone application focused on the collection of citizen science observations of crop health and drought impacts, along with development of innovative low-cost soil moisture sensors to supplement subjective assessments of local soil moisture conditions. Observations provided by citizen scientists include crop type and health, phase of growth, soil moisture conditions, irrigation status, along with an optional photo and comment to provide visual confirmation and other details. In exchange for their participation, users of the app also have access to unique land surface modeling data sets produced at MSFC such as the NASA Land Information System soil moisture and climatology/percentile products from the Short-term Prediction Research and Transition (SPoRT) Center, assessments of vegetation health and stress from NASA and NOAA remote sensing platforms (e.g. MODIS/VIIRS), outputs from a crop stress model developed at the University of Alabama in Huntsville, recent rainfall estimates from the NOAA/NWS network of ground-based weather radars, and other observations made by their fellow citizen scientists. This presentation will highlight development of the application, data collected to date, feedback from participants, and opportunities to use the collected information in support of addressing science questions such as verification and validation of modeling and remote sensing data sets.

Spatial disaggregation of complex soil map units at regional scale based on soil-landscape relationships

NASA Astrophysics Data System (ADS)

Vincent, Sébastien; Lemercier, Blandine; Berthier, Lionel; Walter, Christian

2015-04-01

Accurate soil information over large extent is essential to manage agronomical and environmental issues. Where it exists, information on soil is often sparse or available at coarser resolution than required. Typically, the spatial distribution of soil at regional scale is represented as a set of polygons defining soil map units (SMU), each one describing several soil types not spatially delineated, and a semantic database describing these objects. Delineation of soil types within SMU, ie spatial disaggregation of SMU allows improved soil information's accuracy using legacy data. The aim of this study was to predict soil types by spatial disaggregation of SMU through a decision tree approach, considering expert knowledge on soil-landscape relationships embedded in soil databases. The DSMART (Disaggregation and Harmonization of Soil Map Units Through resampled Classification Trees) algorithm developed by Odgers et al. (2014) was used. It requires soil information, environmental covariates, and calibration samples, to build then extrapolate decision trees. To assign a soil type to a particular spatial position, a weighed random allocation approach is applied: each soil type in the SMU is weighted according to its assumed proportion of occurrence in the SMU. Thus soil-landscape relationships are not considered in the current version of DSMART. Expert rules on soil distribution considering the relief, parent material and wetlands location were proposed to drive the procedure of allocation of soil type to sampled positions, in order to integrate the soil-landscape relationships. Semantic information about spatial organization of soil types within SMU and exhaustive landscape descriptors were used. In the eastern part of Brittany (NW France), 171 soil types were described; their relative area in the SMU were estimated, geomorphological and geological contexts were recorded. The model predicted 144 soil types. An external validation was performed by comparing predicted with effectively observed soil types derived from available soil maps at scale of 1:25.000 or 1:50.000. Overall accuracies were 63.1% and 36.2%, respectively considering or not the adjacent pixels. The introduction of expert rules based on soil-landscape relationships to allocate soil types to calibration samples enhanced dramatically the results in comparison with a simple weighted random allocation procedure. It also enabled the production of a comprehensive soil map, retrieving expected spatial organization of soils. Estimation of soil properties for various depths is planned using disaggregated soil types, according to the GlobalSoilmap.net specifications. Odgers, N.P., Sun, W., McBratney, A.B., Minasny, B., Clifford, D., 2014. Disaggregating and harmonising soil map units through resampled classification trees. Geoderma 214, 91-100.

Land Application of Wastes: An Educational Program. Case Studies Reviewed - Module 14.

ERIC Educational Resources Information Center

Clarkson, W. W.; And Others

This module provides information about 14 existing land application systems. Each case study gives the location and description of the system, volume treated, climate and soil type, cost, land area, and other data. A brief comment about the system is given as well as a more detailed discussion. References are cited which may be used to examine 100…

NASA applications project in Miami County, Indiana

NASA Technical Reports Server (NTRS)

Johannsen, Chris J.; Fernandez, R. Norberto; Lozano-Garcia, D. Fabian

1990-01-01

This project was designed to acquaint county government officials and their clientele with remote sensing and geographic information systems (GIS) products that contain information about land conditions and land use. The specific project objectives are: (1) to investigate the feasibility of using remotely sensed data to identify and quantify specific land cover categories and conditions for purposes of tax assessment, cropland area measurements, and land use evaluation; (2) to evaluate the use of remotely sensed data to assess soil resources and conditions which affect productivity; (3) to investigate the use of satellite remote sensing data as an aid in assessing soil management practices; and (4) to evaluate the market potential of products derived from the above projects.

Rangeland degradation in savannas of South Africa: spatial patterns of soil and vegetation

NASA Astrophysics Data System (ADS)

Sandhage-Hofmann, Alexandra; Löffler, Jörg; du Preez, Chris; Kotzé, Elmarie; Weijers, Stef; Wundram, Dirk; Zacharias, Maximilan; Amelung, Wulf

2017-04-01

Extensive bush encroachment by Acacia mellifera and associated woody species at semi-arid and arid sites are the most notable forms of rangeland degradation in savannas of South Africa. Concerns are growing over the threat of suppression and loss of nutritious perennial grass species. Grazing and different rangeland management systems (communal and freehold) are considered to be of major importance for degradation, but the process of encroachment is not restricted to communal land. A vegetation change is mostly accompanied by changes in soil properties, where soils in savanna systems can profit from woody species due to litter fall, root distribution, shadow and animal resting time. Savannas are very heterogeneous systems with high spatial variation of patches with wood, herbaceous species and bare ground. We hypothesized that the spatial patterns of soil properties in South Africás rangelands are controlled by present or past vegetation, modulated by the tenure systems with higher rangeland degradation in communal areas. To test this, we sampled soils at communal and commercial land in the Kuruman area of South Africa with the following design: three farms per tenure system, 6 randomly chosen plots (100x100m) per farm, and 25 soil samples (0-10 cm) per plot, each in a 5x5m sampling area. At every sampling point, information of overlying vegetation was recorded (species or bare soil, canopy size, height). For each sampling area, if present, trees/ shrubs were sampled and their ages estimated through the counting of annual growth rings. For each plot, high resolution UAV aerial photos were taken to evaluate the extent of bush encroachment. Analyses involved main physical and chemical soil parameters and isotopic analyses. The results of a rough aerial image classification (grass, woody species, bare ground) revealed significant differences between the tenure systems with higher coverage of bare ground and shrubs at communal farms, and higher grass cover at commercial farms. The tenure systems had no differences in main texture classes of the soils, but significant differences in the composition of the sand fraction, with higher levels of fine sand and lower levels of coarse sand in communal farms. The chemical soil properties showed a high variability both within and between the farms, with much higher variability within communal than commercial farms. Additionally, concentrations of nitrogen, carbon, calcium and pH were significant higher in communal farms. Isotopic analyses in soils showed significant differences for 15N with higher levels in commercial farms. Different photosynthetic pathways are responsible for differences found in 13C values, with higher levels (-16-18‰) in C4-grassland and lower values (-22-26‰) in soils under Acacia (C3). We found relationships between soil properties and species or bare ground, where differences in texture likely interact with both, vegetation cover and soil properties.

Spatial variability and temporal changes in the trace metal content of soils: implications for mine restoration plan.

PubMed

Chandra, Rachna; Prusty, B Anjan Kumar; Azeez, P A

2014-06-01

Trace metals in soils may be inherited from the parent materials or added to the system due to anthropogenic activities. In proposed mining areas, trace metals become an integral part of the soil system. Usually, researchers undertake experiments on plant species selection (for the restoration plan) only after the termination of mining activities, i.e. without any pre-mining information about the soil-plant interactions. Though not shown in studies, it is clear that several recovery plans remain unsuccessful while carrying out restoration experiments. Therefore, we hypothesize that to restore the area effectively, it is imperative to consider the pre-mining scenario of metal levels in parent material as well as the vegetation ecology of the region. With these specifics, we examined the concentrations of trace metals in parent soils at three proposed bauxite locations in the Eastern Ghats, India, and compared them at a spatio-temporal scale. Vegetation quantification and other basic soil parameters accounted for establishing the connection between soil and plants. The study recorded significant spatial heterogeneity in trace metal concentrations and the role of vegetation on metal availability. Oxidation reduction potential (ORP), pH and cation exchange capacity (CEC) directly influenced metal content, and Cu and Ni were lithogenic in origin. It implies that for effective restoration plant species varies for each geological location.

Research on visible and near infrared spectral-polarimetric properties of soil polluted by crude oil

NASA Astrophysics Data System (ADS)

Shen, Hui-yan; Zhou, Pu-cheng; Pan, Bang-long

2017-10-01

Hydrocarbon contaminated soil can impose detrimental effects on forest health and quality of agricultural products. To manage such consequences, oil leak indicators should be detected quickly by monitoring systems. Remote sensing is one of the most suitable techniques for monitoring systems, especially for areas which are uninhabitable and difficulty to access. The most available physical quantities in optical remote sensing domain are the intensity and spectral information obtained by visible or infrared sensors. However, besides the intensity and wavelength, polarization is another primary physical quantity associated with an optical field. During the course of reflecting light-wave, the surface of soil polluted by crude oil will cause polarimetric properties which are related to the nature of itself. Thus, detection of the spectralpolarimetric properties for soil polluted by crude oil has become a new remote sensing monitoring method. In this paper, the multi-angle spectral-polarimetric instrument was used to obtain multi-angle visible and near infrared spectralpolarimetric characteristic data of soil polluted by crude oil. And then, the change rule between polarimetric properties with different affecting factors, such as viewing zenith angle, incidence zenith angle of the light source, relative azimuth angle, waveband of the detector as well as different grain size of soil were discussed, so as to provide a scientific basis for the research on polarization remote sensing for soil polluted by crude oil.

An indigenous Pacific Island agroforestry system: Pohnpei Island

Treesearch

Bill Raynor; James Fownes

1993-01-01

The indigenous agroforestry system on Pohnpei was studied using circular plots laid out in transect across 57 randomly-selected farms. Data were collected on species and cultivar presence, size, density, frequency, as well as soil type, slope, aspect, and other related information. Through farmer interviews, farm family demographic data was also recorded. Seasonality...

Modeling spatial patterns of soil respiration in maize fields from vegetation and soil property factors with the use of remote sensing and geographical information system.

PubMed

Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng

2014-01-01

To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m(-2) s(-1). The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China.

Modeling Spatial Patterns of Soil Respiration in Maize Fields from Vegetation and Soil Property Factors with the Use of Remote Sensing and Geographical Information System

PubMed Central

Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng

2014-01-01

To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m−2 s−1. The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China. PMID:25157827

Data assimilation to extract soil moisture information from SMAP observations

USDA-ARS?s Scientific Manuscript database

This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP) observations. Neural Network(NN) and physically-based SMAP soil moisture retrievals were assimilated into the NASA Catchment model over the contiguous United Sta...

Lunar Resources Using Moderate Spectral Resolution Visible and Near-infrared Spectroscopy: Al/si and Soil Maturity

NASA Technical Reports Server (NTRS)

Fischer, Erich M.; Pieters, Carle M.; Head, James W.

1992-01-01

Modern visible and near-infrared detectors are critically important for the accurate identification and relative abundance measurement of lunar minerals; however, even a very small number of well-placed visible and near-infrared bandpass channels provide a significant amount of general information about crucial lunar resources. The Galileo Solid State Imaging system (SSI) multispectral data are an important example of this. Al/Si and soil maturity will be discussed as examples of significant general lunar resource information that can be gleaned from moderate spectral resolution visible and near-infrared data with relative ease. Because quantitative-albedo data are necessary for these kinds of analyses, data such as those obtained by Galileo SSI are critical. SSI obtained synoptic digital multispectral image data for both the nearside and farside of the Moon during the first Galileo Earth-Moon encounter in December 1990. The data consist of images through seven filters with bandpasses ranging from 0.40 microns in the ultraviolet to 0.99 microns in the near-infrared. Although these data are of moderate spectral resolution, they still provide information for the following lunar resources: (1) titanium content of mature mare soils based upon the 0.40/0.56-micron (UV/VIS) ratio; (2) mafic mineral abundance based upon the 0.76/0.99-micron ratio; and (3) the maturity or exposure age of the soils based upon the 0.56-0.76-micron continuum and the 0.76/0.99-micron ratio. Within constraints, these moderate spectral resolution visible and near-infrared reflectance data can also provide elemental information such as Al/Si for mature highland soils.

Relationships between soil parameters and vegetation in abandoned terrace fields vs. non-terraced fields in arid lands (Lanzarote, Spain): An opportunity for restoration

NASA Astrophysics Data System (ADS)

Arévalo, José Ramón; Fernández-Lugo, Silvia; Reyes-Betancort, J. Alfredo; Tejedor, Marisa; Jiménez, Concepción; Díaz, Francisco J.

2017-11-01

Over 90% of terraced fields have been abandoned on the island of Lanzarote in the last 40 years. The present work analyses the effects of abandonment on the soil and vegetation recovery of terraced field agroecosystems by comparing them with adjacent non-terraced fields in Lanzarote, Canary Islands (Spain). This information is necessary to take the appropriate management actions to achieve goals such as soil protection and biodiversity conservation. Results indicate that terraced fields display better soil quality than non-terraced ones, as shown by the significant differences found in parameters such as SAR, exchangeable Na, CaCO3, B content, moisture content or soil depth. Moreover, the terraced fields' plant community has more species similarities with the native plant community when compared with non-terraced areas. Owing to characteristics such as deeper soils, more water capacity, lower salinity and less sodic soils, terraced soils provide better conditions for passive restoration of both soil and vegetation. Therefore, the recovery and maintenance of wall structures and revegetation with native/endemic species are proposed to promote the restoration of native systems and preserve a landscape with cultural and aesthetic value.

Classification of Effective Soil Depth by Using Multinomial Logistic Regression Analysis

NASA Astrophysics Data System (ADS)

Chang, C. H.; Chan, H. C.; Chen, B. A.

2016-12-01

Classification of effective soil depth is a task of determining the slopeland utilizable limitation in Taiwan. The "Slopeland Conservation and Utilization Act" categorizes the slopeland into agriculture and husbandry land, land suitable for forestry and land for enhanced conservation according to the factors including average slope, effective soil depth, soil erosion and parental rock. However, sit investigation of the effective soil depth requires a cost-effective field work. This research aimed to classify the effective soil depth by using multinomial logistic regression with the environmental factors. The Wen-Shui Watershed located at the central Taiwan was selected as the study areas. The analysis of multinomial logistic regression is performed by the assistance of a Geographic Information Systems (GIS). The effective soil depth was categorized into four levels including deeper, deep, shallow and shallower. The environmental factors of slope, aspect, digital elevation model (DEM), curvature and normalized difference vegetation index (NDVI) were selected for classifying the soil depth. An Error Matrix was then used to assess the model accuracy. The results showed an overall accuracy of 75%. At the end, a map of effective soil depth was produced to help planners and decision makers in determining the slopeland utilizable limitation in the study areas.

Comparison of regression coefficient and GIS-based methodologies for regional estimates of forest soil carbon stocks.

PubMed

Campbell, J Elliott; Moen, Jeremie C; Ney, Richard A; Schnoor, Jerald L

2008-03-01

Estimates of forest soil organic carbon (SOC) have applications in carbon science, soil quality studies, carbon sequestration technologies, and carbon trading. Forest SOC has been modeled using a regression coefficient methodology that applies mean SOC densities (mass/area) to broad forest regions. A higher resolution model is based on an approach that employs a geographic information system (GIS) with soil databases and satellite-derived landcover images. Despite this advancement, the regression approach remains the basis of current state and federal level greenhouse gas inventories. Both approaches are analyzed in detail for Wisconsin forest soils from 1983 to 2001, applying rigorous error-fixing algorithms to soil databases. Resulting SOC stock estimates are 20% larger when determined using the GIS method rather than the regression approach. Average annual rates of increase in SOC stocks are 3.6 and 1.0 million metric tons of carbon per year for the GIS and regression approaches respectively.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

PubMed

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

PubMed Central

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points. PMID:26807579

3D Electrical Resistivity Tomography and Mise-à-la-Masse Method as Tools for the Characterization of Vine Roots

NASA Astrophysics Data System (ADS)

Boaga, J.; Mary, B.; Peruzzo, L.; Schmutz, M.; Wu, Y.; Hubbard, S. S.; Cassiani, G.

2017-12-01

The interest on non-invasive geophysical monitoring of soil properties and root architecture is rapidly growing. Despite this, few case studies exist concerning vineyards, which are economically one of the leading sectors of agriculture. In this study, we integrate different geophysical methods in order to gain a better imaging of the vine root system, with the aim of quantifying root development, a key factor to understand roots-soil interaction and water balance. Our test site is a vineyard located in Bordeaux (France), where we adopted the Mise-a-la-Masse method (MALM) and micro-scale electrical resistivity tomography (ERT) on the same 3D electrode configuration. While ERT is a well-established technique to image changes in soil moisture content by root activity, MALM is a relatively new approach in this field of research. The idea is to inject current directly in the plant trunk and verify the resulting voltage distribution in the soil, as an effect of current distribution through the root system. In order to distinguish the root effect from other phenomena linked to the soil heterogeneities, we conducted and compared MALM measurements acquired through injecting current into the stem and into the soil near the stem. Moreover, the MALM data measured in the field were compared with numerical simulations to improve the confidence in the interpretation. Differences obtained between the stem and soil injection clearly validated the assumption that the whole root system is acting as a current pathway, thus highlighting the locations at depth where current is entering the soil from the fine roots. The simulation results indicated that the best fit is obtained through considering distributed sources with depth, reflecting a probable root zone area. The root location and volume estimated using this procedure are in agreement with vineyard experimental evidence. This work suggests the promising application of electrical methods to locate and monitor root systems. Further work is necessary to effectively integrate the geophysical and plant physiology information.

Impacts of Repeated Glyphosate Use on Wheat-Associated Bacteria Are Small and Depend on Glyphosate Use History.

PubMed

Schlatter, Daniel C; Yin, Chuntao; Hulbert, Scot; Burke, Ian; Paulitz, Timothy

2017-11-15

Glyphosate is the most widely used herbicide worldwide and a critical tool for weed control in no-till cropping systems. However, there are concerns about the nontarget impacts of long-term glyphosate use on soil microbial communities. We investigated the impacts of repeated glyphosate treatments on bacterial communities in the soil and rhizosphere of wheat in soils with and without long-term history of glyphosate use. We cycled wheat in the greenhouse using soils from 4 paired fields under no-till (20+-year history of glyphosate) or no history of use. At each cycle, we terminated plants with glyphosate (2× the field rate) or by removing the crowns, and soil and rhizosphere bacterial communities were characterized. Location, cropping history, year, and proximity to the roots had much stronger effects on bacterial communities than did glyphosate, which only explained 2 to 5% of the variation. Less than 1% of all taxa were impacted by glyphosate, more in soils with a long history of use, and more increased than decreased in relative abundance. Glyphosate had minimal impacts on soil and rhizosphere bacteria of wheat, although dying roots after glyphosate application may provide a "greenbridge" favoring some copiotrophic taxa. IMPORTANCE Glyphosate (Roundup) is the most widely used herbicide in the world and the foundation of Roundup Ready soybeans, corn, and the no-till cropping system. However, there have been recent concerns about nontarget impacts of glyphosate on soil microbes. Using next-generation sequencing methods and glyphosate treatments of wheat plants, we described the bacterial communities in the soil and rhizosphere of wheat grown in Pacific Northwest soils across multiple years, different locations, and soils with different histories of glyphosate use. The effects of glyphosate were subtle and much less than those of drivers such as location and cropping systems. Only a small percentage of the bacterial groups were influenced by glyphosate, and most of those were stimulated, probably because of the dying roots. This study provides important information for the future of this important tool for no-till systems and the environmental benefits of reducing soil erosion and fossil fuel inputs. This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply.

Assessment of organic matter resistance to biodegradation in volcanic ash soils assisted by automated interpretation of infrared spectra from humic acid and whole soil samples by using partial least squares

NASA Astrophysics Data System (ADS)

Hernández, Zulimar; Pérez Trujillo, Juan Pedro; Hernández-Hernández, Sergio Alexander; Almendros, Gonzalo; Sanz, Jesús

2014-05-01

From a practical viewpoint, the most interesting possibilities of applying infrared (IR) spectroscopy to soil studies lie on processing IR spectra of whole soil (WS) samples [1] in order to forecast functional descriptors at high organizational levels of the soil system, such as soil C resilience. Currently, there is a discussion on whether the resistance to biodegradation of soil organic matter (SOM) depends on its molecular composition or on environmental interactions between SOM and mineral components, such could be the case with physical encapsulation of particulate SOM or organo-mineral derivatives, e.g., those formed with amorphous oxides [2]. A set of about 200 dependent variables from WS and isolated, ash free, humic acids (HA) [3] was obtained in 30 volcanic ash soils from Tenerife Island (Spain). Soil biogeochemical properties such as SOM, allophane (Alo + 1 /2 Feo), total mineralization coefficient (TMC) or aggregate stability were determined in WS. In addition, structural information on SOM was obtained from the isolated HA fractions by visible spectroscopy and analytical pyrolysis (Py-GC/MS). Aiming to explore the potential of partial least squares regression (PLS) in forecasting soil dependent variables, exclusively using the information extracted from WS and HA IR spectral profiles, data were processed by using ParLeS [4] and Unscrambler programs. Data pre-treatments should be carefully chosen: the most significant PLS models from IR spectra of HA were obtained after second derivative pre-treatment, which prevented effects of intrinsically broadband spectral profiles typical in macromolecular heterogeneous material such as HA. Conversely, when using IR spectra of WS, the best forecasting models were obtained using linear baseline correction and maximum normalization pre-treatment. With WS spectra, the most successful prediction models were obtained for SOM, magnetite, allophane, aggregate stability, clay and total aromatic compounds, whereas the PLS-model for TMC was of little significance. On the other hand, the best successful prediction models using HA spectra were for SOM, TMC, allophane content and soil fungal pigments. In these particular volcanic ash soils, with large concentration of short-range minerals, the use of WS spectra, compared to the use of HA spectra, led to predict higher number of dependent variables. This is interpreted as the fact that the information of mineral constituents may help to explain soil emergent properties (e.g., SOM resilience or hydrophysical properties). The above results coincide with previous research [2] based on classification of soil properties by multidimensional scaling, where it was demonstrated that formation of stable organomineral complexes between HA and allophane coincide with large amounts of SOM and low TMC values. [1] Viscarra Rossel, R.A., Walvoort, D.J.J., McBratney, A.B., Janik, L.J. & Skjemstad, J.O. 2006. Geoderma 131, 59-75. [2] Hernández, Z., Almendros, G. 2012. Soil Biology & Biochemistry 44, 130-142. [3] Hernández, Z. 2009. Functional study of soil organic matter in vineyards from Tenerife Island (Spain). PhD. University of Alcalá, Alcalá de Henares, Madrid. [4] Viscarra-Rossel, R.A. 2008. Chemometrics & Intelligent Laboratory Systems 90, 72-83.

Remote sensing and geographic information system for appraisal of salt-affected soils in India.

PubMed

Singh, Gurbachan; Bundela, D S; Sethi, Madhurama; Lal, Khajanchi; Kamra, S K

2010-01-01

Quantification of the nature, extent, and spatial distribution of salt-affected soils (SAS) for India and the world is essential for planning and implementing reclamation programs in a timely and cost-effective manner for sustained crop production. The national extent of SAS for India over the last four decades was assessed by conventional and remote sensing approaches using diverse methodologies and class definitions and ranged from 6.0 to 26.1 million hectares (Mha) and 1.2 to 10.1 Mha, respectively. In 1966, an area of 6 Mha under SAS was first reported using the former approach. Three national estimates, obtained using remote sensing, were reconciled using a geographic information system, resulting in an acceptable extent of 6.73 Mha. Moderately and severely salt-encrusted lands having large contiguous area have been correctly mapped, but slightly salt-encrusted land having smaller affected areas within croplands has not been accurately mapped. Recent satellite sensors (e.g., Resourcesat-1, Cartosat-2, IKONOS-II, and RISAT-2), along with improved image processing techniques integrated with terrain and other spatial data using a geographic information system, are enabling mapping at large scale. Significant variations in salt encrustation at the surface caused by soil moisture, waterlogging conditions, salt-tolerant crops, and dynamics of subsurface salts present constraints in appraisal, delineation, and mapping efforts. The article provides an overview of development, identification, characterization, and delineation of SAS, past and current national scenarios of SAS using conventional and remote sensing approaches, reconciliation of national estimates, issues of SAS mapping, and future scope.

SaLEM (v1.0) - the Soil and Landscape Evolution Model (SaLEM) for simulation of regolith depth in periglacial environments

NASA Astrophysics Data System (ADS)

Bock, Michael; Conrad, Olaf; Günther, Andreas; Gehrt, Ernst; Baritz, Rainer; Böhner, Jürgen

2018-04-01

We propose the implementation of the Soil and Landscape Evolution Model (SaLEM) for the spatiotemporal investigation of soil parent material evolution following a lithologically differentiated approach. Relevant parts of the established Geomorphic/Orogenic Landscape Evolution Model (GOLEM) have been adapted for an operational Geographical Information System (GIS) tool within the open-source software framework System for Automated Geoscientific Analyses (SAGA), thus taking advantage of SAGA's capabilities for geomorphometric analyses. The model is driven by palaeoclimatic data (temperature, precipitation) representative of periglacial areas in northern Germany over the last 50 000 years. The initial conditions have been determined for a test site by a digital terrain model and a geological model. Weathering, erosion and transport functions are calibrated using extrinsic (climatic) and intrinsic (lithologic) parameter data. First results indicate that our differentiated SaLEM approach shows some evidence for the spatiotemporal prediction of important soil parental material properties (particularly its depth). Future research will focus on the validation of the results against field data, and the influence of discrete events (mass movements, floods) on soil parent material formation has to be evaluated.

Inferring soil salinity in a drip irrigation system from multi-configuration EMI measurements using adaptive Markov chain Monte Carlo

NASA Astrophysics Data System (ADS)

Zaib Jadoon, Khan; Umer Altaf, Muhammad; McCabe, Matthew Francis; Hoteit, Ibrahim; Muhammad, Nisar; Moghadas, Davood; Weihermüller, Lutz

2017-10-01

A substantial interpretation of electromagnetic induction (EMI) measurements requires quantifying optimal model parameters and uncertainty of a nonlinear inverse problem. For this purpose, an adaptive Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to assess multi-orientation and multi-offset EMI measurements in an agriculture field with non-saline and saline soil. In MCMC the posterior distribution is computed using Bayes' rule. The electromagnetic forward model based on the full solution of Maxwell's equations was used to simulate the apparent electrical conductivity measured with the configurations of EMI instrument, the CMD Mini-Explorer. Uncertainty in the parameters for the three-layered earth model are investigated by using synthetic data. Our results show that in the scenario of non-saline soil, the parameters of layer thickness as compared to layers electrical conductivity are not very informative and are therefore difficult to resolve. Application of the proposed MCMC-based inversion to field measurements in a drip irrigation system demonstrates that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil, and provides useful insight about parameter uncertainty for the assessment of the model outputs.

Customer-oriented Data Formats and Services for Global Land Data Assimilation System (GLDAS) Products at the NASA GES DISC

NASA Technical Reports Server (NTRS)

Fang, Hongliang; Beaudoing, Hiroko; Rodell, Matthew; Teng, BIll; Vollmer, Bruce

2008-01-01

The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface Models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of NASA Goddard Earth Sciences Data and Information Services Center (GESDISC).

Digital soil mapping in assessment of land suitability for organic farming

NASA Astrophysics Data System (ADS)

Ghambashidze, Giorgi; Kentchiashvili, Naira; Tarkhnishvili, Maia; Jolokhava, Tamar; Meskhi, Tea

2017-04-01

Digital soil mapping (DSM) is a fast-developing sub discipline of soil science which gets more importance along with increased availability of spatial data. DSM is based on three main components: the input in the form of field and laboratory observational methods, the process used in terms of spatial and non-spatial soil inference systems, and the output in the form of spatial soil information systems, which includes outputs in the form of rasters of prediction along with the uncertainty of prediction. Georgia is one of the countries who are under the way of spatial data infrastructure development, which includes soil related spatial data also. Therefore, it is important to demonstrate the capacity of DSM technics for planning and decision making process, in which assessment of land suitability is a major interest for those willing to grow agricultural crops. In that term land suitability assessment for establishing organic farms is in high demand as market for organically produced commodities is still increasing. It is the first attempt in Georgia to use DSM to predict areas with potential for organic farming development. Current approach is based on risk assessment of soil pollution with toxic elements (As, Hg, Pb, Cd, Cr) and prediction of bio-availability of those elements to plants on example of the region of Western Georgia, where detailed soil survey was conducted and spatial database of soil was created. The results of the study show the advantages of DSM at early stage assessment and depending on availability and quality of the input data, it can achieve acceptable accuracy.

Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture

USGS Publications Warehouse

McNally, Amy; Gregory J. Husak,; Molly Brown,; Carroll, Mark L.; Funk, Christopher C.; Soni Yatheendradas,; Kristi Arsenault,; Christa Peters-Lidard,; Verdin, James

2015-01-01

The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.

Downscaling SMAP Radiometer Soil Moisture over the CONUS using Soil-Climate Information and Ensemble Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, P.; Moradkhani, H.

2017-12-01

Soil moisture contributes significantly towards the improvement of weather and climate forecast and understanding terrestrial ecosystem processes. It is known as a key hydrologic variable in the agricultural drought monitoring, flood modeling and irrigation management. While satellite retrievals can provide an unprecedented information on soil moisture at global-scale, the products are generally at coarse spatial resolutions (25-50 km2). This often hampers their use in regional or local studies, which normally require a finer resolution of the data set. This work presents a new framework based on an ensemble learning method while using soil-climate information derived from remote-sensing and ground-based observations to downscale the level 3 daily composite version (L3_SM_P) of SMAP radiometer soil moisture over the Continental U.S. (CONUS) at 1 km spatial resolution. In the proposed method, a suite of remotely sensed and in situ data sets in addition to soil texture information and topography data among others were used. The downscaled product was validated against in situ soil moisture measurements collected from a limited number of core validation sites and several hundred sparse soil moisture networks throughout the CONUS. The obtained results indicated a great potential of the proposed methodology to derive the fine resolution soil moisture information applicable for fine resolution hydrologic modeling, data assimilation and other regional studies.

Prediction of sedimentation using integration of RS, RUSLE model and GIS in Cameron Highlands, Pahang, Malaysia

NASA Astrophysics Data System (ADS)

Ghani, A. H. A.; Lihan, T.; Rahim, S. A.; Musthapha, M. A.; Idris, W. M. R.; Rahman, Z. A.

2013-11-01

Soil erosion and sediment yield are strongly affected by land use change. Spatially distributed erosion models are of great interest to predict soil erosion loss and sediment yield. Hence, the objective of this study was to determine sediment yield using Revised Universal Soil Loss Equation (RUSLE) model in Geographical Information System (GIS) environment at Cameron Highlands, Pahang, Malaysia. Sediment yield at the study area was determined using RUSLE model in GIS environment The RUSLE factors were computed by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using soil map and field measurement, vegetation cover (C) using satellite images, length and steepness (LS) using contour map and conservation practices using satellite images based on land use/land cover. Field observations were also done to verify the predicted sediment yield. The results indicated that the rate of sediment yield in the study area ranged from very low to extremely high. The higher SY value can be found at middle and lower catchments of Cameron Highland. Meanwhile, the lower SY value can be found at the north part of the study area. Sediment yield value turned out to be higher close to the river due to the topographic characteristic, vegetation type and density, climate and land use within the drainage basin.

Rocky Mountain Arsenal North Boundary Expansion Containment System Construction Foundation Report

DTIC Science & Technology

1984-03-01

APPENDIX C Am-Built Wall Data * 4 ’ FIG Timur TitleLa 2-1 Grain Size Analysis Soil A 2-3ii 2-2 Grain Size Analysis Soil 3 2-3iii 2-3 Finite Difference...letter request for investigation from the Great West- ern Sugar Company to Brigadier General C. S. Shadle, IA, dated 4 June 1954. A subsequent letter...from the Great Western Sugar Company to the Chief of Engineering and Service Division, IKA, dated 18 June 1954, related sore information concerning

Assessing the Utility of 3-km Land Information System Soil Moisture Data for Drought Monitoring and Hydrologic Applications

NASA Technical Reports Server (NTRS)

White, Kristopher D.; Case, Jonathan L.

2014-01-01

The NASA Short term Prediction Research and Transition (SPoRT) Center in Huntsville, AL has been running a real-time configuration of the Noah land surface model within the NASA Land Information System (LIS) since June 2010. The SPoRT LIS version is run as a stand-alone land surface model over a Southeast Continental U.S. domain with 3-km grid spacing. The LIS contains output variables including soil moisture and temperature at various depths, skin temperature, surface heat fluxes, storm surface runoff, and green vegetation fraction (GVF). The GVF represents another real-time SPoRT product, which is derived from the Moderate Resolution Imaging Spectroradiometer instrument aboard NASA's Aqua and Terra satellites. These data have demonstrated operational utility for drought monitoring and hydrologic applications at the National Weather Service (NWS) office in Huntsville, AL since early 2011. The most relevant data for these applications have proven to be the moisture availability (%) in the 0-10 cm and 0-200 cm layers, and the volumetric soil moisture (%) in the 0-10 cm layer. In an effort to better understand their applicability among locations with different terrain, soil and vegetation types, SPoRT is conducting the first formal assessment of these data at NWS offices in Houston, TX, Huntsville, AL and Raleigh, NC during summer 2014. The goal of this assessment is to evaluate the LIS output in the context of assessing flood risk and determining drought designations for the U.S. Drought Monitor. Forecasters will provide formal feedback via a survey question web portal, in addition to the NASA SPoRT blog. In this presentation, the SPoRT LIS and its applications at NWS offices will be presented, along with information about the summer assessment, including training module development and preliminary results.

Compensatory Root Water Uptake of Overlapping Root Systems

NASA Astrophysics Data System (ADS)

Agee, E.; Ivanov, V. Y.; He, L.; Bisht, G.; Shahbaz, P.; Fatichi, S.; Gough, C. M.; Couvreur, V.; Matheny, A. M.; Bohrer, G.

2015-12-01

Land-surface models use simplified representations of root water uptake based on biomass distributions and empirical functions that constrain water uptake during unfavorable soil moisture conditions. These models fail to capture the observed hydraulic plasticity that allows plants to regulate root hydraulic conductivity and zones of active uptake based on local gradients. Recent developments in root water uptake modeling have sought to increase its mechanistic representation by bridging the gap between physically based microscopic models and computationally feasible macroscopic approaches. It remains to be demonstrated whether bulk parameterization of microscale characteristics (e.g., root system morphology and root conductivity) can improve process representation at the ecosystem scale. We employ the Couvreur method of microscopic uptake to yield macroscopic representation in a coupled soil-root model. Using a modified version of the PFLOTRAN model, which represents the 3-D physics of variably saturated soil, we model a one-hectare temperate forest stand under natural and synthetic climatic forcing. Our results show that as shallow soil layers dry, uptake at the tree and stand level shift to deeper soil layers, allowing the transpiration stream demanded by the atmosphere. We assess the potential capacity of the model to capture compensatory root water uptake. Further, the hydraulic plasticity of the root system is demonstrated by the quick response of uptake to rainfall pulses. These initial results indicate a promising direction for land surface models in which significant three-dimensional information from large root systems can be feasibly integrated into the forest scale simulations of root water uptake.

The PRESSCA operational early warning system for landslide forecasting: the 11-12 November 2013 rainfall event in Central Italy.

NASA Astrophysics Data System (ADS)

Ciabatta, Luca; Brocca, Luca; Ponziani, Francesco; Berni, Nicola; Stelluti, Marco; Moramarco, Tommaso

2014-05-01

The Umbria Region, located in Central Italy, is one of the most landslide risk prone area in Italy, almost yearly affected by landslides events at different spatial scales. For early warning procedures aimed at the assessment of the hydrogeological risk, the rainfall thresholds represent the main tool for the Italian Civil Protection System. As shown in previous studies, soil moisture plays a key-role in landslides triggering. In fact, acting on the pore water pressure, soil moisture influences the rainfall amount needed for activating a landslide. In this work, an operational physically-based early warning system, named PRESSCA, that takes into account soil moisture for the definition of rainfall thresholds is presented. Specifically, the soil moisture conditions are evaluated in PRESSCA by using a distributed soil water balance model that is recently coupled with near real-time satellite soil moisture product obtained from ASCAT (Advanced SCATterometer) and from in-situ monitoring data. The integration of three different sources of soil moisture information allows to estimate the most accurate possible soil moisture condition. Then, both observed and forecasted rainfall data are compared with the soil moisture-based thresholds in order to obtain risk indicators over a grid of ~ 5 km. These indicators are then used for the daily hydrogeological risk evaluation and management by the Civil Protection regional service, through the sharing/delivering of near real-time landslide risk scenarios (also through an open source web platform: www.cfumbria.it). On the 11th-12th November, 2013, Umbria Region was hit by an exceptional rainfall event with up to 430mm/72hours that resulted in significant economic damages, but fortunately no casualties among the population. In this study, the results during the rainfall event of PRESSCA system are described, by underlining the model capability to reproduce, two days in advance, landslide risk scenarios in good spatial and temporal agreement with the occurred actual conditions. High-resolution risk scenarios (100mx100m), obtained by coupling PRESSCA forecasts with susceptibility and vulnerability layers, are also produced. The results show good relationship between the PRESSCA forecast and the reported landslides to the Civil Protection Service during the rainfall event, confirming the system robustness. The good forecasts of PRESSCA system have surely contributed to start well in advance the Civil Protection operations (alerting local authorities and population).

HANDBOOK ON ADVANCED NONPHOTOCHEMICAL OXIDATION PROCESSES

EPA Science Inventory

The purpose of this handbook is to summarize commercial-scale system performance and cost data for advanced nonphotochemical oxidation (ANPO) treatment of contaminated water, air, and soil. Similar information from pilot-and bench-scale evaluations of ANPO processes is also inclu...

The assessment of the energetic compound 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-Hexaazaisowurtzitane (CL-20) degradability in soil.

PubMed

Strigul, Nikolay; Braida, Washington; Christodoulatos, Christos; Balas, Wendy; Nicolich, Steven

2006-01-01

CL-20 is a relatively new energetic compound with applications in explosive and propellant formulations. Currently, information about the fate of CL-20 in ecological systems is scarce. The aim of this study is to evaluate the biodegradability of CL-20 in soil environments. Four soils were used where initial CL-20 concentrations (above water solubility) ranged from 125 to 1500 mg of CL-20 per kg dry soil (corresponding to the concentrations derived from unexploded ordnance, low order detonation, or manufacturing spills). CL-20 appears to be biodegradable in soil under anaerobic conditions, and additions of organic substrates can substantially accelerate this process. However, CL-20 is not degraded in soil under aerobic conditions kept in the dark at temperatures up to 30 degrees C without organic amendments. Additions of starch or cellulose promote the biodegradation of CL-20 under aerobic conditions. Soil microbial community mediated biodegradation and plant uptake appears to enhance CL-20 biodegradation, the latter suggesting a possible route for CL-20 to entry in the food chain.

Remote sensing of soils, land forms, and land use in the northern Great Plains in preparation for ERTS applications

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Westin, F. C.; Gropper, J.; Myers, V. I.

1972-01-01

Research to determine the optimum time or season for obtaining imagery to identify and map soil limitations was conducted in the proposed Oahe irrigation project area in South Dakota. The optimum time for securing photographs or imagery is when the soil surface patterns are most apparent. For cultivated areas similar to the study area, May is the optimum time. The density slicing analysis of the May image provided additional and more accurate information than did the existing soil map. The soil boundaries were more accurately located. The use of a density analysis system for an operational soil survey has not been tested, but is obviously dependent upon securing excellent photographs for interpretation. The colors or densities of photographs will have to be corrected for sun angle effects, vignetting effects, and processing to have maximum effectiveness for mapping soil limitations. Rangeland sites were established in Bennett County, South Dakota to determine the usefulness of ERTS imagery. Imagery from these areas was interpreted for land use and drainage patterns.

Evaluating the first Brazilian program of payments for environmental services: An approach for optimizing soil conservation using GIS

NASA Astrophysics Data System (ADS)

Zolin, C. A.; Folegatti, M. V.; Mingoti, R.; Paulino, J.; Sánchez-Román, R. M.; González, A. M.

2013-12-01

Brazil possesses one of the most important water assets in the world, however, the country experiences vast differences among its hydrographic regions. Although Brazil has the largest water reserves in the world, those reserves are not distributed according to the concentration of the population. In addition, the largest portions of these water reserves are not always located where the highest urban concentrations and demands occur, which causes serious problems in maintaining water supply within the country's most populous regions (Zolin et al. 2011). It has become evident that policies aimed at mitigating the growing water resources and water use conflicts in Brazil are crucial. The municipality of Extrema in Minas Gerais state in Brazil pioneered the first Brazilian municipal PES initiative (Conservador das Águas program), based on the relationship between forests and the benefits they provide. This study aimed to assess soil loss in the Posses sub-basin, where the Conservador das Águas program began. Additionally, we aimed to determine the potential that this PES initiative has for soil conservation, as well as to optimize the environmental services provided as a function of forest area size and location. In this sense, considering the prescribed conservation practices, land use situation, and soil cover in the Posses sub-basin, we analyzed the effectiveness of the Conservador das Águas program before and after implementation in relation to reduced soil loss under different land use and soil cover scenarios. We used a geographic information system (GIS) for spatializing and producing different information plans and the Revised Universal Soil Loss Equation (RUSLE) for estimating soil loss. As a result, we found that optimized soil conservation may be obtained by adopting pasture conservation practices. Additionally the expected average soil loss in the Posses sub-basin under conditions of land use and soil cover, before and after implementing the water conservation program, was 30.63 and 7.06 Mg ha-1 year-1, respectively.

FOREST SOIL INFORMATION FOR ENVIRONMENTAL ASSESSMENT IN THE WESTERN OREGON CASCADES BASED ON LANDTYPE MAPPING

EPA Science Inventory

Forest health monitoring and other environmental assessments require information on the spatial distribution of basic soil physical and chemical properties. Traditional soil surveys are not available for large areas of forestland in the western US but there are some soil resour...

Remote sensing as a tool for estimating soil erosion potential

NASA Technical Reports Server (NTRS)

Morris-Jones, D. R.; Morgan, K. M.; Kiefer, R. W.

1979-01-01

The Universal Soil Loss Equation is a frequently used methodology for estimating soil erosion potential. The Universal Soil Loss Equation requires a variety of types of geographic information (e.g. topographic slope, soil erodibility, land use, crop type, and soil conservation practice) in order to function. This information is traditionally gathered from topographic maps, soil surveys, field surveys, and interviews with farmers. Remote sensing data sources and interpretation techniques provide an alternative method for collecting information regarding land use, crop type, and soil conservation practice. Airphoto interpretation techniques and medium altitude, multi-date color and color infrared positive transparencies (70mm) were utilized in this study to determine their effectiveness for gathering the desired land use/land cover data. Successful results were obtained within the test site, a 6136 hectare watershed in Dane County, Wisconsin.

[Changes of soil physical properties during the conversion of cropland to agroforestry system].

PubMed

Wang, Lai; Gao, Peng Xiang; Liu, Bin; Zhong, Chong Gao; Hou, Lin; Zhang, Shuo Xin

2017-01-01

To provide theoretical basis for modeling and managing agroforestry systems, the influence of conversion of cropland to agroforestry system on soil physical properties was investigated via a walnut (Juglans regia)-wheat (Triticum aestivum) intercropping system, a wide spreading local agroforestry model in northern Weihe River of loess area, with the walnut and wheat monoculture systems as the control. The results showed that the improvement of the intercropping system on soil physical properties mainly appeared in the 0-40 cm soil layer. The intercropping system could prevent soil bulk density rising in the surface soil (0-20 cm), and the plow pan in the 20-40 cm soil layer could be significantly alleviated. The intercropping system had conti-nuous improvement on soil field capacity in each soil layer with the planting age increase, and the soil field capacity was higher than that of each monoculture system in each soil layer (except 20-40 cm soil layer) since the 5th year after planting. The intercropping system had continuous improvement on soil porosity in each soil layer, but mainly in the 0-20 and 20-40 cm soil layer, and the ratio of capillary porosity was also improved. The soil bulk density, field capacity and soil porosity obtained continuous improvement during the conversion of cropland to agroforestry system, and the improvement on soil physical properties was stronger in shallow soil layer than in deep soil.

Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

NASA Astrophysics Data System (ADS)

Sheffield, J.; Lobell, D. B.; Wood, E. F.

2010-12-01

Monitoring drought globally is challenging because of the lack of dense in-situ hydrologic data in many regions. In particular, soil moisture measurements are absent in many regions and in real time. This is especially problematic for developing regions such as Africa where water information is arguably most needed, but virtually non-existent on the ground. With the emergence of remote sensing estimates of all components of the water cycle there is now the potential to monitor the full terrestrial water cycle from space to give global coverage and provide the basis for drought monitoring. These estimates include microwave-infrared merged precipitation retrievals, evapotranspiration based on satellite radiation, temperature and vegetation data, gravity recovery measurements of changes in water storage, microwave based retrievals of soil moisture and altimetry based estimates of lake levels and river flows. However, many challenges remain in using these data, especially due to biases in individual satellite retrieved components, their incomplete sampling in time and space, and their failure to provide budget closure in concert. A potential way forward is to use modeling to provide a framework to merge these disparate sources of information to give physically consistent and spatially and temporally continuous estimates of the water cycle and drought. Here we present results from our experimental global water cycle monitor and its African drought monitor counterpart (http://hydrology.princeton.edu/monitor). The system relies heavily on satellite data to drive the Variable Infiltration Capacity (VIC) land surface model to provide near real-time estimates of precipitation, evapotranspiraiton, soil moisture, snow pack and streamflow. Drought is defined in terms of anomalies of soil moisture and other hydrologic variables relative to a long-term (1950-2000) climatology. We present some examples of recent droughts and how they are identified by the system, including objective quantification and tracking of their spatial-temporal characteristics. Further we present strategies for merging various sources of information, including bias correction of satellite precipitation and assimilation of remotely sensed soil moisture, which can augment the monitoring in regions where satellite precipitation is most uncertain. Ongoing work is adding a drought forecast component based on a successful implementation over the U.S. and agricultural productivity estimates based on output from crop yield models. The forecast component uses seasonal global climate forecasts from the NCEP Climate Forecast System (CFS). These are merged with observed climatology in a Bayesian framework to produce ensemble atmospheric forcings that better capture the uncertainties. At the same time, the system bias corrects and downscales the monthly CFS data. We show some initial seasonal (up to 6-month lead) hydrologic forecast results for the African system. Agricultural monitoring is based on the precipitation, temperature and soil moisture from the system to force statistical and process based crop yield models. We demonstrate the feasibility of monitoring major crop types across the world and show a strategy for providing predictions of yields within our drought forecast mode.

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.

Use of geographic information management systems (GIMS) for nitrogen management

NASA Astrophysics Data System (ADS)

Diker, Kenan

1998-11-01

Geographic Information Management Systems (GIMS) was investigated in this study to develop an efficient nitrogen management scheme for corn. The study was conducted on two experimental corn sites. The first site consisted of six non-replicated plots where the canopy reflectance of corn at six nitrogen fertilizer levels was investigated. The reflectance measurements were conducted for nadir and 75sp° view angles. Data from these plots were used to develop relationships between reflectance data and soil and plant parameters. The second site had four corn plots fertilized by different methods such as spoon-fed, pre-plant and side-dress, which created nitrogen variability within the field. Soil and plant nitrogen as well as leaf area, biomass, percent cover measurements, and canopy reflectance data were collected at various growth stages from both sites during the 1995 and 1996 growing seasons. Relationships were developed between the Nitrogen Reflectance Index (NRI) developed by Bausch et al. (1994) and soil and plant variables. Spatial dependence of data was determined by geostatistical methods; variability was mapped in ArcView. Results of this study indicated that the NRI is a better estimator of plant nitrogen status than chlorophyll meter measurements. The NRI can successfully be used to estimate the spatial distribution of soil nitrogen estimates through the plant nitrogen status as well as plant parameters and the yield potential. GIS mapping of measured and estimated soil nitrogen agreed except in locations where hot spots were measured. The NRI value of 0.95 seemed to be the critical value for plant nitrogen status especially for the 75sp° view. The nadir view tended to underestimate plant and soil parameters, whereas, the 75sp° view slightly overestimated these parameters. If available, the 75sp° view data should be used before the tasseling stage for reflectance measurements to reduce the soil background effect. However, it is sensitive to windy conditions. After tasseling, the nadir view should be used because the 75sp° view is obstructed by tassels. Total soil nitrogen at the V6 growth stage was underestimated by the NRI for both view angles. Results also indicated that a nitrogen prescription could be estimated at various growth stages.

Agriculture Canada Central Saskatchewan Vector Soils Data

NASA Technical Reports Server (NTRS)

Knapp, David; Hall, Forrest G. (Editor); Rostad, Harold

2000-01-01

This data set consists of GIS layers that describe the soils of the BOREAS SSA. These original data layers were submitted as vector data in ARC/INFO EXPORT format. These data also include the soil name and soil layer files, which provide additional information about the soils. There are three sets of attributes that include information on the primary, secondary, and tertiary soil type within each polygon. Thus, there is a total of nine main attributes in this data set.

Response of soil biota to vineyard interrow soil cultivation can be altered by the surrounding landscape

NASA Astrophysics Data System (ADS)

Zaller, Johann; Buchholz, Jacob; Querner, Pascal; Paredes, Daniel; Kratschmer, Sophie; Schwantzer, Martina; Winter, Silvia; Strauss, Peter; Bauer, Thomas; Burel, Françoise; Guernion, Muriel; Scimia, Jennifer; Nicolai, Annegret; Cluzeau, Daniel

2017-04-01

Ecosystem services provided by viticultural landscapes result from interactions between management intensity, soil properties, organisms inhabiting these landscapes, and the diversity and structure of the surrounding landscape. However, there is actually very little known to what extent these different factors influence the abundance and diversity of various soil biota. In this study we examined (i) to what extent different soil management intensities of interrows affect the activity and diversity of soil biota (earthworms, Collembola, litter decomposition), (ii) the role of soil properties in influencing these effects and (iii) whether the surrounding landscape structure is altering these interactions. We collected data in 16 vineyards in Austria embedded in landscapes with varying structure (i.e. from structurally simple to complex) and assessed earthworms (hand sorting), Collembola (pitfall trapping and soil coring), litter decomposition (tea bag method). Additionally, soil physical (water infiltration, aggregate stability, porosity, bulk density, soil texture) and chemical (pH, soil carbon content, cation exchange capacity, potassium, phosphorus) parameters were assessed. The landscape surrounding our vineyards within a radius of 750 m was assessed by field mapping using a geographical information system. Results showed that different soil biota/processes are differently affected by soil cultivation intensity and soil properties. Parameters describing the surrounding landscape interacted more with the responses of Collembola to soil cultivation than with earthworms or litter decomposition. These investigations are part of the transdisciplinary BiodivERsA project VineDivers (www.vinedivers.eu) and will ultimately lead into management recommendations for various stakeholders.

Selected Aspects of Soil Science History in the USA - Prehistory to the 1970s

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Fenton, Thomas E.; Homburg, Jeffrey A.

2017-04-01

Interest in understanding America's soils originated in prehistory with Native Americans. Following European settlement, notable individuals such as Thomas Jefferson and Lewis and Clark made observations of soil resources. Moving into the 1800s, state geological surveys became involved in soil work and E.W. Hilgard started to formulate ideas similar to those that would eventually lead to V.V. Dokuchaev being recognized as the father of modern soil science. However, Hilgard's advanced ideas on soil genesis were not accepted by the wider American soil science community at the time. Moving into the 1900s, the National Cooperative Soil Survey, the first nationally organized detailed soil survey in the world, was founded under the direction of M. Whitney. Initial soil classification ideas were heavily based in geology, but over time Russian ideas of soil genesis and classification moved into the American soil science community, mainly due to the influence of C.F. Marbut. Early American efforts in scientific study of soil erosion and soil fertility were also initiated in the 1910s and university programs to educate soil scientists started. Soil erosion studies took on high priority in the 1930s as the USA was impacted by the Dust Bowl. Soil Taxonomy, one of the most widely utilized soil classification systems in the world, was developed from the 1950s through the 1970s under the guidance of G.D. Smith and with administrative support from C.E. Kellogg. American soil scientists, such as H. Jenny, R.W. Simonson, D.L. Johnson, and D. Watson-Stegner, developed influential models of soil genesis during the 20th Century, and the use of soil information expanded beyond agriculture to include issues such as land-use planning, soil geomorphology, and interactions between soils and human health.

Landslide early warning system prototype with GIS analysis indicates by soil movement and rainfall

NASA Astrophysics Data System (ADS)

Artha, Y.; Julian, E. S.

2018-01-01

The aim of this paper is developing and testing of landslide early warning system. The early warning system uses accelerometersas ground movement and tilt-sensing device and a water flow sensor. A microcentroller is used to process the input signal and activate the alarm. An LCD is used to display the acceleration in x,y and z axis. When the soil moved or shifted and rainfall reached 100 mm/day, the alarm rang and signal were sentto the monitoring center via a telemetry system.Data logging information and GIS spatial data can be monitored remotely as tables and graphics as well as in the form of geographical map with the help of web-GIS interface. The system were tested at Kampung Gerendong, Desa Putat Nutug, Kecamatan Ciseeng, Kabupaten Bogor. This area has 3.15 cumulative score, which mean vulnerable to landslide. The results show that the early warning system worked as planned.

Understanding Arsenic Dynamics in Agronomic Systems to ...

EPA Pesticide Factsheets

This review is on arsenic in agronomic systems, and covers processes that influence the entry of arsenic into the human food supply. The scope is from sources of arsenic (natural and anthropogenic) in soils, biogeochemical and rhizosphere processes that control arsenic speciation and availability, through to mechanisms of uptake by crop plants and potential mitigation strategies. This review makes a case for taking steps to prevent or limit crop uptake of arsenic, wherever possible, and to work toward a long-term solution to the presence of arsenic in agronomic systems. The past two decades have seen important advances in our understanding of how biogeochemical and physiological processes influence human exposure to soil arsenic, and thus must now prompt an informed reconsideration and unification of regulations to protect the quality of agricultural and residential soils. Consumption of staple foods such as rice, beverages such as apple juice, or vegetables grown in historically arsenic-contaminated soils is now recognized as a tangible route of arsenic exposure that, in many cases, is more significant than exposure from drinking water. Understanding the sources of arsenic to crop plants and the factors that influence them is key to reducing exposure now and preventing exposure in future. In addition to the abundant natural sources of arsenic, there are a large number of industrial and agricultural sources of arsenic to the soil; from mining wastes, coal fly

Soil erosion modeled with USLE, GIS, and remote sensing: a case study of Ikkour watershed in Middle Atlas (Morocco)

NASA Astrophysics Data System (ADS)

El Jazouli, Aafaf; Barakat, Ahmed; Ghafiri, Abdessamad; El Moutaki, Saida; Ettaqy, Abderrahim; Khellouk, Rida

2017-12-01

The Ikkour watershed located in the Middle Atlas Mountain (Morocco) has been a subject of serious soil erosion problems. This study aimed to assess the soil erosion susceptibility in this mountainous watershed using Universal Soil Loss Equation (USLE) and spectral indices integrated with Geographic Information System (GIS) environment. The USLE model required the integration of thematic factors' maps which are rainfall aggressiveness, length and steepness of the slope, vegetation cover, soil erodibility, and erosion control practices. These factors were calculated using remote sensing data and GIS. The USLE-based assessment showed that the estimated total annual potential soil loss was about 70.66 ton ha-1 year-1. This soil loss is favored by the steep slopes and degraded vegetation cover. The spectral index method, offering a qualitative evaluation of water erosion, showed different degrees of soil degradation in the study watershed according to FI, BI, CI, and NDVI. The results of this study displayed an agreement between the USLE model and spectral index approach, and indicated that the predicted soil erosion rate can be due to the most rugged land topography and an increase in agricultural areas. Indeed, these results can further assist the decision makers in implementation of suitable conservation program to reduce soil erosion.

The informativeness of coefficients a and b of the soil line for the analysis of remote sensing materials

NASA Astrophysics Data System (ADS)

Rukhovich, D. I.; Rukhovich, A. D.; Rukhovich, D. D.; Simakova, M. S.; Kulyanitsa, A. L.; Bryzzhev, A. V.; Koroleva, P. V.

2016-08-01

The coefficients of the soil line are often taken into account in calculations of vegetation indices. These coefficients are usually calculated for the entire satellite image, or are taken as constants without any calculations. In both cases, the informativeness of these coefficients is low and insufficient for the needs of soil mapping. In our study, we calculated soil line coefficients at 8000 lattice points for the territory of Plavsk, Arsen'evsk, and Chern districts of Tula oblast on the basis of 34 Landsat 5, 7, and 8 images obtained in 1985-2014. In order to distinguish between the soil line calculated for a given image and the soil line calculated for lattice points on the basis of dozens of multitemporal images, we suggest that the latter can be referred to as the temporal soil line. The temporal soil line is described by a classical equation: NIR = RED a + b, where a is its slope relative to the horizontal axis (RED), and b is the Y-axis (NIR) intercept. Both coefficients were used to create soil maps. The verification of the maps was performed with the use of data on 1985 soil pits. The informativeness of these coefficients appeared to be sufficient for delineation of eight groups of soils of different taxonomic levels: soddy moderately podzolic soils, soddy slightly podzolic soils, soddy-podzolic soils, light gray forest soils, gray forest soils, dark gray forest soils, podzolized chernozems, and leached chernozems. The b coefficient proved to be more informative, as it allowed us to create the soil map precisely on its basis. In order to create the soil map on the basis of the a coefficient, we had to apply some threshold values of the b coefficient. The bare soil on each of Landsat scenes was separated with the help of the mask of agricultural fields and the notion of the spectral neighborhood of soil line (SNSL).

Enhanced Soil Moisture Initialization Using Blended Soil Moisture Product and Regional Optimization of LSM-RTM Coupled Land Data Assimilation System.

NASA Astrophysics Data System (ADS)

Nair, A. S.; Indu, J.

2017-12-01

Prediction of soil moisture dynamics is high priority research challenge because of the complex land-atmosphere interaction processes. Soil moisture (SM) plays a decisive role in governing water and energy balance of the terrestrial system. An accurate SM estimate is imperative for hydrological and weather prediction models. Though SM estimates are available from microwave remote sensing and land surface model (LSM) simulations, it is affected by uncertainties from several sources during estimation. Past studies have generally focused on land data assimilation (DA) for improving LSM predictions by assimilating soil moisture from single satellite sensor. This approach is limited by the large time gap between two consequent soil moisture observations due to satellite repeat cycle of more than three days at the equator. To overcome this, in the present study, we have performed DA using ensemble products from the soil moisture operational product system (SMOPS) blended soil moisture retrievals from different satellite sensors into Noah LSM. Before the assimilation period, the Noah LSM is initialized by cycling through seven multiple loops from 2008 to 2010 forcing with Global data assimilation system (GDAS) data over the Indian subcontinent. We assimilated SMOPS into Noah LSM for a period of two years from 2010 to 2011 using Ensemble Kalman Filter within NASA's land information system (LIS) framework. Results show that DA has improved Noah LSM prediction with a high correlation of 0.96 and low root mean square difference of 0.0303 m3/m3 (figure 1a). Further, this study has also investigated the notion of assimilating microwave brightness temperature (Tb) as a proxy for SM estimates owing to the close proximity of Tb and SM. Preliminary sensitivity analysis show a strong need for regional parameterization of radiative transfer models (RTMs) to improve Tb simulation. Towards this goal, we have optimized the forward RTM using swarm optimization technique for direct Tb assimilation. The results indicate an improvement in Tb simulations based on the multi polarization difference index approach with a correlation of 0.81 (figure 1b (e)) and bias of < 5 K with respect to the SMOS Tb.

Preliminary Evaluation of TM for Soils Information

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Henderson, K. E.; Houston, A. G.; Pitts, D. E.

1984-01-01

Thematic mapper data acquired over Mississippi County, Arkansas, were examined for utility in separating soil associations within generally level alluvium deposited by the Mississippi River. The 0.76 to 0.90 micron (Band 4) and the 1.55 to 1.75 micron (Band 5) were found to separate the different soil associations fairly well when compared to the USDA-SCS general soil map. The thermal channel also appeared to provide information at this level. A detailed soil survey was available at the field level along with ground observations of crop type, plant height, percent cover and growth stage. Soils within the fields ranged from uniform to soils that occur as patches of sand that stand out strongly against the intermingled areas of dark soil. Examination of the digital values of individual TM bands at the field level indicates that the influence of the soil is greater in TM than it was in MSS bands. The TM appears to provide greater detail of within field variability caused by soils than MSS and thus should provide improved information relating to crop and soil properties. However, this soil influence may cause crop identification classification procedures to have to account for the soil in their algorithms.

Complex Adaptive Systems, soil degradation and land sensitivity to desertification: A multivariate assessment of Italian agro-forest landscape.

PubMed

Salvati, Luca; Mavrakis, Anastasios; Colantoni, Andrea; Mancino, Giuseppe; Ferrara, Agostino

2015-07-15

Degradation of soils and sensitivity of land to desertification are intensified in last decades in the Mediterranean region producing heterogeneous spatial patterns determined by the interplay of factors such as climate, land-use changes, and human pressure. The present study hypothesizes that rising levels of soil degradation and land sensitivity to desertification are reflected into increasingly complex (and non-linear) relationships between environmental and socioeconomic variables. To verify this hypothesis, the Complex Adaptive Systems (CAS) framework was used to explore the spatiotemporal dynamics of eleven indicators derived from a standard assessment of soil degradation and land sensitivity to desertification in Italy. Indicators were made available on a detailed spatial scale (773 agricultural districts) for various years (1960, 1990, 2000 and 2010) and analyzed through a multi-dimensional exploratory data analysis. Our results indicate that the number of significant pair-wise correlations observed between indicators increased with the level of soil and land degradation, although with marked differences between northern and southern Italy. 'Fast' and 'slow' factors underlying soil and land degradation, and 'rapidly-evolving' or 'locked' agricultural districts were identified according to the rapidity of change estimated for each of the indicators studied. In southern Italy, 'rapidly-evolving' districts show a high level of soil degradation and land sensitivity to desertification during the whole period of investigation. On the contrary, those districts in northern Italy are those experiencing a moderate soil degradation and land sensitivity to desertification with the highest increase in the level of sensitivity over time. The study framework contributes to the assessment of complex local systems' dynamics in affluent but divided countries. Results may inform thematic strategies for the mitigation of land and soil degradation in the framework of action plans to combat desertification. Copyright © 2015 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

The Area IV Soil Conservation Districts Cooperative Research Farm: Thirty years of collaborative research to improve cropping system sustainability in the Northern Plains

USDA-ARS?s Scientific Manuscript database

Findings and interpretations generated from long-term cropping system studies serve to inform the status and trajectory of ecosystem services, while concurrently providing opportunities for further inquiry related to basic/fundamental research. Recent calls for increased investment in long-term cro...

The Pilot Study of Integrating Spatial Educational Experiences (Isee) in an Undergraduate Crop Production Course

ERIC Educational Resources Information Center

Mitzman, Stephanie; Snyder, Lori Unruh; Schulze, Darrell G.; Owens, Phillip R.; Bracke, Marianne Stowell

2011-01-01

Recent National Research Council reports make compelling arguments for the need to incorporate spatial abilities and use spatial technologies throughout our educational system. We conducted a pilot study to determine the pedagogical effectiveness of teaching with geographic information systems (GIS) by using a web-based GIS tool of Indiana soils.…

The natural resources inventory system ASVT project

NASA Technical Reports Server (NTRS)

Joyce, A. T.

1979-01-01

The hardware/software and the associated procedures for a natural resource inventory and information system based on the use of LANDSAT-acquired multispectral scanner digital data is described. The system is designed to derive land cover/vegetation information from LANDSAT data and geographically reference this information for the production of various types of maps and for the compilation of acreage by land cover/vegetation category. The system also provides for data base building so that the LANDSAT-derived information can be related to information digitized from other sources (e.g., soils maps) in a geographic context in order to address specific applications. These applications include agricultural crop production estimation, erosion hazard-reforestation need assessment, whitetail deer habitat assessment, and site selection. The system is tested in demonstration areas located in the state of Mississippi, and the results of these application demonstrations are presented. A cost-efficiency comparison of producing land cover/vegetation maps and statistics with this system versus the use of small-scale aerial photography is made.

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Linear Regression between CIE-Lab Color Parameters and Organic Matter in Soils of Tea Plantations

NASA Astrophysics Data System (ADS)

Chen, Yonggen; Zhang, Min; Fan, Dongmei; Fan, Kai; Wang, Xiaochang

2018-02-01

To quantify the relationship between the soil organic matter and color parameters using the CIE-Lab system, 62 soil samples (0-10 cm, Ferralic Acrisols) from tea plantations were collected from southern China. After air-drying and sieving, numerical color information and reflectance spectra of soil samples were measured under laboratory conditions using an UltraScan VIS (HunterLab) spectrophotometer equipped with CIE-Lab color models. We found that soil total organic carbon (TOC) and nitrogen (TN) contents were negatively correlated with the L* value (lightness) ( r = -0.84 and -0.80, respectively), a* value (correlation coefficient r = -0.51 and -0.46, respectively) and b* value ( r = -0.76 and -0.70, respectively). There were also linear regressions between TOC and TN contents with the L* value and b* value. Results showed that color parameters from a spectrophotometer equipped with CIE-Lab color models can predict TOC contents well for soils in tea plantations. The linear regression model between color values and soil organic carbon contents showed it can be used as a rapid, cost-effective method to evaluate content of soil organic matter in Chinese tea plantations.

[Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

PubMed

Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

2012-02-01

In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

Proceedings, 18th Central Hardwood Forest Conference

Treesearch

Gary W. Miller; Thomas M. Schuler; Kurt W. Gottschalk; John R. Brooks; Shawn T. Grushecky; Ben D. Spong; James S., eds. Rentch

2013-01-01

Includes 44 papers and 41 abstracts pertaining to research conducted on biofuels and bioenergy, forest biometrics, forest ecology and physiology, forest economics, forest health including invasive species, forest soils and hydrology, geographic information systems, harvesting and utilization, silviculture, and wildlife management.

A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

NASA Astrophysics Data System (ADS)

Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

2017-12-01

Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.

Biodegradation of hexachlorocyclohexane (HCH) by microorganisms.

PubMed

Phillips, Theresa M; Seech, Alan G; Lee, Hung; Trevors, Jack T

2005-08-01

The organochlorine pesticide Lindane is the gamma-isomer of hexachlorocyclohexane (HCH). Technical grade Lindane contains a mixture of HCH isomers which include not only gamma-HCH, but also large amounts of predominantly alpha-, beta- and delta-HCH. The physical properties and persistence of each isomer differ because of the different chlorine atom orientations on each molecule (axial or equatorial). However, all four isomers are considered toxic and recalcitrant worldwide pollutants. Biodegradation of HCH has been studied in soil, slurry and culture media but very little information exists on in situ bioremediation of the different isomers including Lindane itself, at full scale. Several soil microorganisms capable of degrading, and utilizing HCH as a carbon source, have been reported. In selected bacterial strains, the genes encoding the enzymes involved in the initial degradation of Lindane have been cloned, sequenced, expressed and the gene products characterized. HCH is biodegradable under both oxic and anoxic conditions, although mineralization is generally observed only in oxic systems. As is found for most organic compounds, HCH degradation in soil occurs at moderate temperatures and at near neutral pH. HCH biodegradation in soil has been reported at both low and high (saturated) moisture contents. Soil texture and organic matter appear to influence degradation presumably by sorption mechanisms and impact on moisture retention, bacterial growth and pH. Most studies report on the biodegradation of relatively low (< 500 mg/kg) concentrations of HCH in soil. Information on the effects of inorganic nutrients, organic carbon sources or other soil amendments is scattered and inconclusive. More in-depth assessments of amendment effects and evaluation of bioremediation protocols, on a large scale, using soil with high HCH concentrations, are needed.

The effects of rainfall partitioning and evapotranspiration on the temporal and spatial variation of soil water content in a Mediterranean agroforestry system

NASA Astrophysics Data System (ADS)

Biel, C.; Molina, A.; Aranda, X.; Llorens, P.; Savé, R.

2012-04-01

Tree plantation for wood production has been proposed to mitigate CO2-related climate change. Although these agroforestry systems can contribute to maintain the agriculture in some areas placed between rainfed crops and secondary forests, water scarcity in Mediterranean climate could restrict its growth, and their presence will affect the water balance. Tree plantations management (species, plant density, irrigation, etc), hence, can be used to affect the water balance, resulting in water availability improvement and buffering of the water cycle. Soil water content and meteorological data are widely used in agroforestry systems as indicators of vegetation water use, and consequently to define water management. However, the available information of ecohydrological processes in this kind of ecosystem is scarce. The present work studies how the temporal and spatial variation of soil water content is affected by transpiration and interception loss fluxes in a Mediterranean rainfed plantation of cherry tree (Prunus avium) located in Caldes de Montbui (Northeast of Spain). From May till December 2011, rainfall partitioning, canopy transpiration, soil water content and meteorological parameters were continuously recorded. Rainfall partitioning was measured in 6 trees, with 6 automatic rain recorders for throughfall and 1 automatic rain recorder for stemflow per tree. Transpiration was monitored in 12 nearby trees by means of heat pulse sap flow sensors. Soil water content was also measured at three different depths under selected trees and at two depths between rows without tree cover influence. This work presents the relationships between rainfall partitioning, transpiration and soil water content evolution under the tree canopy. The effect of tree cover on the soil water content dynamics is also analyzed.

Participatory innovation process for testing new practices for soil fertility management in Chókwè Irrigation Scheme (Mozambique)

NASA Astrophysics Data System (ADS)

Sánchez Reparaz, Maite; de Vente, Joris; Famba, Sebastiao; Rougier, Jean-Emmanuel; Ángel Sánchez-Monedero, Miguel; Barberá, Gonzalo G.

2015-04-01

Integrated water and nutrient management are key factors to increase productivity and to reduce the yield gap in irrigated systems in Sub-Saharan Africa. These two elements are affected by an ensemble of abiotic, biotic, management and socio-economic factors that need to be taken into account to reduce the yield gap, as well as farmers' perceptions and knowledge. In the framework of the project European Union and African Union cooperative research to increase Food production in irrigated farming systems in Africa (EAU4Food project) we are carrying out a participatory innovation process in Chókwè irrigation scheme (Mozambique) based on stakeholders engagement, to test new practices for soil fertility management that can increase yields reducing costs. Through a method combining interviews with three farmers' associations and other relevant stakeholders and soil sampling from the interviewed farmers' plots with the organization of Communities of Practices, we tried to capture how soil fertility is managed by farmers, the constraints they find as well as their perceptions about soil resources. This information was the basis to design and conduct a participatory innovation process where compost made with rice straw and manure is being tested by a farmers' association. Most important limitations of the method are also evaluated. Our results show that socio-economic characteristics of farmers condition how they manage soil fertility and their perceptions. The difficulties they face to adopt new practices for soil fertility management, mainly related to economic resources limitations, labour availability, knowledge time or farm structure, require a systemic understanding that takes into account abiotic, biotic, management and socio-economic factors and their implication as active stakeholders in all phases of the innovation process.

Soil Respiration in Eddy Covariance Footprints: A Critical Look at Researcher Needs

NASA Astrophysics Data System (ADS)

Gabriel, Carrie-Ellen; Nickerson, Nick; Creelman, Chance

2017-04-01

Eddy covariance (EC) systems have been widely used across the globe for more than 20 years, offering researchers invaluable measurements of parameters including Net Ecosystem Exchange and ecosystem respiration. However, recent research suggests that EC assumptions and technical obstacles may cause biased gas exchange estimates. Measurements of soil respiration (RS) at the ground level may help alleviate these biases; for example, by allowing researchers to reconcile nocturnal EC flux data with soil respiration or by providing a means to inform gap-filling models. RS measurements have been used sparingly alongside EC towers because of the large cost required to scale chamber systems to the EC footprint, as well as data integration and processing burdens. Here we present how the Forced Diffusion (FD) method is ideal for the measurement of RS at EC sites. The FD method allows for inexpensive and autonomous measurements, providing a scalable approach to matching the EC footprint compared to other RS systems. Here, we briefly present the methodology and results from a pilot study at the Howland Forest AmeriFlux site (Maine), carried out during the summer and fall of 2016, measuring soil respiration using the FD chamber technique. The emphasis of the remainder of the research is on gathering, interpreting and actualizing feedback from soil scientists and eddy covariance researchers and technicians on aspects of the FD methodology, deployment style, integration with existing infrastructure and data quality. Our goal is to eventually provide a framework for "ideal soil respiration measurements" that can be used by researchers, engineers and companies to develop functional and reliable soil respiration data sets that are easily coupled with data measured by EC users, and larger EC networks such as AmeriFlux and EuroFlux.

A Brief History of Soil Mapping and Classification in the USA

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Hartemink, Alfred E.

2014-05-01

Soil maps show the distribution of soils across an area but also depict soil science theory and ideas on soil formation and classification at the time the maps were created. The national soil mapping program in the USA was established in 1899. The first nation-wide soil map was published by M. Whitney in 1909 and showed soil provinces that were largely based on geology. In 1912, G.N. Coffey published the first country-wide map based on soil properties. The map showed 5 broad soil units that used parent material, color and drainage as diagnostic criteria. The 1913 national map was produced by C.F. Marbut, H.H. Bennett, J.E. Lapham, and M.H. Lapham and showed broad physiographic units that were further subdivided into soil series, soil classes and soil types. In 1935, Marbut drafted a series of maps based on soil properties, but these maps were replaced as official U.S. soil maps in 1938 with the work of M. Baldwin, C.E. Kellogg, and J. Thorp. A series of soil maps similar to modern USA maps appeared in the 1960s with the 7th Approximation followed by revisions with the 1975 and 1999 editions of Soil Taxonomy. This review has shown that soil maps in the United States produced since the early 1900s moved initially from a geologic-based concept to a pedologic concept of soils. Later changes were from property-based systems to process-based, and then back to property-based. The information in this presentation is based on Brevik and Hartemink (2013). Brevik, E.C., and A.E. Hartemink. 2013. Soil Maps of the United States of America. Soil Science Society of America Journal 77:1117-1132. doi:10.2136/sssaj2012.0390.

Agroecology of corn production in Tlaxcala, Mexico

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

Altieri, M.A.; Trujillo, J.

1987-06-01

The primary components of Tlaxcalan corn agriculture are described, including cropping patterns employed, resource management strategies, and interactions of human and biological factors. Tlaxcalan farmers grow corn in an array of polyculture and agroforestry designs that result in a series of ecological processes important for insect pest and soil fertility management. Measurements derived from a few selected fields show that trees integrated into cropping systems modify the aerial and soil environment of associated understory corn plants, influencing their growth and yields. With decreasing distance from trees, surface concentrations of most soil nutrients increase. Certain tree species affect corn yields moremore » than others. Arthropod abundance also varies depending on their degree of association with one or more of the vegetational components of the system. Densities of predators and the corn pest Macrodactylus sp. depend greatly on the presence and phenology of adjacent alfalfa strips. Although the data were derived from nonreplicated fields, they nevertheless point out some important trends, information that can be used to design new crop association that will achieve sustained soil fertility and low pest potentials.« less

The propagation of a soil H218O labeling through the atmosphere-plant-soil system under drought using H218O and C18OO as two independent proxies

NASA Astrophysics Data System (ADS)

Barthel, Matthias; Sturm, Patrick; Hammerle, Albin; Siegwolf, Rolf; Gentsch, Lydia; Buchmann, Nina; Knohl, Alexander

2013-04-01

Above- and belowground processes in plants are tightly coupled via carbon and water flows through the atmosphere-plant-soil system. While recent studies elucidated the influence of drought on the carbon flow through plant and soil using 13C, much less is known about the propagation of 18O. Therefore, this study aimed to examine the timing and intensity of 18O enrichment in soil and shoot CO2 and H2O vapor fluxes of European beech saplings (Fagus sylvatica L.) after applying 18O-labeled water to the soil. A custom-made chamber system, separating shoot from soil compartments, allowed independent measurements of shoot and soil related processes in a controlled climate chamber environment. Gas-exchange of oxygen stable isotopes in CO2 and H2O-vapor served as the main tool for investigation and was monitored in real-time using laser spectroscopy. This is the first study measuring concurrently and continuously the enrichment of 18O in CO2 and H2O in shoot- and soil gas-exchange after applying 18O-labeled water to the soil. Photosynthesis (A) and stomatal conductance (gs) of drought-stressed plants showed an immediate coinciding small increase to the H218O irrigation event after only ~30 min. This rapid information transfer, however, was not accompanied by the arrival of 18O labeled water molecules within the shoot. The actual label induced 18O enrichment in transpired water and CO2 occurred not until ~4h after labeling. Further, the timing of the enrichment of 18O in the transpirational flux was similar in both treatments, thus pointing to similar transport rates. However, drought reduced the 18O exchange rate between H2O and CO2at the shoot level, likely caused by a smaller leaf CO2retroflux. Moreover, 18O exchange between H2O and CO2 occurred also in the soil. However, the there was no difference observed between the treatments.

Investigating soil moisture feedbacks on precipitation with tests of Granger causality

NASA Astrophysics Data System (ADS)

Salvucci, Guido D.; Saleem, Jennifer A.; Kaufmann, Robert

Granger causality (GC) is used in the econometrics literature to identify the presence of one- and two-way coupling between terms in noisy multivariate dynamical systems. Here we test for the presence of GC to identify a soil moisture ( S) feedback on precipitation ( P) using data from Illinois. In this framework S is said to Granger cause P if F(P t|Ω t- Δt )≠F(P t|Ω t- Δt -S t- Δt ) where F denotes the conditional distribution of P, Ω t- Δt represents the set of all knowledge available at time t-Δ t, and Ω t- Δt -S t- Δt represents all knowledge except S. Critical for land-atmosphere interaction research is that Ω t- Δt includes all past information on P as well as S. Therefore that part of the relation between past soil moisture and current precipitation which results from precipitation autocorrelation and soil water balance will be accounted for and not attributed to causality. Tests for GC usually specify all relevant variables in a coupled vector autoregressive (VAR) model and then calculate the significance level of decreased predictability as various coupling coefficients are omitted. But because the data (daily precipitation and soil moisture) are distinctly non-Gaussian, we avoid using a VAR and instead express the daily precipitation events as a Markov model. We then test whether the probability of storm occurrence, conditioned on past information on precipitation, changes with information on soil moisture. Past information on precipitation is expressed both as the occurrence of previous day precipitation (to account for storm-scale persistence) and as a simple soil moisture-like precipitation-wetness index derived solely from precipitation (to account for seasonal-scale persistence). In this way only those fluctuations in moisture not attributable to past fluctuations in precipitation (e.g., those due to temperature) can influence the outcome of the test. The null hypothesis (no moisture influence) is evaluated by comparing observed changes in storm probability to Monte-Carlo simulated differences generated with unconditional occurrence probabilities. The null hypothesis is not rejected ( p>0.5) suggesting that contrary to recently published results, insufficient evidence exists to support an influence of soil moisture on precipitation in Illinois.

Geophysics and Nanosciences: Nano to Micro to Meso to Macro Scale Swelling Soils

NASA Astrophysics Data System (ADS)

Cushman, J.

2003-04-01

We use statistical mechanical simulations of nanoporous materials to motivate a choice of independent constitutive variables for a multiscale mixture theory of swelling soils. A video will illustrate the structural behavior of fluids in nanopores when they are adsorbed from a bulk phase vapor to form capillaries on the nanoscale. These simulations suggest that when a swelling soil is very dry, the full strain tensor for the liquid phase should be included in the list of independent variables in any mixture theory. We use this information to develop a three-scale (micro, meso, macro) mixture theory for swelling soils. For a simplified case, we present the underlying multiscale field equations and constitutive theory, solve the resultant well posed system numerically, and present some graphical results for a drying and shrinking body.

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

NASA Technical Reports Server (NTRS)

Koster, Randal

2010-01-01

This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.

Erratum to "Impact of uncertainty in soil, climatic, and chemical information in a pesticide leaching assessment".

PubMed

Loague, Keith; Green, Richard E; Giambelluca, Thomas W; Liang, Tony C; Yost, Russell S

2016-11-01

A simple mobility index, when combined with a geographic information system, can be used to generate rating maps which indicate qualitatively the potential for various organic chemicals to leach to groundwater. In this paper we investigate the magnitude of uncertainty associated with pesticide mobility estimates as a result of data uncertainties. Our example is for the Pearl Harbor Basin, Oahu, Hawaii. The two pesticides included in our analysis are atrazine (2-chloro-4-ethylamino-6-isopropylamino-s-triazine) and diuron [3-(3,4-dichlorophenyl)-1,1-dimethylarea]. The mobility index used here is known as the Attenuation Factor (AF); it requires soil, hydrogeologic, climatic, and chemical information as input data. We employ first-order uncertainty analysis to characterize the uncertainty in estimates of AF resulting from uncertainties in the various input data. Soils in the Pearl Harbor Basin are delineated at the order taxonomic category for this study. Our results show that there can be a significant amount of uncertainty in estimates of pesticide mobility for the Pearl Harbor Basin. This information needs to be considered if future decisions concerning chemical regulation are to be based on estimates of pesticide mobility determined from simple indices. Copyright © 2016. Published by Elsevier B.V.

Application of remote sensing and geographical information system for generation of runoff curve number

NASA Astrophysics Data System (ADS)

Meshram, S. Gajbhiye; Sharma, S. K.; Tignath, S.

2017-07-01

Watershed is an ideal unit for planning and management of land and water resources (Gajbhiye et al., IEEE international conference on advances in technology and engineering (ICATE), Bombay, vol 1, issue 9, pp 23-25, 2013a; Gajbhiye et al., Appl Water Sci 4(1):51-61, 2014a; Gajbhiye et al., J Geol Soc India (SCI-IF 0.596) 84(2):192-196, 2014b). This study aims to generate the curve number, using remote sensing and geographical information system (GIS) and the effect of slope on curve number values. The study was carried out in Kanhaiya Nala watershed located in Satna district of Madhya Pradesh. Soil map, Land Use/Land cover and slope map were generated in GIS Environment. The CN parameter values corresponding to various soil, land cover, and land management conditions were selected from Natural Resource Conservation Service (NRCS) standard table. Curve number (CN) is an index developed by the NRCS, to represent the potential for storm water runoff within a drainage area. The CN for a drainage basin is estimated using a combination of land use, soil, and antecedent soil moisture condition (AMC). In present study effect of slope on CN values were determined. The result showed that the CN unadjusted value are higher in comparison to CN adjusted with slope. Remote sensing and GIS is very reliable technique for the preparation of most of the input data required by the SCS curve number model.

Lignin in the Organic Matter of the Soils of the Russian Plain as Biomarker of Palaeoenvironment

NASA Astrophysics Data System (ADS)

Kovalev, I. V.; Kovaleva, N. O.

2018-01-01

It has been shown by the methods of biochemistry, nuclear magnetic resonance, and isotope geochemistry that the proportions of lignin phenols may be used as molecular traces of paleovegetation due to their biochemical and physiological specificity and high resistance to decomposition. Lignin structures have been detected in soils and in iron-manganese concretions. The comparison of the 13C NMR spectra of native lignin preparations isolated from different woody and herbaceous species with those of soil humic acids makes it possible to identify many characteristic shifts of lignin nature in humic acids at 56, 102, 115, 119, 131, 147, 151-152, 160, and 166 ppm. The information role of biomarker has been tested at the reconstruction of paleovegetation in the uplands of the Russian Plain. The representativeness of information has been increased using the isotope analysis (δ13C) and the radiocarbon dating; a new parameter—the composition of lignin phenols—has been introduced to the existing system of biomarkers.

Soil process-oriented modelling of within-field variability based on high-resolution 3D soil type distribution maps.

NASA Astrophysics Data System (ADS)

Bönecke, Eric; Lück, Erika; Gründling, Ralf; Rühlmann, Jörg; Franko, Uwe

2016-04-01

Today, the knowledge of within-field variability is essential for numerous purposes, including practical issues, such as precision and sustainable soil management. Therefore, process-oriented soil models have been applied for a considerable time to answer question of spatial soil nutrient and water dynamics, although, they can only be as consistent as their variation and resolution of soil input data. Traditional approaches, describe distribution of soil types, soil texture or other soil properties for greater soil units through generalised point information, e.g. from classical soil survey maps. Those simplifications are known to be afflicted with large uncertainties. Varying soil, crop or yield conditions are detected even within such homogenised soil units. However, recent advances of non-invasive soil survey and on-the-go monitoring techniques, made it possible to obtain vertical and horizontal dense information (3D) about various soil properties, particularly soil texture distribution which serves as an essential soil key variable affecting various other soil properties. Thus, in this study we based our simulations on detailed 3D soil type distribution (STD) maps (4x4 m) to adjacently built-up sufficient informative soil profiles including various soil physical and chemical properties. Our estimates of spatial STD are based on high-resolution lateral and vertical changes of electrical resistivity (ER), detected by a relatively new multi-sensor on-the-go ER monitoring device. We performed an algorithm including fuzzy-c-mean (FCM) logic and traditional soil classification to estimate STD from those inverted and layer-wise available ER data. STD is then used as key input parameter for our carbon, nitrogen and water transport model. We identified Pedological horizon depths and inferred hydrological soil variables (field capacity, permanent wilting point) from pedotransferfunctions (PTF) for each horizon. Furthermore, the spatial distribution of soil organic carbon (SOC), as essential input variable, was predicted by measured soil samples and associated to STD of the upper 30 cm. The comprehensive and high-resolution (4x4 m) soil profile information (up to 2 m soil depth) were then used to initialise a soil process model (Carbon and Nitrogen Dynamics - CANDY) for soil functional modelling (daily steps of matter fluxes, soil temperature and water balances). Our study was conducted on a practical field (~32,000 m²) of an agricultural farm in Central Germany with Chernozem soils under arid conditions (average rainfall < 550 mm). This soil region is known to have differences in soil structure mainly occurring within the subsoil, since topsoil conditions are described as homogenous. The modelled soil functions considered local climate information and practical farming activities. Results show, as expected, distinguished functional variability, both on spatial and temporal resolution for subsoil evident structures, e.g. visible differences for available water capacity within 0-100 cm but homogenous conditions for the topsoil.

Satellite Gravimetry Applied to Drought Monitoring

NASA Technical Reports Server (NTRS)

Rodell, Matthew

2010-01-01

Near-surface wetness conditions change rapidly with the weather, which limits their usefulness as drought indicators. Deeper stores of water, including root-zone soil wetness and groundwater, portend longer-term weather trends and climate variations, thus they are well suited for quantifying droughts. However, the existing in situ networks for monitoring these variables suffer from significant discontinuities (short records and spatial undersampling), as well as the inherent human and mechanical errors associated with the soil moisture and groundwater observation. Remote sensing is a promising alternative, but standard remote sensors, which measure various wavelengths of light emitted or reflected from Earth's surface and atmosphere, can only directly detect wetness conditions within the first few centimeters of the land s surface. Such sensors include the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) C-band passive microwave measurement system on the National Aeronautic and Space Administration's (NASA) Aqua satellite, and the combined active and passive L-band microwave system currently under development for NASA's planned Soil Moisture Active Passive (SMAP) satellite mission. These instruments are sensitive to water as deep as the top 2 cm and 5 cm of the soil column, respectively, with the specific depth depending on vegetation cover. Thermal infrared (TIR) imaging has been used to infer water stored in the full root zone, with limitations: auxiliary information including soil grain size is required, the TIR temperature versus soil water content curve becomes flat as wetness increases, and dense vegetation and cloud cover impede measurement. Numerical models of land surface hydrology are another potential solution, but the quality of output from such models is limited by errors in the input data and tradeoffs between model realism and computational efficiency. This chapter is divided into eight sections, the next of which describes the theory behind satellite gravimetry. Following that is a summary of the GRACE mission and how hydrological information is gleaned from its gravity products. The fourth section provides examples of hydrological science enabled by GRACE. The fifth and sixth sections list the challenging aspects of GRACE derived hydrology data and how they are being overcome, including the use of data assimilation. The seventh section describes recent progress in applying GRACE for drought monitoring, including the development of new soil moisture and drought indicator products, and that is followed by a discussion of future prospects in satellite gravimetry based drought monitoring.

Following The Money: Characterizing the Dynamics of Microbial Ecosystems and Labile Organic Matter in Grassland Soils

NASA Astrophysics Data System (ADS)

Herbert, B. E.; McNeal, K. S.

2006-12-01

The dynamics of soil microbial ecosystems and labile fractions of soil organic matter in grasslands have important implications for the response of these critical ecosystems to perturbations. Organic, inorganic and genetic biomarkers in the solid (e.g. lipids, microbial DNA), liquid (e.g. porewater ions) or gaseous phases (e.g. carbon dioxide) have been used to characterize carbon cycling and soil microbial ecology. These proxies are generally limited in the amount of temporal information that they can provide (i.e., solid-phase proxies) or the amount of specific information they can provide about carbon sources or microbial community processes (e.g. inorganic gases). It is the aim of this research to validate the use of soil volatile organic carbon emissions (VOCs) as useful indicators of subsurface microbial community shifts and processes as a function of ecosystem perturbations. We present results of method validation using laboratory microcosm, where VOC metabolites as characterized by gas chromatography and mass spectrometry (GC-MS), were related to other proxies including carbon dioxide (CO2) via infra-red technology, and microbial community shifts as measured by Biolog© and fatty acid methyl ester (FAME) techniques. Experiments with soil collected from grasslands along the coastal margin region in southern Texas were preformed where environmental factors such as soil water content, soil type, and charcoal content are manipulated. Results indicate that over fifty identifiable VOC metabolites are produced from the soils, where many (~15) can be direct indicators of microbial ecology. Principle component analysis (PCA) evidences these trends through similar cluster patterns for the VOC results, the Biolog© results, and FAME. Regression analysis further shows that VOCs are significant (p < 0.05) indicators of microbial stress. Our results are encouraging that characterizing VOCs production in grassland soils are easy to measure, relatively inexpensive method, and useful proxies of subsurface microbial ecosystems and the dynamics of labile carbon in these systems.

The Phytophthora species assemblage and diversity in riparian alder ecosystems of western Oregon, USA.

PubMed

Sims, Laura Lee; Sutton, Wendy; Reeser, Paul; Hansen, Everett M

2015-01-01

Phytophthora species were systematically sampled, isolated, identified and compared for presence in streams, soil and roots of alder (Alnus species) dominated riparian ecosystems in western Oregon. We describe the species assemblage and evaluate Phytophthora diversity associated with alder. We recovered 1250 isolates of 20 Phytophthora species. Only three species were recovered from all substrates (streams, soil, alder roots): P. gonapodyides, the informally described "P. taxon Pgchlamydo", and P. siskiyouensis. P. alni ssp. uniformis along with five other species not previously recovered in Oregon forests are included in the assemblage: P.citricola s.l., P. gregata, P. gallica, P. nicotianae and P. parsiana. Phytophthora species diversity was greatest in downstream riparian locations. There was no significant difference in species diversity comparing soil and unwashed roots (the rhizosphere) to stream water. There was a difference between the predominating species from the rhizosphere compared to stream water. The most numerous species was the informally described "P. taxon Oaksoil", which was mainly recovered from, and most predominant in, stream water. The most common species from riparian forest soils and alder root systems was P. gonapodyides. © 2015 by The Mycological Society of America.

Runoff and recharge processes under a strong semi-arid climatic gradient

NASA Astrophysics Data System (ADS)

Ries, F.; Lange, J.; Sauter, M.; Schmidt, S.

2012-04-01

Hydrological processes in semi-arid environments are highly dynamic. In the eastern slopes of the West Bank these dynamics are even intensified due to the predominant karst morphology, the strong climatic gradient (150-700 mm mean annual precipitation) and the small-scale variability of land use, topography and soil cover. The region is characterized by a scarcity in water resources and a high population growth. Therefore detailed information about the temporal and spatial distribution, amount and variability of available water resources is required. Providing this information by the use of hydrological models is challenging, because available data are extremely limited. From 2007 on, the research area of Wadi Auja, northeast of Jerusalem, has been instrumented with a dense monitoring network. Rainfall distribution and climatic parameters as well as the hydrological reaction of the system along the strong semi-arid climatic gradient are measured on the plot (soil moisture), hillslope (runoff generation) and catchment scale (spring discharge, groundwater level, flood runoff). First data from soil moisture plots situated along the climatic gradient are presented. They allow insights into physical properties of the soil layer and its impact on runoff and recharge processes under different climatic conditions. From continuous soil moisture profiles, soil water balances are calculated for singe events and entire seasons. These data will be used to parameterize the distributed hydrological model TRAIN-ZIN, which has been successfully applied in several studies in the Jordan River Basin.

Islands of biogeodiversity in arid lands on a polygons map study: Detecting scale invariance patterns from natural resources maps.

PubMed

Ibáñez, J J; Pérez-Gómez, R; Brevik, Eric C; Cerdà, A

2016-12-15

Many maps (geology, hydrology, soil, vegetation, etc.) are created to inventory natural resources. Each of these resources is mapped using a unique set of criteria, including scales and taxonomies. Past research indicates that comparing results of related maps (e.g., soil and geology maps) may aid in identifying mapping deficiencies. Therefore, this study was undertaken in Almeria Province, Spain to (i) compare the underlying map structures of soil and vegetation maps and (ii) investigate if a vegetation map can provide useful soil information that was not shown on a soil map. Soil and vegetation maps were imported into ArcGIS 10.1 for spatial analysis, and results then exported to Microsoft Excel worksheets for statistical analyses to evaluate fits to linear and power law regression models. Vegetative units were grouped according to the driving forces that determined their presence or absence: (i) climatophilous (ii) lithologic-climate; and (iii) edaphophylous. The rank abundance plots for both the soil and vegetation maps conformed to Willis or Hollow Curves, meaning the underlying structures of both maps were the same. Edaphophylous map units, which represent 58.5% of the vegetation units in the study area, did not show a good correlation with the soil map. Further investigation revealed that 87% of the edaphohygrophilous units were found in ramblas, ephemeral riverbeds that are not typically classified and mapped as soils in modern systems, even though they meet the definition of soil given by the most commonly used and most modern soil taxonomic systems. Furthermore, these edaphophylous map units tend to be islands of biodiversity that are threatened by anthropogenic activity in the region. Therefore, this study revealed areas that need to be revisited and studied pedologically. The vegetation mapped in these areas and the soils that support it are key components of the earth's critical zone that must be studied, understood, and preserved. Copyright © 2016 Elsevier B.V. All rights reserved.

Integrationof Remote Sensing and Geographic information system in Ground Water Quality Assessment and Management

NASA Astrophysics Data System (ADS)

Shakak, N.

2015-04-01

Spatial variations in ground water quality in the Khartoum state, Sudan, have been studied using geographic information system (GIS) and remote sensing technique. Gegraphical informtion system a tool which is used for storing, analyzing and displaying spatial data is also used for investigating ground water quality information. Khartoum landsat mosac image aquired in 2013was used, Arc/Gis software applied to extract the boundary of the study area, the image was classified to create land use/land cover map. The land use map,geological and soil map are used for correlation between land use , geological formations, and soil types to understand the source of natural pollution that can lower the ground water quality. For this study, the global positioning system (GPS), used in the field to identify the borehole location in a three dimentional coordinate (Latitude, longitude, and altitude), water samples were collected from 156 borehole wells, and analyzed for physico-chemical parameters like electrical conductivity, Total dissolved solid,Chloride, Nitrate, Sodium, Magnisium, Calcium,and Flouride, using standard techniques in the laboratory and compared with the standards.The ground water quality maps of the entire study area have been prepared using spatial interpolation technique for all the above parameters.then the created maps used to visualize, analyze, and understand the relationship among the measured points. Mapping was coded for potable zones, non-potable zones in the study area, in terms of water quality sutability for drinking water and sutability for irrigation. In general satellite remote sensing in conjunction with geographical information system (GIS) offers great potential for water resource development and management.

An integrated and open source GIS environmental management system for a protected area in the south of Portugal

NASA Astrophysics Data System (ADS)

Teodoro, A.; Duarte, L.; Sillero, N.; Gonçalves, J. A.; Fonte, J.; Gonçalves-Seco, L.; Pinheiro da Luz, L. M.; dos Santos Beja, N. M. R.

2015-10-01

Herdade da Contenda (HC), located in Moura municipality, Beja district (Alentejo province) in the south of Portugal (southwestern Iberia Peninsula), is a national hunting area with 5270ha. The development of an integrated system that aims to make the management of the natural and cultural heritage resources will be very useful for an effective management of this area. This integrated system should include the physical characterization of the territory, natural conservation, land use and land management themes, as well the cultural heritage resources. This paper presents a new tool for an integrated environmental management system of the HC, which aims to produce maps under a GIS open source environment (QGIS). The application is composed by a single button which opens a window. The window is composed by twelve menus (File, DRASTIC, Forest Fire Risk, Revised Universal Soil Loss Equation (RUSLE), Bioclimatic Index, Cultural Heritage, Fauna and Flora, Ortofoto, Normalizes Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), Land Use Land Cover Cover (LULC) and Help. Several inputs are requires to generate these maps, e.g. DEM, geologic information, soil map, hydraulic conductivity information, LULC map, vulnerability and economic information, NDVI. Six buttons were added to the toolbar which allows to manipulate the information in the map canvas: Zoom in, Zoom out, Pan, Print/Layout and Clear. This integrated and open source GIS environment management system was developed for the HC area, but could be easily adapted to other natural or protected area. Despite the lack of data, the methodology presented fulfills the objectives.

The biogeochemistry of bioenergy landscapes: carbon, nitrogen, and water considerations.

PubMed

Robertson, G Philip; Hamilton, Stephen K; Del Grosso, Stephen J; Parton, William J

2011-06-01

The biogeochemical liabilities of grain-based crop production for bioenergy are no different from those of grain-based food production: excessive nitrate leakage, soil carbon and phosphorus loss, nitrous oxide production, and attenuated methane uptake. Contingent problems are well known, increasingly well documented, and recalcitrant: freshwater and coastal marine eutrophication, groundwater pollution, soil organic matter loss, and a warming atmosphere. The conversion of marginal lands not now farmed to annual grain production, including the repatriation of Conservation Reserve Program (CRP) and other conservation set-aside lands, will further exacerbate the biogeochemical imbalance of these landscapes, as could pressure to further simplify crop rotations. The expected emergence of biorefinery and combustion facilities that accept cellulosic materials offers an alternative outcome: agricultural landscapes that accumulate soil carbon, that conserve nitrogen and phosphorus, and that emit relatively small amounts of nitrous oxide to the atmosphere. Fields in these landscapes are planted to perennial crops that require less fertilizer, that retain sediments and nutrients that could otherwise be transported to groundwater and streams, and that accumulate carbon in both soil organic matter and roots. If mixed-species assemblages, they additionally provide biodiversity services. Biogeochemical responses of these systems fall chiefly into two areas: carbon neutrality and water and nutrient conservation. Fluxes must be measured and understood in proposed cropping systems sufficient to inform models that will predict biogeochemical behavior at field, landscape, and regional scales. Because tradeoffs are inherent to these systems, a systems approach is imperative, and because potential biofuel cropping systems and their environmental contexts are complex and cannot be exhaustively tested, modeling will be instructive. Modeling alternative biofuel cropping systems converted from different starting points, for example, suggests that converting CRP to corn ethanol production under conventional tillage results in substantially increased net greenhouse gas (GHG) emissions that can be only partly mitigated with no-till management. Alternatively, conversion of existing cropland or prairie to switchgrass production results in a net GHG sink. Outcomes and policy must be informed by science that adequately quantifies the true biogeochemical costs and advantages of alternative systems.

Effect of land use land cover change on soil erosion potential in an agricultural watershed.

PubMed

Sharma, Arabinda; Tiwari, Kamlesh N; Bhadoria, P B S

2011-02-01

Universal soil loss equation (USLE) was used in conjunction with a geographic information system to determine the influence of land use and land cover change (LUCC) on soil erosion potential of a reservoir catchment during the period 1989 to 2004. Results showed that the mean soil erosion potential of the watershed was increased slightly from 12.11 t ha(-1) year(-1) in the year 1989 to 13.21 t ha(-1) year(-1) in the year 2004. Spatial analysis revealed that the disappearance of forest patches from relatively flat areas, increased in wasteland in steep slope, and intensification of cultivation practice in relatively more erosion-prone soil were the main factors contributing toward the increased soil erosion potential of the watershed during the study period. Results indicated that transition of other land use land cover (LUC) categories to cropland was the most detrimental to watershed in terms of soil loss while forest acted as the most effective barrier to soil loss. A p value of 0.5503 obtained for two-tailed paired t test between the mean erosion potential of microwatersheds in 1989 and 2004 also indicated towards a moderate change in soil erosion potential of the watershed over the studied period. This study revealed that the spatial location of LUC parcels with respect to terrain and associated soil properties should be an important consideration in soil erosion assessment process.

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

Forest soil chemistry and terrain attributes in a Catskills watershed

USGS Publications Warehouse

Johnson, C.E.; Ruiz-Mendez, J. J.; Lawrence, G.B.

2000-01-01

Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pH(w), effective cation-exchange capacity (CEC(e)), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pH(w) together explained 33 to 66% of the variation in exchangeable bases and CEC(e). Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CEC(e) (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CEC(e) occupied by H explained 44% of the variation in pH(w). Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pHw, effective cation-exchange capacity (CECe), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pHw together explained 33 to 66% of the variation in exchangeable bases and CECe. Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CECe (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CECe occupied by H explained 44% of the variation in pHw. Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.

Proposal for a Spatial Organization Model in Soil Science (The Example of the European Communities Soil Map).

ERIC Educational Resources Information Center

King, D.; And Others

1994-01-01

Discusses the computational problems of automating paper-based spatial information. A new relational structure for soil science information based on the main conceptual concepts used during conventional cartographic work is proposed. This model is a computerized framework for coherent description of the geographical variability of soils, combined…

Using semi-variogram analysis for providing spatially distributed information on soil surface condition for land surface modeling

NASA Astrophysics Data System (ADS)

Croft, Holly; Anderson, Karen; Kuhn, Nikolaus J.

2010-05-01

The ability to quantitatively and spatially assess soil surface roughness is important in geomorphology and land degradation studies. Soils can experience rapid structural degradation in response to land cover changes, resulting in increased susceptibility to erosion and a loss of Soil Organic Matter (SOM). Changes in soil surface condition can also alter sediment detachment, transport and deposition processes, infiltration rates and surface runoff characteristics. Deriving spatially distributed quantitative information on soil surface condition for inclusion in hydrological and soil erosion models is therefore paramount. However, due to the time and resources involved in using traditional field sampling techniques, there is a lack of spatially distributed information on soil surface condition. Laser techniques can provide data for a rapid three dimensional representation of the soil surface at a fine spatial resolution. This provides the ability to capture changes at the soil surface associated with aggregate breakdown, flow routing, erosion and sediment re-distribution. Semi-variogram analysis of the laser data can be used to represent spatial dependence within the dataset; providing information about the spatial character of soil surface structure. This experiment details the ability of semi-variogram analysis to spatially describe changes in soil surface condition. Soil for three soil types (silt, silt loam and silty clay) was sieved to produce aggregates between 1 mm and 16 mm in size and placed evenly in sample trays (25 x 20 x 2 cm). Soil samples for each soil type were exposed to five different durations of artificial rainfall, to produce progressively structurally degraded soil states. A calibrated laser profiling instrument was used to measure surface roughness over a central 10 x 10 cm plot of each soil state, at 2 mm sample spacing. The laser data were analysed within a geostatistical framework, where semi-variogram analysis quantitatively represented the change in soil surface structure during crusting. The laser data were also used to create digital surface models (DSM) of the soil states for visual comparison. This research has shown that aggregate breakdown and soil crusting can be shown quantitatively by a decrease in sill variance (silt soil: 11.67 (control) to 1.08 (after 90 mins rainfall)). Features present within semi-variograms were spatially linked to features at the soil surface, such as soil cracks, tillage lines and areas of deposition. Directional semi-variograms were used to provide a spatially orientated component, where the directional sill variance associated with a soil crack was shown to increase from 7.95 to 19.33. Periodicity within semi-variogram was also shown to quantify the spatial scale of soil cracking networks and potentially surface flowpaths; an average distance between soil cracks of 37 mm closely corresponded to the distance of 38 mm shown in the semi-variogram. The results provide a strong basis for the future retrieval of spatio-temporal variations in soil surface condition. Furthermore, the presence of process-based information on hydrological pathways within semi-variograms may work towards an inclusion of geostatisically-derived information in land surface models and the understanding of complex surface processes at different spatial scales.

Dye injection for predicting pesticide movement in micro-irrigated polyethylene film mulch beds.

PubMed

Csinos, Alex S; Laska, James E; Childers, Stan

2002-04-01

A new method is described for tracing water movement in polyethylene film covered soil beds. Dye was delivered via a drip tape micro-irrigation system which was placed in the bed as the soil beds were shaped and covered with polyethylene film. The dye was injected into the system and irrigated with water for 4-24 h at 0.41-1.38 bar (41-138 kPa) pressure depending on the experiment. The dye appeared as blue circles on the soil surface within 20 min of injection and produced a three-dimensional pattern in the soil profile. Injection-irrigation-pressure scenarios were evaluated by measuring dye movement directly below and between emitters by sliding fabricated blades vertically into the bed at the desired examination point and excavating the soil away from the blade. The dye typically produced a U shape on the face of the bed and the area was calculated for each of these exposed faces. The area increased as the length of irrigation and water pressure increased. Interrupted irrigation (pulsing) scenarios did not alter the calculated areas encompassed by the dye compared to uninterrupted irrigation scenarios. The blue dye provided a direct, inexpensive and easy method of visualizing water movement in soil beds. This information will be used to optimize application of emulsifiable plant-care products in polyethylene film mulch beds.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Temperature sensitivity of soil respiration rates enhanced by microbial community response.

PubMed

Karhu, Kristiina; Auffret, Marc D; Dungait, Jennifer A J; Hopkins, David W; Prosser, James I; Singh, Brajesh K; Subke, Jens-Arne; Wookey, Philip A; Agren, Göran I; Sebastià, Maria-Teresa; Gouriveau, Fabrice; Bergkvist, Göran; Meir, Patrick; Nottingham, Andrew T; Salinas, Norma; Hartley, Iain P

2014-09-04

Soils store about four times as much carbon as plant biomass, and soil microbial respiration releases about 60 petagrams of carbon per year to the atmosphere as carbon dioxide. Short-term experiments have shown that soil microbial respiration increases exponentially with temperature. This information has been incorporated into soil carbon and Earth-system models, which suggest that warming-induced increases in carbon dioxide release from soils represent an important positive feedback loop that could influence twenty-first-century climate change. The magnitude of this feedback remains uncertain, however, not least because the response of soil microbial communities to changing temperatures has the potential to either decrease or increase warming-induced carbon losses substantially. Here we collect soils from different ecosystems along a climate gradient from the Arctic to the Amazon and investigate how microbial community-level responses control the temperature sensitivity of soil respiration. We find that the microbial community-level response more often enhances than reduces the mid- to long-term (90 days) temperature sensitivity of respiration. Furthermore, the strongest enhancing responses were observed in soils with high carbon-to-nitrogen ratios and in soils from cold climatic regions. After 90 days, microbial community responses increased the temperature sensitivity of respiration in high-latitude soils by a factor of 1.4 compared to the instantaneous temperature response. This suggests that the substantial carbon stores in Arctic and boreal soils could be more vulnerable to climate warming than currently predicted.

Use of Electronic Hand-held Devices for Collection of Savannah River Site Environmental Data - 13329

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

Marberry, Hugh; Moore, Winston

2013-07-01

Savannah River Nuclear Solutions has begun using Xplore Tablet PC's to collect data in the field for soil samples, groundwater samples, air samples and round sheets at the Savannah River Site (SRS). EPA guidelines for groundwater sampling are incorporated into the application to ensure the sample technician follows the proper protocol. The sample technician is guided through the process for sampling and round sheet data collection by a series of menus and input boxes. Field measurements and well stabilization information are entered into the tablet for uploading into Environmental Restoration Data Management System (ERDMS). The process helps to eliminate inputmore » errors and provides data integrity. A soil sample technician has the ability to collect information about location of sample, field parameter, describe the soil sample, print bottle labels, and print chain of custody for the sample that they have collected. An air sample technician has the ability to provide flow, pressure, hours of operation, print bottle labels and chain of custody for samples they collect. Round sheets are collected using the information provided in the various procedures. The data are collected and uploaded into ERDMS. The equipment used is weather proof and hardened for the field use. Global Positioning System (GPS) capabilities are integrated into the applications to provide the location where samples were collected and to help sample technicians locate wells that are not visited often. (authors)« less

Peculiarities of changes in the soil cover of landscapes adjacent to a megalopolis

NASA Astrophysics Data System (ADS)

Lazareva, Margarita; Aparin, Boris; Sukhacheva, Elena

2017-04-01

The progressive growth of cities has a significant impact on the soil cover of territories adjacent to the same. Megalopolises are centers of anthropogenic impact on the soils. Generally, forms and intensity of the urban impact on the soil cover weaken with increasing distance from the city's boundaries. In this respect, ample opportunities for the analysis of urban impact on the adjacent territories are provided by the study of the soil cover in the Leningrad Region (the LR). Saint Petersburg is a major European megalopolis, which is the administrative center of the LR. The time period of Saint Petersburg's impact on the environment does not exceed 300 years, which allows us to identify very clearly the character and areas of its impact on the soil cover. Over the past decades, there have been significant changes in the soils and the soil cover of the LR. In a large territory, there appeared new anthropogenic soils and soil cover organization forms, having no natural analogues, with a dramatic increase in the surface area of degraded soils. To access the current state of soil cover, to identify the role of anthropogenic factors of changes in this state; to carry out land reclamation, remediation and rehabilitation measures; to perform land cadastral valuation etc., we need an information resource containing data on the current state of soils and soil cover in the LR, the key element of which should be a map. We carried out mapping and created a 1:200 000 digital soil map (DSM) for the LR's territories. Diagnostics of soil contours were performed using traditionally drawn-up (paper) maps of soils and soil-formation factors; satellite images (Google, Yandex); data of remote sensing (Spot 5, Landsat 7,8); digital maps of main soil-formation factors (topographical ones, etc.). The digital soil map of the LR has been created in the geographic information system - QGIS. The map clarifies the contours of natural soils and soil combinations, and shows, for the first time, the contours of: - non-soil formations; - soils of the initial soil formation; - soils of agricultural lands within their existing boundaries; - soils and soil combinations that are specific for human settlements and horticultural land plots; - fallow lands; - anthropogenically disturbed soils. During the analysis of the created digital medium-scale soil map, we identified some changes in the soil cover of the territories adjacent to Saint Petersburg. Virtually in all the landscapes, we found a large number of soil cover structures, the components of which, along with natural soils, are anthropogenically disturbed soils, anthropogenic soils and non-soil formations. We revealed that the human impact on the soil cover is manifested within the range that varies from insignificant changes in soil parameters to radical transformations of the soil profile, complete destruction of soil and "creation" of new soil forms and soil cover organization forms. We have developed a typology of anthropogenically changed and anthropogenically created soil cover structures, taking into consideration the types of the economic impact on and the quality of environmental functions performed by the soils.

Effect of land-use change on soil organic carbon stocks in the Eastern Usambara Mountain (Tanzania)

NASA Astrophysics Data System (ADS)

Kirsten, Maximilian; Kaaya, Abel; Klinger, Thomas; Feger, Karl-Heinz

2014-05-01

A soil organic carbon (SOC) inventory, covering 10 sites with 5 different land-use systems (primary forest, secondary forest, tea plantation, home garden, and cropland) was conducted in the tropical monsoonal Eastern Usambara Mountains (EUM), NE Tanzania. At all sites the environmental factors such as climate and parent material, for soil formation (gneiss), as well as elevation and slope position are highly comparable. The evergreen submontane primary rain forest, which still exists in vast areas in the EUM and the well-known land-use history there provide nearly optimal conditions for the assessment of land-use change effects on soil properties, notably the SOC stocks. We collected horizon-wise samples from soil pit profiles. In addition, samples from fixed depth-intervals were taken from 8 augering points located systematically around each soil pit. The sampling scheme yielded a unique set of soil information (pedological, chemical, and physical) that favours a reliable assessment of SOC stocks and future analytical work on SOM quality and binding mechanisms. The investigated soils are characterized by high clay contents, which increase with depth. Soil pH varies between 3.5 and 5.4 over all land-use systems and horizons, higher pH values could be detected for the agricultural systems in the topsoil, the differences between agricultural and forest systems decrease in the subsoil. The potential cation exchange capacity is in most cases < 24 cmolc kg-1, furthermore the base saturation is always < 50 % in the subsoil. Thus, based on that analytical data all soils can be classified as Acrisols revealing the high comparability of the investigated sites. This is an excellent prerequisite for the 'false chronosequence' approach applied. Organic carbon (C) stocks in the soils from the investigated land-use systems cover a wide range between 17.1 and 24.2 kg m-2 (0-100 cm). Variability is even high in the subset of the 3 primary forests. Statistically significant differences between the forest and cropland systems occur in the uppermost depth interval 0-10 cm. Furthermore, the primary forests have higher, but not significantly different SOC stocks in the topsoil (0-40 cm) compared with the cropland systems. In all investigated soils the SOC stocks for the entire soil profiles (0-100 cm) are in a narrow range. This may give a hint on SOC relocation from the topsoil to the subsoil when forests were converted to cropland systems. Our results reveal that this land-use change has led to a shift in above- and belowground litter distribution and amount. Also slash and burn practises as well as burning of plant residues in arable farming are common in the EUM. Both phenomena may control SOC relocation as they are associated with a changed C input and/or the formation of C compounds that can be relocated in the profile. In all investigated soils high concentrations of dithionite- and oxalate- extractable iron and aluminum were analyzed. Hence, interaction of SOC with oxides formed by the two metals is here probably one of the main stabilization mechanisms of SOC. The relocation and stabilization processes of SOC are the key functions for the implementation of sustainable agriculture in the EUM, and the conducted study provide a suitable basis for our ongoing research in this region of the wet tropics of Africa.

Using GIS and Ahp for Planning Primer Transportation of Forest Products

NASA Astrophysics Data System (ADS)

Akay, A. E.; Yılmaz, B.

2017-11-01

Primer transportation is one of the most costly and time consuming forestry activities in extraction of timber from forest lands. Transportation methods are essentially determined based on terrain characteristics, especially ground slope. Besides, unsuitable machine selection and unplanned operations may cause ecological damages such as soil disturbance. Soil damage can lead to long term impacts on forest ecosystem. Thus, the optimum transportation methods should be determined by considering not only economic factors but also topographical factors and soil conditions. In recent decades, some of the advanced features of Geographical Information System (GIS) assist decision makers to solve such complex transportation problems with various constraints. In this study, it was aimed to plan forest transportation operation by using GIS integrated Analytical Hierarchy Process (AHP) method, considering ground slope, soil type, and available transportation equipment in the region. This method was implemented within the border of İnegöl Forest Enterprise Chief in the city of Bursa in Turkey. Alternative transportation method included cable system, chute system, skidder, and farm tractor. GIS-based method integrated with AHP found that skidder was the optimal transportation method for about 60% of the study area, while farm tractor was the second most suitable method with 25% ground cover. The results indicated that GIS-based decision support systems can be effectively used as rational, quick, and economic tool for forest transportation planning.

Debris flow early warning systems in Norway: organization and tools

NASA Astrophysics Data System (ADS)

Kleivane, I.; Colleuille, H.; Haugen, L. E.; Alve Glad, P.; Devoli, G.

2012-04-01

In Norway, shallow slides and debris flows occur as a combination of high-intensity precipitation, snowmelt, high groundwater level and saturated soil. Many events have occurred in the last decades and are often associated with (or related to) floods events, especially in the Southern of Norway, causing significant damages to roads, railway lines, buildings, and other infrastructures (i.e November 2000; August 2003; September 2005; November 2005; Mai 2008; June and Desember 2011). Since 1989 the Norwegian Water Resources and Energy Directorate (NVE) has had an operational 24 hour flood forecasting system for the entire country. From 2009 NVE is also responsible to assist regions and municipalities in the prevention of disasters posed by landslides and snow avalanches. Besides assisting the municipalities through implementation of digital landslides inventories, susceptibility and hazard mapping, areal planning, preparation of guidelines, realization of mitigation measures and helping during emergencies, NVE is developing a regional scale debris flow warning system that use hydrological models that are already available in the flood warning systems. It is well known that the application of rainfall thresholds is not sufficient to evaluate the hazard for debris flows and shallow slides, and soil moisture conditions play a crucial role in the triggering conditions. The information on simulated soil and groundwater conditions and water supply (rain and snowmelt) based on weather forecast, have proved to be useful variables that indicate the potential occurrence of debris flows and shallow slides. Forecasts of runoff and freezing-thawing are also valuable information. The early warning system is using real-time measurements (Discharge; Groundwater level; Soil water content and soil temperature; Snow water equivalent; Meteorological data) and model simulations (a spatially distributed version of the HBV-model and an adapted version of 1-D soil water and energy balance model COUP). The data are presented in a web- and GIS-based system with daily nationwide maps showing the meteorological and hydrological conditions for the present and the near future from quantitative weather prognosis. In addition a division of the country in homogenous debris flow-prone regions is also under progress based on geomorfological, topographic parameters and loose quaternary deposits distribution. Threshold-levels are being investigated by using statistical analyses of historical debris flows events and measured hydro-meteorological parameters. The debris flow early warning system is currently being tested and is expected to be operational in 2013. Final products will be warning messages and a map showing the different hazard levels, from low to high, indicating the landslide probability and the type of expected damages in a certain area. Many activities are realized in strong collaboration with the road and railway authorities, the geological survey and private consultant companies.

Environmental impacts on soil and groundwater at airports: origin, contaminants of concern and environmental risks.

PubMed

Nunes, L M; Zhu, Y-G; Stigter, T Y; Monteiro, J P; Teixeira, M R

2011-11-01

Environmental impacts of airports are similar to those of many industries, though their operations expand over a very large area. Most international impact assessment studies and environmental management programmes have been giving less focus on the impacts to soil and groundwater than desirable. This may be the result of the large attention given to air and noise pollution, relegating other environmental descriptors to a second role, even when the first are comparatively less relevant. One reason that contributes to such "biased" evaluation is the lack of systematic information about impacts to soil and groundwater from airport activities, something the present study intends to help correct. Results presented here include the review of over seven hundred documents and online databases, with the objective of obtaining the following information to support environmental studies: (i) which operations are responsible for chemical releases?; (ii) where are these releases located?; (iii) which contaminants of concern are released?; (iv) what are the associated environmental risks? Results showed that the main impacts occur as a result of fuel storage, stormwater runoff and drainage systems, fuel hydrant systems, fuel transport and refuelling, atmospheric deposition, rescue and fire fighting training areas, winter operations, electrical substations, storage of chemical products by airport owners or tenants, and maintenance of green areas. A new method for ranking environmental risks of organic substances, based on chemical properties, is proposed and applied. Results show that the contaminants with the highest risks are the perfluorochemicals, benzene, trichloroethylene and CCl(4). The obtained information provides a basis for establishing the planning and checking phases of environmental management systems, and may also help in the best design of pollution prevention measures in order to avoid or reduce significant environmental impacts from airports.

Endosulfan in China 2-emissions and residues.

PubMed

Jia, Hongliang; Sun, Yeqing; Li, Yi-Fan; Tian, Chongguo; Wang, Degao; Yang, Meng; Ding, Yongshen; Ma, Jianmin

2009-05-01

Endosulfan is one of the organochlorine pesticides (OCPs) and also a candidate to be included in a group of new persistent organic pollutants (UNEP 2007). The first national endosulfan usage inventories in China with 1/4 degrees longitude by 1/6 degrees latitude resolution has been reported in an accompanying paper. In the second part of the paper, we compiled the gridded historical emissions and soil residues of endosulfan in China from the usage inventories. Based on the residue/emission data, gridded concentrations of endosulfan in Chinese soil and air have been calculated. These inventories will provide valuable data for the further study of endosulfan. Emission and residue of endosulfan were calculated from endosulfan usage by using a simplified gridded pesticide emission and residue model-SGPERM, which is an integrated modeling system combining mathematical model, database management system, and geographic information system. By using the emission and residue inventories, annual air and soil concentrations of endosulfan in each cell were determined. Historical gridded emission and residue inventories of alpha- and beta-endosulfan in agricultural soil in China with 1/4 degrees longitude by 1/6 degrees latitude resolution have been created. Total emissions were around 10,800 t, with alpha-endosulfan at 7,400 t and beta-endosulfan at 3,400 t from 1994 to 2004. The highest residues were 140 t for alpha-endosulfan and 390 t for beta-endosulfan, and the lowest residues were 0.7 t for alpha-endosulfan and 170 t for beta-endosulfan in 2004 in Chinese agricultural soil where endosulfan was applied. Based on the emission and residue inventories, concentrations of alpha- and beta-endosulfan in Chinese air and agricultural surface soil were also calculated for each grid cell. We have estimated annual averaged air concentrations and the annual minimum and maximum soil concentrations across China. The real concentrations will be different from season to season. Although our model does not consider the transport of the insecticide in the atmosphere, which could be very important in some areas during some special time, the estimated concentrations of endosulfan in Chinese air and soil derived from the endosulfan emission and residue inventories are in general consistent with the published monitoring data. To our knowledge, this work is the first inventory of this kind for endosulfan published on a national scale. Concentrations of the chemical in Chinese air and agricultural surface soil were calculated for each grid cell. Results show that the estimated concentrations of endosulfan in Chinese air and soil agree reasonably well with the monitoring data in general. The gridded endosulfan emission/residue inventories and also the air and soil concentration inventories created in this study will be updated upon availability of new information, including usage and monitoring data. The establishment of these inventories for the OCP is important for both scientific communities and policy makers.

Regulatory guidance on soil cover systems

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

Kane, J.D.

1991-12-31

The US Nuclear Regulatory Commission (NRC) in September 1991, completed revisions to 14 sections of the Standard Review Plan (SRP) for the Review of a License Application for a Low-Level Radioactive Waste Disposal Facility. The major purposes of the SRP are to ensure the quality and uniformity of the NRC staff`s safety reviews, and to present a well-defined base from which to evaluate the acceptability of information and data provided in the Safety Analysis Report (SAR) portion of the license application. SRP 3.2, entitled, Design Considerations for Normal and Abnormal/Accident Conditions, was one of the sections that was revised bymore » the NRC staff. This revision was completed to provide additional regulatory guidance on the important considerations that need to be addressed for the proper design and construction of soil cover systems that are to be placed over the LLW. The cover system over the waste is acknowledged to be one of the most important engineered barriers for the long-term stable performance of the disposal facility. The guidance in revised SRP 3.2 summarizes the previous efforts and recommendations of the US Army Corps of Engineers (COE), and a peer review panel on the placement of soil cover systems. NRC published these efforts in NUREG/CR-5432. The discussions in this paper highlight selected recommendations on soil cover issues that the NRC staff considers important for ensuring the safe, long-term performance of the soil cover systems. The development phases to be discussed include: (1) cover design; (2) cover material selection; (3) laboratory and field testing; (4) field placement control and acceptance; and (5) penetrations through the constructed covers.« less

Evaluation of Soil Contamination Indices in a Mining Area of Jiangxi, China

PubMed Central

Wu, Jin; Teng, Yanguo; Lu, Sijin; Wang, Yeyao; Jiao, Xudong

2014-01-01

There is currently a wide variety of methods used to evaluate soil contamination. We present a discussion of the advantages and limitations of different soil contamination assessment methods. In this study, we analyzed seven trace elements (As, Cd, Cr, Cu, Hg, Pb, and Zn) that are indicators of soil contamination in Dexing, a city in China that is famous for its vast nonferrous mineral resources in China, using enrichment factor (EF), geoaccumulation index (Igeo), pollution index (PI), and principal component analysis (PCA). The three contamination indices and PCA were then mapped to understand the status and trends of soil contamination in this region. The entire study area is strongly enriched in Cd, Cu, Pb, and Zn, especially in areas near mine sites. As and Hg were also present in high concentrations in urban areas. Results indicated that Cr in this area originated from both anthropogenic and natural sources. PCA combined with Geographic Information System (GIS) was successfully used to discriminate between natural and anthropogenic trace metals. PMID:25397401

Single versus repeated applications of CuO and Ag nanomaterials and their effect on soil microflora.

PubMed

Schlich, Karsten; Beule, Lukas; Hund-Rinke, Kerstin

2016-08-01

Nanomaterials enter the terrestrial environment via the repeated application of sludge to soils over many years. The goal of this investigation was to compare the effects of CuO and Ag nanomaterials on soil microorganisms after a single application and after repeated applications ultimately resulting in the same test concentrations. The effect on soil microorganisms was determined using the ammonium oxidation (ISO 15685), enzymatic activity patterns (ISO 22939) and MicroResp™ tests on days 28, 56 and 84. The comparability of single and repeated applications of ion-releasing nanomaterials depended on the test endpoint and duration. No significant differences between single and repeated applications were observed when testing nitrifying microorganisms and exoenzymes, but differences were observed in the substrate-induced respiration test. The three test systems used together provide more comprehensive information about the impact of different nanomaterials on the soil microflora and its diversity. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

NASA Technical Reports Server (NTRS)

Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

1998-01-01

The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

Regionalising MUSLE factors for application to a data-scarce catchment

NASA Astrophysics Data System (ADS)

Gwapedza, David; Slaughter, Andrew; Hughes, Denis; Mantel, Sukhmani

2018-04-01

The estimation of soil loss and sediment transport is important for effective management of catchments. A model for semi-arid catchments in southern Africa has been developed; however, simplification of the model parameters and further testing are required. Soil loss is calculated through the Modified Universal Soil Loss Equation (MUSLE). The aims of the current study were to: (1) regionalise the MUSLE erodibility factors and; (2) perform a sensitivity analysis and validate the soil loss outputs against independently-estimated measures. The regionalisation was developed using Geographic Information Systems (GIS) coverages. The model was applied to a high erosion semi-arid region in the Eastern Cape, South Africa. Sensitivity analysis indicated model outputs to be more sensitive to the vegetation cover factor. The simulated soil loss estimates of 40 t ha-1 yr-1 were within the range of estimates by previous studies. The outcome of the present research is a framework for parameter estimation for the MUSLE through regionalisation. This is part of the ongoing development of a model which can estimate soil loss and sediment delivery at broad spatial and temporal scales.

Forest management applications of Landsat data in a geographic information system

NASA Technical Reports Server (NTRS)

Maw, K. D.; Brass, J. A.

1982-01-01

The utility of land-cover data resulting from Landsat MSS classification can be greatly enhanced by use in combination with ancillary data. A demonstration forest management applications data base was constructed for Santa Cruz County, California, to demonstrate geographic information system applications of classified Landsat data. The data base contained detailed soils, digital terrain, land ownership, jurisdictional boundaries, fire events, and generalized land-use data, all registered to a UTM grid base. Applications models were developed from problems typical of fire management and reforestation planning.

Analysis of Summer Thunderstorms in Central Alabama Using the NASA Land Information System

NASA Technical Reports Server (NTRS)

James, Robert; Case, Jonathan; Molthan, Andrew; Jedloved, Gary

2010-01-01

Forecasters have difficulty predicting "random" afternoon thunderstorms during the summer months. Differences in soil characteristics could be a contributing factor for storms. The NASA Land Information System (LIS) may assist forecasters in predicting summer convection by identifying boundaries in land characteristics. This project identified case dates during the summer of 2009 by analyzing synoptic weather maps, radar, and satellite data to look for weak atmospheric forcing and disorganized convective development. Boundaries in land characteristics that may have lead to convective initiation in central Alabama were then identified using LIS.

Wildland fire in ecosystems: effects of fire on soils and water

Treesearch

Daniel G. Neary; Kevin C. Ryan; Leonard F. DeBano

2005-01-01

This state-of-knowledge review about the effects of fire on soils and water can assist land and fire managers with information on the physical, chemical, and biological effects of fire needed to successfully conduct ecosystem management, and effectively inform others about the role and impacts of wildland fire. Chapter topics include the soil resource, soil physical...

Farmer data sourcing. The case study of the spatial soil information maps in South Tyrol.

NASA Astrophysics Data System (ADS)

Della Chiesa, Stefano; Niedrist, Georg; Thalheimer, Martin; Hafner, Hansjörg; La Cecilia, Daniele

2017-04-01

Nord-Italian region South Tyrol is Europe's largest apple growing area exporting ca. 15% in Europe and 2% worldwide. Vineyards represent ca. 1% of Italian production. In order to deliver high quality food, most of the farmers in South Tyrol follow sustainable farming practices. One of the key practice is the sustainable soil management, where farmers collect regularly (each 5 years) soil samples and send for analyses to improve cultivation management, yield and finally profitability. However, such data generally remain inaccessible. On this regard, in South Tyrol, private interests and the public administration have established a long tradition of collaboration with the local farming industry. This has granted to the collection of large spatial and temporal database of soil analyses along all the cultivated areas. Thanks to this best practice, information on soil properties are centralized and geocoded. The large dataset consist mainly in soil information of texture, humus content, pH and microelements availability such as, K, Mg, Bor, Mn, Cu Zn. This data was finally spatialized by mean of geostatistical methods and several high-resolution digital maps were created. In this contribution, we present the best practice where farmers data source soil information in South Tyrol. Show the capability of a large spatial-temporal geocoded soil dataset to reproduce detailed digital soil property maps and to assess long-term changes in soil properties. Finally, implication and potential application are discussed.

Soil moisture monitoring for crop management

NASA Astrophysics Data System (ADS)

Boyd, Dale

2015-07-01

The 'Risk management through soil moisture monitoring' project has demonstrated the capability of current technology to remotely monitor and communicate real time soil moisture data. The project investigated whether capacitance probes would assist making informed pre- and in-crop decisions. Crop potential and cropping inputs are increasingly being subject to greater instability and uncertainty due to seasonal variability. In a targeted survey of those who received regular correspondence from the Department of Primary Industries it was found that i) 50% of the audience found the information generated relevant for them and less than 10% indicted with was not relevant; ii) 85% have improved their knowledge/ability to assess soil moisture compared to prior to the project, with the most used indicator of soil moisture still being rain fall records; and iii) 100% have indicated they will continue to use some form of the technology to monitor soil moisture levels in the future. It is hoped that continued access to this information will assist informed input decisions. This will minimise inputs in low decile years with a low soil moisture base and maximise yield potential in more favourable conditions based on soil moisture and positive seasonal forecasts

Contribution of Soil Moisture Information to Streamflow Prediction in the Snowmelt Season: A Continental-Scale Analysis

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Mahanama, Sarith; Koster, Randal; Lettenmaier, Dennis

2009-01-01

In areas dominated by winter snowcover, the prediction of streamflow during the snowmelt season may benefit from three pieces of information: (i) the accurate prediction of weather variability (precipitation, etc.) leading up to and during the snowmelt season, (ii) estimates of the amount of snow present during the winter season, and (iii) estimates of the amount of soil moisture underlying the snowpack during the winter season. The importance of accurate meteorological predictions and wintertime snow estimates is obvious. The contribution of soil moisture to streamflow prediction is more subtle yet potentially very important. If the soil is dry below the snowpack, a significant fraction of the snowmelt may be lost to streamflow and potential reservoir storage, since it may infiltrate the soil instead for later evaporation. Such evaporative losses are presumably smaller if the soil below the snowpack is wet. In this paper, we use a state-of-the-art land surface model to quantify the contribution of wintertime snow and soil moisture information -- both together and separately -- to skill in forecasting springtime streamflow. We find that soil moisture information indeed contributes significantly to streamflow prediction skill.

Data acquisition system for soil degradation measurements in sloping vineyard

NASA Astrophysics Data System (ADS)

Bidoccu, Marcella; Opsi, Francesca; Cavallo, Eugenio

2013-04-01

The agricultural management techniques and mechanization adopted in sloping areas under temperate and sub-continental climate can affect the physical and hydrological characteristics of the soil with an increase of the soil erosion rates. Vineyards have been reported among the land uses most prone to erosion. Agricultural operations can be conducted to enhance the soil conservation, it is therefore important to know the site-specific characteristics and conditions of adopted practices. A long-term monitoring to evaluate the influence of management systems in hilly vineyard on erosion and runoff and soil properties has been carried out in the north-western Italy since 2000. Three different inter-rows tillage systems were compared: conventional tillage (CT), reduced tillage (RT) and controlled grass cover (GC). To record the rainfall amount and duration, an agro-meteorological station was located near experimental plots. The three plots are hydraulically isolated, thus runoff and sediment have been collected at the bottom by a drain, connected with a tipping bucket device to measure the discharge of runoff. The system was implemented with electromagnetic counters that allow the automatic accounting with data capture by a control unit, powered by a photovoltaic panel and transmitted to a data collection center for remote viewing via web page. A portion of the runoff-sediment mixture was usually sampled and analyzed for soil and nutrients losses. In order to analyze with more detail the erosion process by means of predictive models, a micro-plot system was placed in the experimental site in 2012. Splash cups have been installed in each plot since 2011 to evaluate how the soil management affects the in-field splash erosion process. Rapid measurement of soil moisture content and temperature were performed starting from August 2011 to allow continuous monitoring of parameters that can provide an evaluation of space-time hydrological processes, determining the surface runoff response to a given precipitation events. Electromagnetic sensors were installed in the topsoil and measures were recorded in one-hour intervals by a data collection device. Some physical and hydrological properties were considered to provide information on the degree of soil compaction and its influence on soil status. The parameters analyzed are bulk density by core method and soil compaction by static and dynamic recording penetrometers. Since autumn 2011 the reduced tillage management was replaced with conventional tillage with a grass strip in the bottom of each inter-row (CTS). At the same time the grass cover of the GC plot was renewed after execution of tillage operation. Recurring measurements of the soil water content up to a depth of 60 cm and hydraulic conductivity tests with the Simplified Falling Head Technique (SFH) have been started in 2012, to observe the spatial and temporal variability of hydraulic behavior in the experimental plots.

Soil! Get the Scoop - The Soil Science Society of America's International Year of Soils Campaign

NASA Astrophysics Data System (ADS)

Lindbo, David L.; Hopmans, Jan; Olson, Carolyn; Fisk, Susan; Chapman, Susan; van Es, Harold

2015-04-01

Soils are a finite natural resource and are nonrenewable on a human time scale. Soils are the foundation for food, animal feed, fuel and natural fiber production, the supply of clean water, nutrient cycling and a range of ecosystem functions. The area of fertile soils covering the world's surface is limited and increasingly subject to degradation, poor management and loss to urbanization. Increased awareness of the life-supporting functions of soil is called for if this trend is to be reversed and so enable the levels of food production necessary to meet the demands of population levels predicted for 2050. The Soil Science Society of America is coordinating with the Global Soil Partnership and other organizations around the world to celebrate the 2015 International Year of Soils and raise awareness and promote the sustainability of our limited soil resources. We all have a valuable role in communicating vital information on soils, a life sustaining natural resource. Therefore, we will provide resources to learn about soils and help us tell the story of soils. We will promote IYS on social media by sharing our posts from Facebook and Twitter. Additionally SSSA developed 12 monthly themes that reflect the diverse value of soils to our natural environment and society. Each month has information on the theme, a lesson plan, and other outreach activities. All information is available on a dedicated website www.soil.org/IYS. The site will be updated constantly throughout the year.

Evaluation of a Soil Moisture Data Assimilation System Over the Conterminous United States

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Crow, W. T.; Zhan, X.; Reynolds, C. A.; Jackson, T. J.

2008-12-01

A data assimilation system has been designed to integrate surface soil moisture estimates from the EOS Advanced Microwave Scanning Radiometer (AMSR-E) with an online soil moisture model used by the USDA Foreign Agriculture Service for global crop estimation. USDA's International Production Assessment Division (IPAD) of the Office of Global Analysis (OGA) ingests global soil moisture within a Crop Assessment Data Retrieval and Evaluation (CADRE) Decision Support System (DSS) to provide nowcasts of crop conditions and agricultural-drought. This information is primarily used to derive mid-season crop yield estimates for the improvement of foreign market access for U.S. agricultural products. The CADRE is forced by daily meteorological observations (precipitation and temperature) provided by the Air Force Weather Agency (AFWA) and World Meteorological Organization (WMO). The integration of AMSR-E observations into the two-layer soil moisture model employed by IPAD can potentially enhance the reliability of the CADRE soil moisture estimates due to AMSR-E's improved repeat time and greater spatial coverage. Assimilation of the AMSR-E soil moisture estimates is accomplished using a 1-D Ensemble Kalman filter (EnKF) at daily time steps. A diagnostic calibration of the filter is performed using innovation statistics by accurately weighting the filter observation and modeling errors for three ranges of vegetation biomass density estimated using historical data from the Advanced Very High Resolution Radiometer (AVHRR). Assessment of the AMSR-E assimilation has been completed for a five year duration over the conterminous United States. To evaluate the ability of the filter to compensate for incorrect precipitation forcing into the model, a data denial approach is employed by comparing soil moisture results obtained from separate model simulations forced with precipitation products of varying uncertainty. An analysis of surface and root-zone anomalies is presented for each model simulation over the conterminous United States, as well as statistical assessments for each simulation over various land cover types.

A multi-technique approach to assess chemical speciation of phosphate in soils

NASA Astrophysics Data System (ADS)

Belchior Abdala, Dalton; Rodrigues, Marcos; Herrera, Wilfrand; Pavinato, Paulo Sergio

2017-04-01

Soil scientists see chemical characterization of phosphorus (e.g., chemical speciation) as a winning strategy to increase phosphorus use efficiency in agriculture, to understand the fate of applied P fertilizer in soils and to devise strategies to minimize P losses to the environment. Phosphorus (P) is majorly presented in soils as phosphate, bound to mineral components of soils such as Al-, Ca- and Fe-(hydr)oxides or associated with organic molecules, being thus generally referred to as organic phosphates. In addition, because of the turnover of P between plants and microbes, it delivers P back to soils as a mixture of species with high spatial and chemical heterogeneity, adding complexity to the determination of the P species contained in environmental samples. Therefore, due to the variety of forms that phosphate can present in soils, its precise chemical characterization can only be achieved using a set of analytical techniques. Although established methodologies (e. g., soil test P, sequential chemical fractionation, P isotherms) have been useful to subsidize information for the establishment of policies and guidelines for soil management and P fertilizers use, they have failed to provide detailed information on P chemistry and reactivity in soils in a more satisfactory manner, which are critical to predict P bioavailability to plants and loss potential to the environment. More recently, the association of wet chemistry analysis with spectroscopy and microscopy techniques has arguably represented the most successful means to chemically speciate phosphate in soils. This is because using qualitative (chemical speciation), quantitative (chemical fractionation) and spatial (microscopy) data allows for triangulation of information, thereby reducing bias and increasing validity of the results. The analysis framework that we propose in this study includes the use of (i) sequential chemical fractionation of soil P to determine the partitioning of P within the different P pools considered in the fractionation protocol, (ii) two synchrotron-based X-ray absorption spectroscopic techniques, XANES and EXAFS, for chemical characterization of the P forms and mineralogy of Fe-(hydr)oxides present in a sample, and (iii) Scanning Electron Microscopy and Energy-Dispersive spectroscopy, SEM/EDS, to provide complimentary information to corroborate and aid in the interpretation of our P XANES data. It was shown that the combination of techniques can assist us not only in the determination of the P chemical species present in a given material, but also to better understand the complex and dynamic processes to which P is subjected in soils. The association of spectroscopy (XANES and EXAFS) and microscopy (SEM/EDS) with wet chemistry data in this study was key to shift our understanding of the relationship between P and other soil mineral components from a macroscopic into a microscopic one. This represents a strong driving force to integrate the results of multi-analytical techniques into a more complete understanding of the systems under study. In addition, we provide a library of reference spectra for P K-edge XANES containing P sorbed to single and binary mixtures of mineral analogues intended to assist in the identification of P sorbed species commonly found in soils and sediments. Key-words: P K-edge XANES, Fe K-edge EXAFS, sequential chemical fractionation, soil phosphorus

Soil erosion assessment using the Universal Soil Loss Equation (USLE) in a GIS framework: A case study of Zacatecas, México

NASA Astrophysics Data System (ADS)

Betanzos Arroyo, L. I.; Prol Ledesma, R. M.; da Silva Pinto da Rocha, F. J. P.

2014-12-01

The Universal Soil Loss Equation (USLE), which is considered to be a contemporary approach in soil loss assessment, was used to assess soil erosion hazard in the Zacatecas mining district. The purpose of this study is to produce erosion susceptibility maps for an area that is polluted with mining tailings which are susceptible to erosion and can disperse the particles that contain heavy metals and other toxic elements. USLE method is based in the estimation of soil loss per unit area and takes into account specific parameters such as precipitation data, topography, soil erodibility, erosivity and runoff. The R-factor (rainfall erosivity) was calculated from monthly and annual precipitation data. The K-factor (soil erodibility) was estimated using soil maps available from the CONABIO at a scale of 1:250000. The LS-factor (slope length and steepness) was determined from a 30-m digital elevation model. A raster-based Geographic Information System (GIS) was used to interactively calculate soil loss and map erosion hazard. The results show that estimated erosion rates ranged from 0 to 4770.48 t/ha year. Maximum proportion of the total area of the Zacatecas mining district have nil to very extremely slight erosion severity. Small areas in the central and south part of the study area shows the critical condition requiring sustainable land management.

Soil loss estimation and prioritization of sub-watersheds of Kali River basin, Karnataka, India, using RUSLE and GIS.

PubMed

Markose, Vipin Joseph; Jayappa, K S

2016-04-01

Most of the mountainous regions in tropical humid climatic zone experience severe soil loss due to natural factors. In the absence of measured data, modeling techniques play a crucial role for quantitative estimation of soil loss in such regions. The objective of this research work is to estimate soil loss and prioritize the sub-watersheds of Kali River basin using Revised Universal Soil Loss Equation (RUSLE) model. Various thematic layers of RUSLE factors such as rainfall erosivity (R), soil erodibility (K), topographic factor (LS), crop management factor (C), and support practice factor (P) have been prepared by using multiple spatial and non-spatial data sets. These layers are integrated in geographic information system (GIS) environment and estimated the soil loss. The results show that ∼42 % of the study area falls under low erosion risk and only 6.97 % area suffer from very high erosion risk. Based on the rate of soil loss, 165 sub-watersheds have been prioritized into four categories-very high, high, moderate, and low erosion risk. Anthropogenic activities such as deforestation, construction of dams, and rapid urbanization are the main reasons for high rate of soil loss in the study area. The soil erosion rate and prioritization maps help in implementation of a proper watershed management plan for the river basin.

Development of a Coordinated National Soil Moisture Network: A Pilot Study

NASA Astrophysics Data System (ADS)

Lucido, J. M.; Quiring, S. M.; Verdin, J. P.; Pulwarty, R. S.; Baker, B.; Cosgrove, B.; Escobar, V. M.; Strobel, M.

2014-12-01

Soil moisture data is critical for accurate drought prediction, flood forecasting, climate modeling, prediction of crop yields and water budgeting. However, soil moisture data are collected by many agencies and organizations in the United States using a variety of instruments and methods for varying applications. These data are often distributed and represented in disparate formats, posing significant challenges for use. In recognition of these challenges, the President's Climate Action Plan articulated the need for a coordinated national soil moisture network. In response to this action plan, a team led by the National Integrated Drought Information System has begun to develop a framework for this network and has instituted a proof-of-concept pilot study. This pilot is located in the south-central plains of the US, and will serve as a reference architecture for the requisite data systems and inform the design of the national network. The pilot comprises both in-situ and modeled soil moisture datasets (historical and real-time) and will serve the following use cases: operational drought monitoring, experimental land surface modeling, and operational hydrological modeling. The pilot will be implemented using a distributed network design in order to serve dispersed data in real-time directly from data providers. Standard service protocols will be used to enable future integration with external clients. The pilot network will additionally contain a catalog of data sets and web service endpoints, which will be used to broker web service calls. A mediation and aggregation service will then intelligently request, compile, and transform the distributed datasets from their native formats into a standardized output. This mediation framework allows data to be hosted and maintained locally by the data owners while simplifying access through a single service interface. These data services will then be used to create visualizations, for example, views of the current soil moisture conditions compared to historical baselines via a map-based web application. This talk will comprise an overview of the pilot design and implementation, a discussion of strategies for integrating in-situ and modeled soil moisture data sets as well as lessons learned during the course of the pilot.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Hydrological modeling of upper Indus Basin and assessment of deltaic ecology

USDA-ARS?s Scientific Manuscript database

Managing water resources is mostly required at watershed scale where the complex hydrology processes and interactions linking land surface, climatic factors and human activities can be studied. Geographical Information System based watershed model; Soil and Water Assessment Tool (SWAT) is applied f...

Information model for digital exchange of soil-related data - potential modifications on ISO 28258

NASA Astrophysics Data System (ADS)

Schulz, Sina; Eberhardt, Einar; Reznik, Tomas

2017-04-01

ABSTRACT The International Standard ISO 28258 "Digital exchange of soil-related data" provides an information model that describes the organization of soil data to facilitate data transfer between data producers, holders and users. The data model contains a fixed set of "core" soil feature types, data types and properties, whereas its customization is on the data provider level, e.g. by adding user-specific properties. Rules for encoding these information are given by a customized XML-based format (called "SoilML"). Some technical shortcomings are currently under consideration in the ISO working group. Directly after publication of ISO 28258 in 2013, also several conceptual and implementation issues concerning the information model had been identified, such as renaming of feature types, modification of data types, and enhancement of definitions or addition of super-classes are part of the current revision process. Conceptual changes for the current ISO data model that are compatible with the Australian/New Zealand soil data model ANZSoilML and the EU INSPIRE Data Specifications Soil are also discussed. The concept of a model with a limited set of properties that can be extended by the data provider should remain unaffected. This presentation aims to introduce and comment on the current ISO soil information model and the proposed modifications. Moreover, we want to discuss these adjustments with respect to enhanced applicability of this International Standard.

Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal

USGS Publications Warehouse

Dieye, A.M.; Roy, David P.; Hanan, N.P.; Liu, S.; Hansen, M.; Toure, A.

2012-01-01

Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.

Use of geographic information systems for applications on gas pipeline rights-of-way

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

Sydelko, P.J.; Wilkey, P.L.

1992-12-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

GIS least-cost analysis approach for siting gas pipeline ROWs

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

Sydelko, P.J.; Wilkey, P.L.

1994-09-01

Geographic-information-system applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation corridors, endangered species habitats, wetlands, and public line surveys. A geographic information system was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas-pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

Use of geographic information systems for applications on gas pipeline rights-of-way

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

Sydelko, P.J.

1993-10-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for land use/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

Use of geographic information systems for applications on gas pipeline rights-of-way

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

Sydelko, P.J.; Wilkey, P.L.

1992-01-01

Geographic information system (GIS) applications for the siting and monitoring of gas pipeline rights-of-way (ROWS) were developed for areas near Rio Vista, California. The data layers developed for this project represent geographic features, such as landcover, elevation, aspect, slope, soils, hydrography, transportation, endangered species, wetlands, and public line surveys. A GIS was used to develop and store spatial data from several sources; to manipulate spatial data to evaluate environmental and engineering issues associated with the siting, permitting, construction, maintenance, and monitoring of gas pipeline ROWS; and to graphically display analysis results. Examples of these applications include (1) determination of environmentallymore » sensitive areas, such as endangered species habitat, wetlands, and areas of highly erosive soils; (2) evaluation of engineering constraints, including shallow depth to bedrock, major hydrographic features, and shallow water table; (3) classification of satellite imagery for landuse/landcover that will affect ROWS; and (4) identification of alternative ROW corridors that avoid environmentally sensitive areas or areas with severe engineering constraints.« less

An application of Landsat and computer technology to potential water pollution from soil erosion

NASA Technical Reports Server (NTRS)

Campbell, W. J.

1981-01-01

Agricultural activity has been recognized as the primary source of nonpoint source water pollution. Water quality planners have needed information that is timely, accurate, easily reproducible, and relatively inexpensive to utilize to implement 'Best Management Practices' for water quality. In this paper, a case study shows how the combination of satellite data, which can give accurate land-cover/land-use information, and a computerized geographic information system, can assess nonpoint pollution at a regional scale and be cost effective.

Mapping soil texture targeting predefined depth range or synthetizing from standard layers?

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Dezső Kaposi, András; Szatmári, Gábor; Takács, Katalin; Pásztor, László

2017-04-01

There are increasing demands nowadays on spatial soil information in order to support environmental related and land use management decisions. Physical soil properties, especially particle size distribution play important role in this context. A few of the requirements can be satisfied by the sand-, silt-, and clay content maps compiled according to global standards such as GlobalSoilMap (GSM) or Soil Grids. Soil texture classes (e. g. according to USDA classification) can be derived from these three fraction data, in this way texture map can be compiled based on the proper separate maps. Soil texture class as well as fraction information represent direct input of crop-, meteorological- and hydrological models. The model inputs frequently require maps representing soil features of 0-30 cm depth, which is covered by three consecutive depth intervals according to standard specifications: 0-5 cm, 5-15 cm, 15-30 cm. Becoming GSM and SoilGrids the most detailed freely available spatial soil data sources, the common model users (e. g. meteorologists, agronomists, or hydrologists) would produce input map from (the weighted mean of) these three layers. However, if the basic soil data and proper knowledge is obtainable, a soil texture map targeting directly the 0-30 cm layer could be independently compiled. In our work we compared Hungary's soil texture maps compiled using the same reference and auxiliary data and inference methods but for differing layer distribution. We produced the 0-30 cm clay, silt and sand map as well as the maps for the three standard layers (0-5 cm, 5-15 cm, 15-30 cm). Maps of sand, silt and clay percentage were computed through regression kriging (RK) applying Additive Log-Ratio (alr) transformation. In addition to the Hungarian Soil Information and Monitoring System as reference soil data, digital elevation model and its derived components, soil physical property maps, remotely sensed images, land use -, geological-, as well as meteorological data were applied as auxiliary variables. We compared the directly compiled and the synthetized clay-, sand content, and texture class maps by different tools. In addition to pairwise comparison of basic statistical features (histograms, scatter plots), we examined the spatial distribution of the differences. We quantified the taxonomical distances of the textural classes, in order to investigate the differences of the map-pairs. We concluded that the directly computed and the synthetized maps show various differences. In the case of clay-, and sand content maps, the map-pairs have to be considered statistically different. On the other hand, the differences of the texture class maps are not significant. However, in all cases, the differences rather concern the extreme ranges and categories. Using of synthetized maps can intensify extremities by error propagation in models and scenarios. Based on our results, we suggest the usage of the directly composed maps.

Using satellite image data to estimate soil moisture

NASA Astrophysics Data System (ADS)

Chuang, Chi-Hung; Yu, Hwa-Lung

2017-04-01

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

The role of soil communities in improving ecosystem services in organic farming

NASA Astrophysics Data System (ADS)

Zandbergen, Jelmer; Koorneef, Guusje; Veen, Cees; Schrama, Jan; van der Putten, Wim

2017-04-01

Worldwide soil fertility decreases and it is generally believed that organic matter (OM) addition to agricultural soils can improve soil properties leading to beneficial ecosystem services. However, it remains unknown under which conditions and how fast biotic, physical and chemical soil properties respond to varying quality and quantity of OM inputs. Therefore, the aims of this research project are (1) to unravel biotic, physical and chemical responses of soils to varying quantity and quality of OM addition; and (2) to understand how we can accelerate the response of soils in order to improve beneficial soil ecosystem services faster. The first step in our research project is to determine how small-scale spatio-temporal patterns in soil biotic, physical and chemical properties relate to crop production and quality. To do this we combine field measurements on soil properties with remote and proximate sensing measures on crop development and yield in a long-term farming systems experiment in the Netherlands (Vredepeel). We hypothesize that spatio-temporal variation in crop development and yield are strongly related to spatio-temporal variation in soil parameters. In the second step of our project we will use this information to identify biological interactions underlying improving soil functions in response to OM addition over time. We will specifically focus on the role of soil communities in driving nutrient cycling, disease suppression and the formation of soil structure, all crucial elements of key soil services in agricultural soils. The knowledge that will be generated in our project can be used to detect specific organic matter qualities that support the underlying ecological processes to accelerate the transition towards improved soil functioning thereby governing enhanced crop yields.

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

NASA Technical Reports Server (NTRS)

Bolten, John D.; Mladenova, Iliana E.; Crow, Wade; De Jeu, Richard

2016-01-01

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

[The design and implementation of the web typical surface object spectral information system in arid areas based on .NET and SuperMap].

PubMed

Xia, Jun; Tashpolat, Tiyip; Zhang, Fei; Ji, Hong-jiang

2011-07-01

The characteristic of object spectrum is not only the base of the quantification analysis of remote sensing, but also the main content of the basic research of remote sensing. The typical surface object spectral database in arid areas oasis is of great significance for applied research on remote sensing in soil salinization. In the present paper, the authors took the Ugan-Kuqa River Delta Oasis as an example, unified .NET and the SuperMap platform with SQL Server database stored data, used the B/S pattern and the C# language to design and develop the typical surface object spectral information system, and established the typical surface object spectral database according to the characteristics of arid areas oasis. The system implemented the classified storage and the management of typical surface object spectral information and the related attribute data of the study areas; this system also implemented visualized two-way query between the maps and attribute data, the drawings of the surface object spectral response curves and the processing of the derivative spectral data and its drawings. In addition, the system initially possessed a simple spectral data mining and analysis capabilities, and this advantage provided an efficient, reliable and convenient data management and application platform for the Ugan-Kuqa River Delta Oasis's follow-up study in soil salinization. Finally, It's easy to maintain, convinient for secondary development and practically operating in good condition.

Facing policy challenges with inter- and transdisciplinary soil research focused on the UN Sustainable Development Goals

NASA Astrophysics Data System (ADS)

Bouma, Johan; Montanarella, Luca

2016-04-01

Our current information society, populated by increasingly well-informed and critical stakeholders, presents a challenge to both the policy and science arenas. The introduction of the UN Sustainable Development Goals (SDGs) offers a unique and welcome opportunity to direct joint activities towards these goals. Soil science, even though it is not mentioned as such, plays an important role in realizing a number of SDGs focusing on food, water, climate, health, biodiversity, and sustainable land use. A plea is made for a systems approach to land use studies, to be initiated by soil scientists, in which these land-related SDGs are considered in an integrated manner. To connect with policy makers and stakeholders, two approaches are functional. The first of these is the policy cycle when planning and executing research, which includes signaling, design, decision making, implementation, and evaluation. Many current research projects spend little time on signaling, which may lead to disengagement of stakeholders. Also, implementation is often seen as the responsibility of others, while it is crucial to demonstrate - if successful - the relevance of soil science. The second approach is the DPSIR approach when following the policy cycle in land-related research, distinguishing external drivers, pressures, impact, and responses to land use change that affect the state of the land in the past, present, and future. Soil science cannot by itself realize SDGs, and interdisciplinary studies on ecosystem services (ESs) provide an appropriate channel to define contributions of soil science in terms of the seven soil functions. ESs, in turn, can contribute to addressing the six SDGs (2, 3, 6, 12, 13, and 15) with an environmental, land-related character. SDGs have a societal focus and future soil science research can only be successful if stakeholders are part of the research effort in transdisciplinary projects, based on the principle of time-consuming "joint learning". The internal organization of the soil science discipline is not yet well tuned to the needs of inter- and transdisciplinary approaches.

Spatial modeling of biological soil crusts to support rangeland assessment and monitoring

USGS Publications Warehouse

Bowker, M.A.; Belnap, J.; Miller, M.E.

2006-01-01

Biological soil crusts are a diverse soil surface community, prevalent in semiarid regions, which function as ecosystem engineers and perform numerous important ecosystem services. Loss of crusts has been implicated as a factor leading to accelerated soil erosion and other forms of land degradation. To support assessment and monitoring efforts aimed at ensuring the sustainability of rangeland ecosystems, managers require spatially explicit information concerning potential cover and composition of biological soil crusts. We sampled low disturbance sites in Grand Staircase-Escalante National Monument (Utah, USA) to determine the feasibility of modeling the potential cover and composition of biological soil crusts in a large area. We used classification and regression trees to model cover of four crust types (light cyanobacterial, dark cyanobacterial, moss, lichen) and 1 cyanobacterial biomass proxy (chlorophyll a), based upon a parsimonious set of GIS (Geographic Information Systems) data layers (soil types, precipitation, and elevation). Soil type was consistently the best predictor, although elevation and precipitation were both invoked in the various models. Predicted and observed values for the dark cyanobacterial, moss, and lichen models corresponded moderately well (R 2 = 0.49, 0.64, 0.55, respectively). Cover of late successional crust elements (moss + lichen + dark cyanobacterial) was also successfully modeled (R2 = 0.64). We were less successful with models of light cyanobacterial cover (R2 = 0.22) and chlorophyll a (R2 = 0.09). We believe that our difficulty modeling chlorophyll a concentration is related to a severe drought and subsequent cyanobacterial mortality during the course of the study. These models provide the necessary reference conditions to facilitate the comparison between the actual cover and composition of biological soil crusts at a given site and their potential cover and composition condition so that sites in poor condition can be identified and management actions can be taken.

A long-term soil structure observatory for post-compaction soil structure evolution: design and initial soil structure recovery observations

NASA Astrophysics Data System (ADS)

Keller, Thomas; Colombi, Tino; Ruiz, Siul; Grahm, Lina; Reiser, René; Rek, Jan; Oberholzer, Hans-Rudolf; Schymanski, Stanislaus; Walter, Achim; Or, Dani

2016-04-01

Soil compaction due to agricultural vehicular traffic alters the geometrical arrangement of soil constituents, thereby modifying mechanical properties and pore spaces that affect a range of soil hydro-ecological functions. The ecological and economic costs of soil compaction are dependent on the immediate impact on soil functions during the compaction event, and a function of the recovery time. In contrast to a wealth of soil compaction information, mechanisms and rates of soil structure recovery remain largely unknown. A long-term (>10-yr) soil structure observatory (SSO) was established in 2014 on a loamy soil in Zurich, Switzerland, to quantify rates and mechanisms of structure recovery of compacted arable soil under different post-compaction management treatments. We implemented three initial compaction treatments (using a two-axle agricultural vehicle with 8 Mg wheel load): compaction of the entire plot area (i.e. track-by-track), compaction in wheel tracks, and no compaction. After compaction, we implemented four post-compaction soil management systems: bare soil (BS), permanent grass (PG), crop rotation without mechanical loosening (NT), and crop rotation under conventional tillage (CT). BS and PG provide insights into uninterrupted natural processes of soil structure regeneration under reduced (BS) and normal biological activity (PG). The two cropping systems (NT and CT) enable insights into soil structure recovery under common agricultural practices with minimal (NT) and conventional mechanical soil disturbance (CT). Observations include periodic sampling and measurements of soil physical properties, earthworm abundance, crop measures, electrical resistivity and ground penetrating radar imaging, and continuous monitoring of state variables - soil moisture, temperature, CO2 and O2 concentrations, redox potential and oxygen diffusion rates - for which a network of sensors was installed at various depths (0-1 m). Initial compaction increased soil bulk density to about half a metre, decreased gas and water transport functions (air permeability, gas diffusivity, saturated hydraulic conductivity), and increased mechanical impedance. Water infiltration at the soil surface was initially reduced by three orders of magnitude, but significantly recovered within a year. However, within the soil profile, recovery of transport properties is much smaller. Air permeability tended to recover more than gas diffusivity, suggesting that initial post-compaction recovery is initiated by new macropores (e.g. biopores). Tillage recovered topsoil bulk density but not topsoil transport functions. Compaction changed grass species composition in PG, and significantly reduced grass biomass in PG and crop yields in NT and CT.

Taxonomic classification of soils using digital information from LANDSAT data. Huayllamarca and eucaliptus areas. M.S. Thesis - Bolivia Univ.

NASA Technical Reports Server (NTRS)

Quiroga, S. Q.

1977-01-01

The applicability of LANDSAT digital information to soil mapping is described. A compilation of all cartographic information and bibliography of the study area is made. LANDSAT MSS images on a scale of 1:250,000 are interpreted and a physiographic map with legend is prepared. The study area is inspected and a selection of the sample areas is made. A digital map of the different soil units is produced and the computer mapping units are checked against the soil units encountered in the field. The soil boundaries obtained by automatic mapping were not substantially changed by field work. The accuracy of the automatic mapping is rather high.

Monitoring the Global Soil Moisture Climatology Using GLDAS/LIS

NASA Astrophysics Data System (ADS)

Meng, J.; Mitchell, K.; Wei, H.; Gottschalck, J.

2006-05-01

Soil moisture plays a crucial role in the terrestrial water cycle through governing the process of partitioning precipitation among infiltration, runoff and evaporation. Accurate assessment of soil moisture and other land states, namely, soil temperature, snowpack, and vegetation, is critical in numerical environmental prediction systems because of their regulation of surface water and energy fluxes between the surface and atmosphere over a variety of spatial and temporal scales. The Global Land Data Assimilation System (GLDAS) is developed, jointly by NASA Goddard Space Flight Center (GSFC) and NOAA National Centers for Environmental Prediction (NCEP), to perform high-quality global land surface simulation using state-of-art land surface models and further minimizing the errors of simulation by constraining the models with observation- based precipitation, and satellite land data assimilation techniques. The GLDAS-based Land Information System (LIS) infrastructure has been installed on the NCEP supercomputer that serves the operational weather and climate prediction systems. In this experiment, the Noah land surface model is offline executed within the GLDAS/LIS infrastructure, driven by the NCEP Global Reanalysis-2 (GR2) and the CPC Merged Analysis of Precipitation (CMAP). We use the same Noah code that is coupled to the operational NCEP Global Forecast System (GFS) for weather prediction and test bed versions of the NCEP Climate Forecast System (CFS) for seasonal prediction. For assessment, it is crucial that this uncoupled GLDAS/Noah uses exactly the same Noah code (and soil and vegetation parameters therein), and executes with the same horizontal grid, landmask, terrain field, soil and vegetation types, seasonal cycle of green vegetation fraction and surface albedo as in the coupled GFS/Noah and CFS/Noah. This execution is for the 25-year period of 1980-2005, starting with a pre-execution 10-year spin-up. This 25-year GLDAS/Noah global land climatology will be used for both climate variability assessment and as a source of land initial conditions for ensemble CFS/Noah seasonal hindcast experiments. Finally, this GLDAS/Noah climatology will serve as the foundation for a global drought/flood monitoring system that includes near realtime daily updates of the global land states.

DOSoReMI.hu: collection of countrywide DSM products partly according to GSM.net specifications, partly driven by specific user demands

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor; Illés, Gábor; Bakacsi, Zsófia; Szabó, József

2017-04-01

Due to former soil surveys and mapping activities significant amount of soil information has accumulated in Hungary. In traditional soil mapping the creation of a new map was troublesome and laborious. As a consequence, robust maps were elaborated and rather the demands were fitted to the available map products. Until recently spatial soil information demands have been serviced with the available datasets either in their actual form or after certain specific and often enforced, thematic and spatial inference. Considerable imperfection may occur in the accuracy and reliability of the map products, since there might be significant discrepancies between the available data and the expected information. The DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project was started intentionally for the renewal of the national soil spatial infrastructure in Hungary. During our activities we have significantly extended the potential, how soil information requirements could be satisfied. Soil property, soil type as well as functional soil maps were targeted. The set of the applied digital soil mapping techniques has been gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. Soil property maps have been compiled partly according to GSM.net specifications, partly by slightly or more strictly changing some of their predefined parameters (depth intervals, pixel size, property etc.) according to the specific demands on the final products. The elaborated primary maps were further processed, since even DOSoReMI.hu intended to take steps for the regionalization of higher level soil information (processes, functions, and services) involving crop models in the spatial modelling. The framework of DOSoReMI.hu also provides opportunity for the elaboration of goal specific soil maps, with the prescription of the parameters (thematic, resolution, accuracy, reliability etc.) characterizing the map product. As a result, unique digital soil map products (in a more general meaning) were elaborated regionalizing specific soil (related) features, which were never mapped before, even nationally with high ( 1 ha) spatial resolution. Based upon the collected experiences, the full range of GSM.net products were also targeted. The web publishing of the results was also elaborated creating a proper WMS environment. Our paper will present the resulted national maps furthermore some conclusions drawn from the experiences.] Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA) under Grant K105167 and AGRARKLÍMA.2 VKSZ_12-1-2013-0034.

Local Soils Information Needed to Define the Root Zone in Process Models on the Gulf Coastal Plain

Treesearch

Mary Anne Sword Sayer; Allan E. Tiarks

2002-01-01

We combined published information and our own experimental results from the Gulf Coastal Plain to evaluate how soil aeration and strength interact with loblolly pine root growth. Our results demonstrate that soil aeration and strength differ by soil series and year and are subject to vertical and horizontal spatial variation. Comparison of loblolly pine root phenology...

Ecological site-based assessments of wind and water erosion: informing accelerated soil erosion management in rangelands

USGS Publications Warehouse

Webb, Nicholas P.; Herrick, Jeffrey E.; Duniway, Michael C.

2014-01-01

Accelerated soil erosion occurs when anthropogenic processes modify soil, vegetation or climatic conditions causing erosion rates at a location to exceed their natural variability. Identifying where and when accelerated erosion occurs is a critical first step toward its effective management. Here we explore how erosion assessments structured in the context of ecological sites (a land classification based on soils, landscape setting and ecological potential) and their vegetation states (plant assemblages that may change due to management) can inform systems for reducing accelerated soil erosion in rangelands. We evaluated aeolian horizontal sediment flux and fluvial sediment erosion rates for five ecological sites in southern New Mexico, USA, using monitoring data and rangeland-specific wind and water erosion models. Across the ecological sites, plots in shrub-encroached and shrub-dominated vegetation states were consistently susceptible to aeolian sediment flux and fluvial sediment erosion. Both processes were found to be highly variable for grassland and grass-succulent states across the ecological sites at the plot scale (0.25 Ha). We identify vegetation thresholds that define cover levels below which rapid (exponential) increases in aeolian sediment flux and fluvial sediment erosion occur across the ecological sites and vegetation states. Aeolian sediment flux and fluvial erosion in the study area can be effectively controlled when bare ground cover is 100 cm in length is less than ~35%. Land use and management activities that alter cover levels such that they cross thresholds, and/or drive vegetation state changes, may increase the susceptibility of areas to erosion. Land use impacts that are constrained within the range of natural variability should not result in accelerated soil erosion. Evaluating land condition against the erosion thresholds identified here will enable identification of areas susceptible to accelerated soil erosion and the development of practical management solutions.

Mapping soil heterogeneity using RapidEye satellite images

NASA Astrophysics Data System (ADS)

Piccard, Isabelle; Eerens, Herman; Dong, Qinghan; Gobin, Anne; Goffart, Jean-Pierre; Curnel, Yannick; Planchon, Viviane

2016-04-01

In the frame of BELCAM, a project funded by the Belgian Science Policy Office (BELSPO), researchers from UCL, ULg, CRA-W and VITO aim to set up a collaborative system to develop and deliver relevant information for agricultural monitoring in Belgium. The main objective is to develop remote sensing methods and processing chains able to ingest crowd sourcing data, provided by farmers or associated partners, and to deliver in return relevant and up-to-date information for crop monitoring at the field and district level based on Sentinel-1 and -2 satellite imagery. One of the developments within BELCAM concerns an automatic procedure to detect soil heterogeneity within a parcel using optical high resolution images. Such heterogeneity maps can be used to adjust farming practices according to the detected heterogeneity. This heterogeneity may for instance be caused by differences in mineral composition of the soil, organic matter content, soil moisture or soil texture. Local differences in plant growth may be indicative for differences in soil characteristics. As such remote sensing derived vegetation indices may be used to reveal soil heterogeneity. VITO started to delineate homogeneous zones within parcels by analyzing a series of RapidEye images acquired in 2015 (as a precursor for Sentinel-2). Both unsupervised classification (ISODATA, K-means) and segmentation techniques were tested. Heterogeneity maps were generated from images acquired at different moments during the season (13 May, 30 June, 17 July, 31 August, 11 September and 1 November 2015). Tests were performed using blue, green, red, red edge and NIR reflectances separately and using derived indices such as NDVI, fAPAR, CIrededge, NDRE2. The results for selected winter wheat, maize and potato fields were evaluated together with experts from the collaborating agricultural research centers. For a few fields UAV images and/or yield measurements were available for comparison.

Identification and Simulation of Subsurface Soil patterns using hidden Markov random fields and remote sensing and geophysical EMI data sets

NASA Astrophysics Data System (ADS)

Wang, Hui; Wellmann, Florian; Verweij, Elizabeth; von Hebel, Christian; van der Kruk, Jan

2017-04-01

Lateral and vertical spatial heterogeneity of subsurface properties such as soil texture and structure influences the available water and resource supply for crop growth. High-resolution mapping of subsurface structures using non-invasive geo-referenced geophysical measurements, like electromagnetic induction (EMI), enables a characterization of 3D soil structures, which have shown correlations to remote sensing information of the crop states. The benefit of EMI is that it can return 3D subsurface information, however the spatial dimensions are limited due to the labor intensive measurement procedure. Although active and passive sensors mounted on air- or space-borne platforms return 2D images, they have much larger spatial dimensions. Combining both approaches provides us with a potential pathway to extend the detailed 3D geophysical information to a larger area by using remote sensing information. In this study, we aim at extracting and providing insights into the spatial and statistical correlation of the geophysical and remote sensing observations of the soil/vegetation continuum system. To this end, two key points need to be addressed: 1) how to detect and recognize the geometric patterns (i.e., spatial heterogeneity) from multiple data sets, and 2) how to quantitatively describe the statistical correlation between remote sensing information and geophysical measurements. In the current study, the spatial domain is restricted to shallow depths up to 3 meters, and the geostatistical database contains normalized difference vegetation index (NDVI) derived from RapidEye satellite images and apparent electrical conductivities (ECa) measured from multi-receiver EMI sensors for nine depths of exploration ranging from 0-2.7 m. The integrated data sets are mapped into both the physical space (i.e. the spatial domain) and feature space (i.e. a two-dimensional space framed by the NDVI and the ECa data). Hidden Markov Random Fields (HMRF) are employed to model the underlying heterogeneities in spatial domain and finite Gaussian mixture models are adopted to quantitatively describe the statistical patterns in terms of center vectors and covariance matrices in feature space. A recently developed parallel stochastic clustering algorithm is adopted to implement the HMRF models and the Markov chain Monte Carlo based Bayesian inference. Certain spatial patterns such as buried paleo-river channels covered by shallow sediments are investigated as typical examples. The results indicate that the geometric patterns of the subsurface heterogeneity can be represented and quantitatively characterized by HMRF. Furthermore, the statistical patterns of the NDVI and the EMI data from the soil/vegetation-continuum system can be inferred and analyzed in a quantitative manner.

A multi-level assessment methodology for determining the potential for groundwater contamination by pesticides.

PubMed

Crowe, A S; Booty, W G

1995-05-01

A multi-level pesticide assessment methodology has been developed to permit regulatory personnel to undertake a variety of assessments on the potential for pesticide used in agricultural areas to contaminate the groundwater regime at an increasingly detailed geographical scale of investigation. A multi-level approach accounts for a variety of assessment objectives and detail required in the assessment, the restrictions on the availability and accuracy of data, the time available to undertake the assessment, and the expertise of the decision maker. The level 1: regional scale is designed to prioritize districts having a potentially high risk for groundwater contamination from the application of a specific pesticide for a particular crop. The level 2: local scale is used to identify critical areas for groundwater contamination, at a soil polygon scale, within a district. A level 3: soil profile scale allows the user to evaluate specific factors influencing pesticide leaching and persistence, and to determine the extent and timing of leaching, through the simulation of the migration of a pesticide within a soil profile. Because of the scale of investigation, limited amount of data required, and qualitative nature of the assessment results, the level 1 and level 2 assessment are designed primarily for quick and broad guidance related to management practices. A level 3 assessment is more complex, requires considerably more data and expertise on the part of the user, and hence is designed to verify the potential for contamination identified during the level 1 or 2 assessment. The system combines environmental modelling, geographical information systems, extensive databases, data management systems, expert systems, and pesticide assessment models, to form an environmental information system for assessing the potential for pesticides to contaminate groundwater.

Soil moisture monitoring in Candelaro basin, Southern Italy

NASA Astrophysics Data System (ADS)

Campana, C.; Gigante, V.; Iacobellis, V.

2012-04-01

The signature of the hydrologic regime can be investigated, in principle, by recognizing the main mechanisms of runoff generation that take place in the basin and affect the seasonal behavior or the rainfall-driven events. In this framework, besides the implementation of hydrological models, a crucial role should be played by direct observation of key state variables such as soil moisture at different depths and different distances from the river network. In fact, understanding hydrological systems is often limited by the frequency and spatial distribution of observations. Experimental catchments, which are field laboratories with long-term measurements of hydrological variables, are not only sources of data but also sources of knowledge. Wireless distributed sensing platforms are a key technology to address the need for overcoming field limitations such as conflicts between soil use and cable connections. A stand-alone wireless network system has been installed for continuous monitoring of soil water contents at multiple depths along a transect located in Celone basin (sub-basin of Candelaro basin in Puglia, Southern Italy). The transect consists of five verticals, each one having three soil water content sensors at multiple depths: 0,05 m, 0,6 m and 1,2 m below the ground level. The total length of the transect is 307 m and the average distance between the verticals is 77 m. The main elements of the instrumental system installed are: fifteen Decagon 10HS Soil Moisture Sensors, five Decagon Em50R Wireless Radio Data Loggers, one Rain gauge, one Decagon Data Station and one Campbell CR1000 Data Logger. Main advantages of the system as described and presented in this work are that installation of the wireless network system is fast and easy to use, data retrieval and monitoring information over large spatial scales can be obtained in (near) real-time mode and finally other type of sensors can be connected to the system, also offering wide potentials for future applications. First records of the wireless underground network system indicate the presence of interesting patterns in space-time variability of volumetric soil moisture content, that provide evidence of the combined process of vertical infiltration and lateral flow. ACKNOWLEDGEMENT The research in this work is supported by the MIRAGE FP7 project (Grant agreement n. 211732).

The Unified North American Soil Map and its implication on the soil organic carbon stock in North America

NASA Astrophysics Data System (ADS)

Liu, S.; Wei, Y.; Post, W. M.; Cook, R. B.; Schaefer, K.; Thornton, M. M.

2012-10-01

The Unified North American Soil Map (UNASM) was developed 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 with the Harmonized World Soil Database version 1.1 (HWSD1.1). 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 top soil layer (0-30 cm) and the sub soil layer (30-100 cm) respectively, of the spatial resolution of 0.25° 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 347.70 Pg, of which 24.7% is under trees, 14.2% is under shrubs, and 1.3% is under grasses and 3.8% under crops. This UNASM data will provide a resource for use in land surface and terrestrial biogeochemistry modeling both for input of soil characteristics and for benchmarking model output.

Resampling soil profiles can constrain large-scale changes in the C cycle: obtaining robust information from radiocarbon measurements

NASA Astrophysics Data System (ADS)

Baisden, W. T.; Prior, C.; Lambie, S.; Tate, K.; Bruhn, F.; Parfitt, R.; Schipper, L.; Wilde, R. H.; Ross, C.

2006-12-01

Soil organic matter contains more C than terrestrial biomass and atmospheric CO2 combined, and reacts to climate and land-use change on timescales requiring long-term experiments or monitoring. The direction and uncertainty of soil C stock changes has been difficult to predict and incorporate in decision support tools for climate change policies. Moreover, standardization of approaches has been difficult because historic methods of soil sampling have varied regionally, nationally and temporally. The most common and uniform type of historic sampling is soil profiles, which have commonly been collected, described and archived in the course of both soil survey studies and research. Resampling soil profiles has considerable utility in carbon monitoring and in parameterizing models to understand the ecosystem responses to global change. Recent work spanning seven soil orders in New Zealand's grazed pastures has shown that, averaged over approximately 20 years, 31 soil profiles lost 106 g C m-2 y-1 (p=0.01) and 9.1 g N m{^-2} y-1 (p=0.002). These losses are unexpected and appear to extend well below the upper 30 cm of soil. Following on these recent results, additional advantages of resampling soil profiles can be emphasized. One of the most powerful applications afforded by resampling archived soils is the use of the pulse label of radiocarbon injected into the atmosphere by thermonuclear weapons testing circa 1963 as a tracer of soil carbon dynamics. This approach allows estimation of the proportion of soil C that is `passive' or `inert' and therefore unlikely to respond to global change. Evaluation of resampled soil horizons in a New Zealand soil chronosequence confirms that the approach yields consistent values for the proportion of `passive' soil C, reaching 25% of surface horizon soil C over 12,000 years. Across whole profiles, radiocarbon data suggest that the proportion of `passive' C in New Zealand grassland soil can be less than 40% of total soil C. Below 30 cm, 1 kg C m-2 or more may be reactive on decadal timescales, supporting evidence of soil C losses from throughout the soil profiles. Information from resampled soil profiles can be combined with additional contemporary measurements to test hypotheses about mechanisms for soil C changes. For example, Δ14C in excess of 200‰ in water extractable dissolved organic C (DOC) from surface soil horizons supports the hypothesis that decadal movement of DOC represents an important translocation of soil C. These preliminary results demonstrate that resampling whole soil profiles can support substantial progress in C cycle science, ranging from updating operational C accounting systems to the frontiers of research. Resampling can be complementary or superior to fixed-depth interval sampling of surface soil layers. Resampling must however be undertaken with relative urgency to maximize the potential interpretive power of bomb-derived radiocarbon.

Investigation of remote sensing techniques of measuring soil moisture

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator); Blanchard, A. J.; Nieber, J. L.; Lascano, R.; Tsang, L.; Vanbavel, C. H. M.

1981-01-01

Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

Phthalate esters in soil, plastic film, and vegetable from greenhouse vegetable production bases in Beijing, China: Concentrations, sources, and risk assessment.

PubMed

Li, Cheng; Chen, Jiayi; Wang, Jihua; Han, Ping; Luan, Yunxia; Ma, Xupu; Lu, Anxiang

2016-10-15

The increased use of plastic film in greenhouse vegetable production (GVP) could result in phthalate ester (PAE) contamination in vegetables. However, limited information is currently available on their occurrence and associated potential risks in GVP systems. The present study documents the occurrence and composition of 15 PAEs in soil, plastic film, and vegetable samples from eight large-scale GVP bases in Beijing, China. Results showed that PAEs are ubiquitous contaminants in these GVP bases. Total PAE concentrations ranged from 0.14 to 2.13mg/kg (mean 0.99mg/kg) in soils and from 0.15 to 6.94mg/kg (mean 1.49mg/kg) in vegetables. Di (2-ethylhexyl) phthalate, di-n-butyl phthalate, and diisobutyl phthalate were the most abundant components, which accounted for >90% of the total PAEs. This investigation also indicated that the widespread application of plastic film in GVP systems may be the primary source of these PAEs. The non-cancer and carcinogenic risks of target PAEs were estimated based on the exposures of vegetable intake. The hazard quotients of PAE in all vegetable samples were lower than 1 and the carcinogenic risks were also at acceptable levels for consumers. The data in this study can provide valuable information to understand the status of potential pollutants, specifically PAEs, in GVP systems. Copyright © 2016 Elsevier B.V. All rights reserved.