Assessing NIR & MIR Spectral Analysis as a Method for Soil C Estimation Across a Network of Sampling Sites

NASA Astrophysics Data System (ADS)

Spencer, S.; Ogle, S.; Borch, T.; Rock, B.

2008-12-01

Monitoring soil C stocks is critical to assess the impact of future climate and land use change on carbon sinks and sources in agricultural lands. A benchmark network for soil carbon monitoring of stock changes is being designed for US agricultural lands with 3000-5000 sites anticipated and re-sampling on a 5- to10-year basis. Approximately 1000 sites would be sampled per year producing around 15,000 soil samples to be processed for total, organic, and inorganic carbon, as well as bulk density and nitrogen. Laboratory processing of soil samples is cost and time intensive, therefore we are testing the efficacy of using near-infrared (NIR) and mid-infrared (MIR) spectral methods for estimating soil carbon. As part of an initial implementation of national soil carbon monitoring, we collected over 1800 soil samples from 45 cropland sites in the mid-continental region of the U.S. Samples were processed using standard laboratory methods to determine the variables above. Carbon and nitrogen were determined by dry combustion and inorganic carbon was estimated with an acid-pressure test. 600 samples are being scanned using a bench- top NIR reflectance spectrometer (30 g of 2 mm oven-dried soil and 30 g of 8 mm air-dried soil) and 500 samples using a MIR Fourier-Transform Infrared Spectrometer (FTIR) with a DRIFT reflectance accessory (0.2 g oven-dried ground soil). Lab-measured carbon will be compared to spectrally-estimated carbon contents using Partial Least Squares (PLS) multivariate statistical approach. PLS attempts to develop a soil C predictive model that can then be used to estimate C in soil samples not lab-processed. The spectral analysis of soil samples either whole or partially processed can potentially save both funding resources and time to process samples. This is particularly relevant for the implementation of a national monitoring network for soil carbon. This poster will discuss our methods, initial results and potential for using NIR and MIR spectral approaches to either replace or augment traditional lab-based carbon analyses of soils.

Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron

2016-02-01

Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the globe, this study may have important applications in aiding water resources management in different regions.

The Raam regional soil moisture monitoring network in the Netherlands

NASA Astrophysics Data System (ADS)

Benninga, Harm-Jan F.; Carranza, Coleen D. U.; Pezij, Michiel; van Santen, Pim; van der Ploeg, Martine J.; Augustijn, Denie C. M.; van der Velde, Rogier

2018-01-01

We have established a soil moisture profile monitoring network in the Raam region in the Netherlands. This region faces water shortages during summers and excess of water during winters and after extreme precipitation events. Water management can benefit from reliable information on the soil water availability and water storing capacity in the unsaturated zone. In situ measurements provide a direct source of information on which water managers can base their decisions. Moreover, these measurements are commonly used as a reference for the calibration and validation of soil moisture content products derived from earth observations or obtained by model simulations. Distributed over the Raam region, we have equipped 14 agricultural fields and 1 natural grass field with soil moisture and soil temperature monitoring instrumentation, consisting of Decagon 5TM sensors installed at depths of 5, 10, 20, 40 and 80 cm. In total, 12 stations are located within the Raam catchment (catchment area of 223 km2), and 5 of these stations are located within the closed sub-catchment Hooge Raam (catchment area of 41 km2). Soil-specific calibration functions that have been developed for the 5TM sensors under laboratory conditions lead to an accuracy of 0.02 m3 m-3. The first set of measurements has been retrieved for the period 5 April 2016-4 April 2017. In this paper, we describe the Raam monitoring network and instrumentation, the soil-specific calibration of the sensors, the first year of measurements, and additional measurements (soil temperature, phreatic groundwater levels and meteorological data) and information (elevation, soil physical characteristics, land cover and a geohydrological model) available for performing scientific research. The data are available at https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56.

A Networked Sensor System for the Analysis of Plot-Scale Hydrology.

PubMed

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W; Navarro, Miguel; Li, Yimei; Slater, Thomas A; Liang, Yao; Liang, Xu

2017-03-20

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments.

A Networked Sensor System for the Analysis of Plot-Scale Hydrology

PubMed Central

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W.; Navarro, Miguel; Li, Yimei; Slater, Thomas A.; Liang, Yao; Liang, Xu

2017-01-01

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments. PMID:28335534

Multi-scale soil moisture model calibration and validation: An ARS Watershed on the South Fork of the Iowa River

USDA-ARS?s Scientific Manuscript database

Soil moisture monitoring with in situ technology is a time consuming and costly endeavor for which a method of increasing the resolution of spatial estimates across in situ networks is necessary. Using a simple hydrologic model, the resolution of an in situ watershed network can be increased beyond...

Mobile Wireless Sensor Networks for Advanced Soil Sensing and Ecosystem Monitoring

NASA Astrophysics Data System (ADS)

Mollenhauer, Hannes; Schima, Robert; Remmler, Paul; Mollenhauer, Olaf; Hutschenreuther, Tino; Toepfer, Hannes; Dietrich, Peter; Bumberger, Jan

2015-04-01

For an adequate characterization of ecosystems it is necessary to detect individual processes with suitable monitoring strategies and methods. Due to the natural complexity of all environmental compartments, single point or temporally and spatially fixed measurements are mostly insufficient for an adequate representation. The application of mobile wireless sensor networks for soil and atmosphere sensing offers significant benefits, due to the simple adjustment of the sensor distribution, the sensor types and the sample rate (e.g. by using optimization approaches or event triggering modes) to the local test conditions. This can be essential for the monitoring of heterogeneous and dynamic environmental systems and processes. One significant advantage in the application of mobile ad-hoc wireless sensor networks is their self-organizing behavior. Thus, the network autonomously initializes and optimizes itself. Due to the localization via satellite a major reduction in installation and operation costs and time is generated. In addition, single point measurements with a sensor are significantly improved by measuring at several optimized points continuously. Since performing analog and digital signal processing and computation in the sensor nodes close to the sensors a significant reduction of the data to be transmitted can be achieved which leads to a better energy management of nodes. Furthermore, the miniaturization of the nodes and energy harvesting are current topics under investigation. First results of field measurements are given to present the potentials and limitations of this application in environmental science. In particular, collected in-situ data with numerous specific soil and atmosphere parameters per sensor node (more than 25) recorded over several days illustrates the high performance of this system for advanced soil sensing and soil-atmosphere interaction monitoring. Moreover, investigations of biotic and abiotic process interactions and optimization of sensor positioning for measuring soil moisture are scopes of this work and initial results of these issues will be presented.

State of the Art in Large-Scale Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

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

Examining the Suitability of a Sparse In Situ Soil Moisture Monitoring Network for Assimilation into a Spatially Distributed Hydrologic Model

NASA Astrophysics Data System (ADS)

De Vleeschouwer, N.; Verhoest, N.; Pauwels, V. R. N.

2015-12-01

The continuous monitoring of soil moisture in a permanent network can yield an interesting data product for use in hydrological data assimilation. Major advantages of in situ observations compared to remote sensing products are the potential vertical extent of the measurements, the finer temporal resolution of the observation time series, the smaller impact of land cover variability on the observation bias, etc. However, two major disadvantages are the typical small integration volume of in situ measurements and the often large spacing between monitoring locations. This causes only a small part of the modelling domain to be directly observed. Furthermore, the spatial configuration of the monitoring network is typically temporally non-dynamic. Therefore two questions can be raised. Do spatially sparse in situ soil moisture observations contain a sufficient data representativeness to successfully assimilate them into the largely unobserved spatial extent of a distributed hydrological model? And if so, how is this assimilation best performed? Consequently two important factors that can influence the success of assimilating in situ monitored soil moisture are the spatial configuration of the monitoring network and the applied assimilation algorithm. In this research the influence of those factors is examined by means of synthetic data-assimilation experiments. The study area is the ± 100 km² catchment of the Bellebeek in Flanders, Belgium. The influence of the spatial configuration is examined by varying the amount of locations and their position in the landscape. The latter is performed using several techniques including temporal stability analysis and clustering. Furthermore the observation depth is considered by comparing assimilation of surface layer (5 cm) and deeper layer (50 cm) observations. The impact of the assimilation algorithm is assessed by comparing the performance obtained with two well-known algorithms: Newtonian nudging and the Ensemble Kalman Filter.

Scaling an in situ network for high resolution modeling during SMAPVEX15

NASA Astrophysics Data System (ADS)

Coopersmith, E. J.; Cosh, M. H.; Jacobs, J. M.; Jackson, T. J.; Crow, W. T.; Holifield Collins, C.; Goodrich, D. C.; Colliander, A.

2015-12-01

Among the greatest challenges within the field of soil moisture estimation is that of scaling sparse point measurements within a network to produce higher resolution map products. Large-scale field experiments present an ideal opportunity to develop methodologies for this scaling, by coupling in situ networks, temporary networks, and aerial mapping of soil moisture. During the Soil Moisture Active Passive Validation Experiments in 2015 (SMAPVEX15) in and around the USDA-ARS Walnut Gulch Experimental Watershed and LTAR site in southeastern Arizona, USA, a high density network of soil moisture stations was deployed across a sparse, permanent in situ network in coordination with intensive soil moisture sampling and an aircraft campaign. This watershed is also densely instrumented with precipitation gages (one gauge/0.57 km2) to monitor the North American Monsoon System, which dominates the hydrologic cycle during the summer months in this region. Using the precipitation and soil moisture time series values provided, a physically-based model is calibrated that will provide estimates at the 3km, 9km, and 36km scales. The results from this model will be compared with the point-scale gravimetric samples, aircraft-based sensor, and the satellite-based products retrieved from NASA's Soil Moisture Active Passive mission.

Scaling and calibration of a core validation site for the soil moisture active passive mission

USDA-ARS?s Scientific Manuscript database

The calibration and validation of soil moisture remote sensing products is complicated due to the logistics of installing a long term soil moisture monitoring network in an active landscape. It is more efficient to locate these stations along agricultural field boundaries, but unfortunately this oft...

Event-based estimation of water budget components using the network of multi-sensor capacitance probes

USDA-ARS?s Scientific Manuscript database

A time-scale-free approach was developed for estimation of water fluxes at boundaries of monitoring soil profile using water content time series. The approach uses the soil water budget to compute soil water budget components, i.e. surface-water excess (Sw), infiltration less evapotranspiration (I-E...

Monitoring Climate Variability and Change in Northern Alaska: Updates to the U.S. Geological Survey (USGS) Climate and Permafrost Monitoring Network

NASA Astrophysics Data System (ADS)

Urban, F. E.; Clow, G. D.; Meares, D. C.

2004-12-01

Observations of long-term climate and surficial geological processes are sparse in most of the Arctic, despite the fact that this region is highly sensitive to climate change. Instrumental networks that monitor the interplay of climatic variability and geological/cryospheric processes are a necessity for documenting and understanding climate change. Improvements to the spatial coverage and temporal scale of Arctic climate data are in progress. The USGS, in collaboration with The Bureau of Land Management (BLM) and The Fish and Wildlife Service (FWS) currently maintains two types of monitoring networks in northern Alaska: (1) A 15 site network of continuously operating active-layer and climate monitoring stations, and (2) a 21 element array of deep bore-holes in which the thermal state of deep permafrost is monitored. Here, we focus on the USGS Alaska Active Layer and Climate Monitoring Network (AK-CLIM). These 15 stations are deployed in longitudinal transects that span Alaska north of the Brooks Range, (11 in The National Petroleum Reserve Alaska, (NPRA), and 4 in The Arctic National Wildlife Refuge (ANWR)). An informative overview and update of the USGS AK-CLIM network is presented, including insight to current data, processing and analysis software, and plans for data telemetry. Data collection began in 1998 and parameters currently measured include air temperature, soil temperatures (5-120 cm), snow depth, incoming and reflected short-wave radiation, soil moisture (15 cm), wind speed and direction. Custom processing and analysis software has been written that calculates additional parameters such as active layer thaw depth, thawing-degree-days, albedo, cloudiness, and duration of seasonal snow cover. Data from selected AK-CLIM stations are now temporally sufficient to begin identifying trends, anomalies, and inter-annual variability in the climate of northern Alaska.

Integrated global background monitoring network. Preliminary results from Torres del Paine and Olympic National Parks

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

Wiersma, G.B.; Kohler, A.; Boelcke, C.

1985-10-01

During 1984, a pilot project was initiated for monitoring pollution at Torres del Paine National Park in southern Chile and Olympic National Park in the United States. These are two of three initial sites that are to be established as part of an integrated global backgound monitoring network. Eventually, the plan is to establish a world-wide system of such sites. We collected and analyzed samples of the soil, water, air, and two species of plants (moss and lichen). We also collected and analyzed samples of the forest litter. We compared the samples of soil and vegetation against reference samples. Wemore » also compared samples of soil, vegetation, and of organic material from Torres del Paine against similar samples from Olympic and Sequoia-Kings Canyon National Parks in the United States. Although the data is preliminary, it is in agreement with out initial hypothesis that Torres del Paine and Olympic National Parks are not a polluted sites.« less

The South Fork Experimental Watershed: Soil moisture and precipitation network for satellite validation

NASA Astrophysics Data System (ADS)

Cosh, M. H.; Prueger, J. H.; McKee, L.; Bindlish, R.

2013-12-01

A recently deployed long term network for the study of soil moisture and precipitation was deployed in north central iowa, in cooperation between USDA and NASA. This site will be a joint calibration/validation network for the Soil Moisture Active Passive (SMAP) and Global Precipitation Measurement (GPM) missions. At total of 20 dual gauge precipitation gages were established across a watershed landscape with an area of approximately 600 km2. In addition, four soil moisture probes were installed in profile at 5, 10, 20, and 50 cm. The network was installed in April of 2013, at the initiation of the Iowa Flood Study (IFloodS) which was a six week intensive ground based radar observation period, conducted in coordination with NASA and the University of Iowa. This site is a member watershed of the Group on Earth Observations Joint Experiments on Crop Assessment and Monitoring (GEO-JECAM) program. A variety of quality control procedures are examined and spatial and temporal stability aspects of the network are examined. Initial comparisons of the watershed to soil moisture estimates from satellites are also conducted.

Delta-Flux: An eddy covariance network for a climate-smart Lower Mississippi Basin

USGS Publications Warehouse

Runkle, Benjamin R. K.; Rigby, James R.; Reba, Michele L.; Anapalli, Saseendran S.; Bhattacharjee, Joydeep; Krauss, Ken W.; Liang, Lu; Locke, Martin A.; Novick, Kimberly A.; Sui, Ruixiu; Suvočarev, Kosana; White, Paul M.

2017-01-01

Networks of remotely monitored research sites are increasingly the tool used to study regional agricultural impacts on carbon and water fluxes. However, key national networks such as the National Ecological Observatory Network and AmeriFlux lack contributions from the Lower Mississippi River Basin (LMRB), a highly productive agricultural area with opportunities for soil carbon sequestration through conservation practices. The authors describe the rationale to create the new Delta-Flux network, which will coordinate efforts to quantify carbon and water budgets at seventeen eddy covariance flux tower sites in the LMRB. The network structure will facilitate climate-smart management strategies based on production-scale and continuous measurements of carbon and water fluxes from the landscape to the atmosphere under different soil and water management conditions. The seventeen instrumented field sites are expected to monitor fluxes within the most characteristic landscapes of the target area: row-crop fields, pasture, grasslands, forests, and marshes. The network participants are committed to open collaboration and efficient regionalization of site-level findings to support sustainable agricultural and forestry management and conservation of natural resources.

A Field-Scale Sensor Network Data Set for Monitoring and Modeling the Spatial and Temporal Variation of Soil Water Content in a Dryland Agricultural Field

NASA Astrophysics Data System (ADS)

Gasch, C. K.; Brown, D. J.; Campbell, C. S.; Cobos, D. R.; Brooks, E. S.; Chahal, M.; Poggio, M.

2017-12-01

We describe a soil water content monitoring data set and auxiliary data collected at a 37 ha experimental no-till farm in the Northwestern United States. Water content measurements have been compiled hourly since 2007 by ECH2O-TE and 5TE sensors installed at 42 locations and five depths (0.3, 0.6, 0.9, 1.2, and 1.5 m, 210 sensors total) across the R.J. Cook Agronomy Farm, a Long-Term Agro-Ecosystem Research Site stationed on complex terrain in a Mediterranean climate. In addition to soil water content readings, the data set includes hourly and daily soil temperature readings, annual crop histories, a digital elevation model, Bt horizon maps, seasonal apparent electrical conductivity, soil texture, and soil bulk density. Meteorological records are also available for this location. We discuss the unique challenges of maintaining the network on an operating farm and demonstrate the nature and complexity of the soil water content data. This data set is accessible online through the National Agriculture Library, has been assigned a DOI, and will be maintained for the long term.

Feasibility analysis of using inverse modeling for estimating field-scale evapotranspiration in maize and soybean fields from soil water content monitoring networks

NASA Astrophysics Data System (ADS)

Foolad, Foad; Franz, Trenton E.; Wang, Tiejun; Gibson, Justin; Kilic, Ayse; Allen, Richard G.; Suyker, Andrew

2017-03-01

In this study, the feasibility of using inverse vadose zone modeling for estimating field-scale actual evapotranspiration (ETa) was explored at a long-term agricultural monitoring site in eastern Nebraska. Data from both point-scale soil water content (SWC) sensors and the area-average technique of cosmic-ray neutron probes were evaluated against independent ETa estimates from a co-located eddy covariance tower. While this methodology has been successfully used for estimates of groundwater recharge, it was essential to assess the performance of other components of the water balance such as ETa. In light of recent evaluations of land surface models (LSMs), independent estimates of hydrologic state variables and fluxes are critically needed benchmarks. The results here indicate reasonable estimates of daily and annual ETa from the point sensors, but with highly varied soil hydraulic function parameterizations due to local soil texture variability. The results of multiple soil hydraulic parameterizations leading to equally good ETa estimates is consistent with the hydrological principle of equifinality. While this study focused on one particular site, the framework can be easily applied to other SWC monitoring networks across the globe. The value-added products of groundwater recharge and ETa flux from the SWC monitoring networks will provide additional and more robust benchmarks for the validation of LSM that continues to improve their forecast skill. In addition, the value-added products of groundwater recharge and ETa often have more direct impacts on societal decision-making than SWC alone. Water flux impacts human decision-making from policies on the long-term management of groundwater resources (recharge), to yield forecasts (ETa), and to optimal irrigation scheduling (ETa). Illustrating the societal benefits of SWC monitoring is critical to insure the continued operation and expansion of these public datasets.

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.

Dark Fiber and Distributed Acoustic Sensing: Applications to Monitoring Seismicity and Near-Surface Properties

NASA Astrophysics Data System (ADS)

Ajo Franklin, J. B.; Lindsey, N.; Dou, S.; Freifeld, B. M.; Daley, T. M.; Tracy, C.; Monga, I.

2017-12-01

"Dark Fiber" refers to the large number of fiber-optic lines installed for telecommunication purposes but not currently utilized. With the advent of distributed acoustic sensing (DAS), these unused fibers have the potential to become a seismic sensing network with unparalleled spatial extent and density with applications to monitoring both natural seismicity as well as near-surface soil properties. While the utility of DAS for seismic monitoring has now been conclusively shown on built-for-purpose networks, dark fiber deployments have been challenged by the heterogeneity of fiber installation procedures in telecommunication as well as access limitations. However, the potential of telecom networks to augment existing broadband monitoring stations provides a strong incentive to explore their utilization. We present preliminary results demonstrating the application of DAS to seismic monitoring on a 20 km run of "dark" telecommunications fiber between West Sacramento, CA and Woodland CA, part of the Dark Fiber Testbed maintained by the DOE's ESnet user facility. We show a small catalog of local and regional earthquakes detected by the array and evaluate fiber coupling by using variations in recorded frequency content. Considering the low density of broadband stations across much of the Sacramento Basin, such DAS recordings could provide a crucial data source to constrain small-magnitude local events. We also demonstrate the application of ambient noise interferometry using DAS-recorded waveforms to estimate soil properties under selected sections of the dark fiber transect; the success of this test suggests that the network could be utilized for environmental monitoring at the basin scale. The combination of these two examples demonstrates the exciting potential for combining DAS with ubiquitous dark fiber to greatly extend the reach of existing seismic monitoring networks.

The design of tea garden environmental monitoring system based on WSN

NASA Astrophysics Data System (ADS)

Chen, Huajun; Yuan, Lina

2018-01-01

Through the application of wireless sensor network (WSN) in tea garden, it can realize the change of traditional tea garden to the modern ones, and effectively improves the comprehensive productive capacity of tea garden. According to the requirement of real-time remote in agricultural information collection and monitoring and the power supply affected by environmental limitations, based on WSN, this paper designs a set of tea garden environmental monitoring system, which achieves the monitoring nodes with ad-hoc network as well as automatic acquisition and transmission to the tea plantations of air temperature, light intensity, soil temperature and humidity.

Evaluation of AMSR2 soil moisture products over the contiguous United States using in situ data from the International Soil Moisture Network

NASA Astrophysics Data System (ADS)

Wu, Qiusheng; Liu, Hongxing; Wang, Lei; Deng, Chengbin

2016-03-01

High quality soil moisture datasets are required for various environmental applications. The launch of the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission 1-Water (GCOM-W1) in May 2012 has provided global near-surface soil moisture data, with an average revisit frequency of two days. Since AMSR2 is a new passive microwave system in operation, it is very important to evaluate the quality of AMSR2 products before widespread utilization of the data for scientific research. In this paper, we provide a comprehensive evaluation of the AMSR2 soil moisture products retrieved by the Japan Aerospace Exploration Agency (JAXA) algorithm. The evaluation was performed for a three-year period (July 2012-June 2015) over the contiguous United States. The AMSR2 soil moisture products were evaluated by comparing ascending and descending overpass products to each other as well as comparing them to in situ soil moisture observations of 598 monitoring stations obtained from the International Soil Moisture Network (ISMN). The accuracy of AMSR2 soil moisture product was evaluated against several types of monitoring networks, and for different land cover types and ecoregions. Three performance metrics, including mean difference (MD), root mean squared difference (RMSD), and correlation coefficient (R), were used in our accuracy assessment. Our evaluation results revealed that AMSR2 soil moisture retrievals are generally lower than in situ measurements. The AMSR2 soil moisture retrievals showed the best agreement with in situ measurements over the Great Plains and the worst agreement over forested areas. This study offers insights into the suitability and reliability of AMSR2 soil moisture products for different ecoregions. Although AMSR2 soil moisture retrievals represent useful and effective measurements for some regions, further studies are required to improve the data accuracy.

Toward a Continental-Scale Mesonet: USDA National Resources Conservation Service SCAN and SNOTEL System

NASA Astrophysics Data System (ADS)

Schaffer, G.; Marks, D.

2004-12-01

Since 1978 snow deposition and SWE in the inter-mountain western US have been monitored by the NRCS SNOTEL (SNOwpack TELemetry) system. This revolutionary network utilizes Meteorburst technology to telemeter data back to a central location in near real-time. With a pilot program starting in 1991, NRCS introduced SCAN (Soil Climate and Analysis Network) adding a focus on soil moisture and climate in regions outside the intermountain west. In the mid-1990's SNOTEL sites began to be augmented to match the full climate instrumentation (air temperature, humidity, solar radiation, wind, and soil moisture and temperature in addition to precipitation, snow depth and SWE) of the SCAN system. At present there are nearly 700 SNOTEL sites in 12 states in the western US and Alaska, and over 100 SCAN sites in 40 states, Puerto Rico, and several foreign countries. Though SNOTEL was originally a western snow-monitoring network, differences between SCAN and SNOTEL have largely disappeared. The combined SNOTEL/SCAN system provides a continental-scale mesonet to support river basin to continental scale hydro-climatic analysis. The system is flexible and based on off-the-shelf data recording technology, allowing instrumentation, sampling and averaging intervals to be specified by site conditions, issues, or scientific questions. Because of the NRCS data management structure, all sites have active telemetery and provide near real-time access to data through the internet. An ongoing research program is directed to improved instrumentation for measuring precipitation, snow depth and SWE, and soil moisture and temperature. Future directions include expansion of the network to be more comprehensive, and to develop focused monitoring efforts to more effectively observe elevational and regional gradients, and to capture high intensity hydro-climatic events such as potential flooding from convective storms and rain-on-snow.

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.

SoilNet - A Zigbee based soil moisture sensor network

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Weuthen, A.; Rosenbaum, U.; Huisman, J. A.; Vereecken, H.

2007-12-01

Soil moisture plays a key role in partitioning water and energy fluxes, in providing moisture to the atmosphere for precipitation, and controlling the pattern of groundwater recharge. Large-scale soil moisture variability is driven by variation of precipitation and radiation in space and time. At local scales, land cover, soil conditions, and topography act to redistribute soil moisture. Despite the importance of soil moisture, it is not yet measured in an operational way, e.g. for a better prediction of hydrological and surface energy fluxes (e.g. runoff, latent heat) at larger scales and in the framework of the development of early warning systems (e.g. flood forecasting) and the management of irrigation systems. The SoilNet project aims to develop a sensor network for the near real-time monitoring of soil moisture changes at high spatial and temporal resolution on the basis of the new low-cost ZigBee radio network that operates on top of the IEEE 802.15.4 standard. The sensor network consists of soil moisture sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee wireless sensor network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. such as rainfall occurrences. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. We will present first results of experiments to verify network stability and the accuracy of the soil moisture sensors. Simultaneously, we have developed a data management and visualisation system. We tested the wireless network on a 100 by 100 meter forest plot equipped with 25 end devices each consisting of 6 vertically arranged soil moisture sensors. The next step will be the instrumentation of two small catchments (~30 ha) with a 30 m spacing of the end devices. juelich.de/icg/icg-4/index.php?index=739

Iowa flood studies (IFloodS) in the South Fork experimental watershed: soil moisture and precipitation monitoring

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are valuable for hydrologic modeling and agricultural decision support. These estimates are typically produced via a combination of sparse ¬in situ networks and remotely-sensed products or where sensory grids and quality satellite estimates are unavailable, through derived h...

Variation in density and diversity of species of Phytophthora in two forest stream networks

Treesearch

Jaesoon Hwang; Steven N. Jeffers; Steven W. Oak

2010-01-01

Monitoring occurrence and distribution of Phytophthora species, including Phytophthora ramorum, in forest ecosystems can be achieved in several ways including sampling symptomatic plants, infested soils, and infested streams. Collecting plant and soil samples can be laborious and time consuming due to the distance surveyors...

Air Monitoring Network at Tonopah Test Range: Network Description and Capabilities

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

Jeffrey Tappen; George Nikolich; Ken Giles

2010-05-18

During the period April to June 2008, at the behest of the U.S. Department of Energy (DOE) National Nuclear Security Administration, Nevada Site Office (NNSA/NSO); the Desert Research Institute (DRI) constructed and deployed two portable environmental monitoring stations at the Tonopah Test Range (TTR) as part of the Environmental Restoration Project Soils Sub-Project. The TTR is located within the boundaries of the Nevada Test and Training Range (NTTR) near the northern edge, and covers an area of approximately 725.20 km2 (179,200 acres). The primary objective of the monitoring stations is to evaluate whether and under what conditions there is windmore » transport of radiological contaminants from one of the three Soil Sub-Project Corrective Action Units (CAUs) associated with Operation Roller Coaster on TTR. Operation Roller Coaster was a series of tests, conducted in 1963, designed to examine the stability and dispersal of plutonium in storage and transportation accidents. These tests did not result in any nuclear explosive yield. However, the tests did result in the dispersal of plutonium and contamination of surface soils in the surrounding area.« less

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Werban, Ulrike; Zacharias, Steffen; Pohle, Marco; Dietrich, Peter; Wollschläger, Ute

2017-01-01

Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ, with particular focus on the temporal variability of the spatial patterns of ECa and θ. To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ, and (iii) the ECa-θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ, and the use of EMI-based ECa data with respect to hydrological applications.

Long term (2006-2016) seasonal and inter-annual variability of soil electrical resistivity in a Laotian catchment of the OZCAR network. Impact of land use change, soil type and rainfall

NASA Astrophysics Data System (ADS)

Robain, Henri; Ribolzi, Olivier; De Rouw, Anneke; Silvera, Norbert; Souniaphong, Phabvilay; Soulileuth, Bousamai; Latchasak, Keooudone; Sengtaheuanghoung, Oloth; Valentin, Christian; Gaillardet, Jerome

2017-04-01

The MSEC(1) observatory of the critical zone in south-east Asia, which is part of the OZCAR(2) Network, has been monitored since 1999 (Laos, Thailand, Vietnam) to study the long term impact of land use changes in tropical mountainous regions, in terms of soil properties (porosity, depth, SOC, nutrients…), biodiversity (weeds, soil macro fauna), plant roots (architecture, functions,…), and transfers within the critical zone at various temporal and space scales: partition between infiltration and runoff, water quality (physical, chemical and bacteriological) and erosion processes (splash, inter-rill and rill, tillage, mass-movement). In the Houay Pano catchment located in Northern Laos, a long-term monitoring system was implemented in 2006 combining Electrical Resistivity Tomography (ERT), with soil and hydrological equipments to better analyse the interactions between bank and hillslopes groundwater, and streamwater, in a context of steep slopes (>50%) and rapid land use change (conversion of annual crops to teak plantation). This continuous ERT monitoring has been carried out along a representative 100 m long transect in the middle of the 65 ha catchment perpendicular to the stream. The data were collected every week during rainy season and every second week during dry season. It has been associated with hydrological monitoring (piezometers, limnimeters, gauging weirs). Such high resolution geophysical monitoring data set (approx. 900 apparent resistivity measurements for each acquisition) provides an invaluable non-invasive proxy of soil water content variations in the different layers of the vadose zone. It demonstrates: i) the influence of plant cover on water infiltration; ii) the pathways for vertical and horizontal water fluxes within the soil cover; iii) the control of soil organisation along the hillslope over the hydrological behaviour of the unsaturated part of the critical zone. (1) «Multi-Scale Environmental Changes» : http://msec.obs-mip.fr/ (2) «Observatoires de la Zone Critique Applications et Recherches» Including the former RBV (Réseau de Bassins Versants) : http://portailrbv.sedoo.fr/

Establishment of a hydrological monitoring network in a tropical African catchment: An integrated participatory approach

NASA Astrophysics Data System (ADS)

Gomani, M. C.; Dietrich, O.; Lischeid, G.; Mahoo, H.; Mahay, F.; Mbilinyi, B.; Sarmett, J.

Sound decision making for water resources management has to be based on good knowledge of the dominant hydrological processes of a catchment. This information can only be obtained through establishing suitable hydrological monitoring networks. Research catchments are typically established without involving the key stakeholders, which results in instruments being installed at inappropriate places as well as at high risk of theft and vandalism. This paper presents an integrated participatory approach for establishing a hydrological monitoring network. We propose a framework with six steps beginning with (i) inception of idea; (ii) stakeholder identification; (iii) defining the scope of the network; (iv) installation; (v) monitoring; and (vi) feedback mechanism integrated within the participatory framework. The approach is illustrated using an example of the Ngerengere catchment in Tanzania. In applying the approach, the concept of establishing the Ngerengere catchment monitoring network was initiated in 2008 within the Resilient Agro-landscapes to Climate Change in Tanzania (ReACCT) research program. The main stakeholders included: local communities; Sokoine University of Agriculture; Wami Ruvu Basin Water Office and the ReACCT Research team. The scope of the network was based on expert experience in similar projects and lessons learnt from literature review of similar projects from elsewhere integrated with local expert knowledge. The installations involved reconnaissance surveys, detailed surveys, and expert consultations to identify best sites. First, a Digital Elevation Model, land use, and soil maps were used to identify potential monitoring sites. Local and expert knowledge was collected on flow regimes, indicators of shallow groundwater plant species, precipitation pattern, vegetation, and soil types. This information was integrated and used to select sites for installation of an automatic weather station, automatic rain gauges, river flow gauging stations, flow measurement sites and shallow groundwater wells. The network is now used to monitor hydro-meteorological parameters in collaboration with key stakeholders in the catchment. Preliminary results indicate that the network is working well. The benefits of this approach compared to conventional narrow scientific/technical approaches have been shown by gaining rapid insight into the hydrology of the catchment, identifying best sites for the instruments; and voluntary participation of stakeholders in installation, monitoring and safeguarding the installations. This approach has proved simple yet effective and yielded good results. Based on this experience gained in applying the approach in establishing the Ngerengere catchment monitoring network, we conclude that the integrated participatory approach helps to assimilate local and expert knowledge in catchments monitoring which consequently results in: (i) identifying best sites for the hydrologic monitoring; (ii) instilling the sense of ownership; (iii) providing security of the installed network; and (iv) minimizing costs for installation and monitoring.

Soil moisture and precipitation monitoring in the South Fork experimental watershed during the Iowa flood studies (IFloodS)

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are valuable for hydrologic modeling and agricultural decision support. These estimates are typically produced via a combination of sparse in situ networks and remotely-sensed products or where sensory grids and quality satellite estimates are unavailable, through derived hy...

A spatiotemporal analysis of hydrological patterns based on a wireless sensor network system

NASA Astrophysics Data System (ADS)

Plaza, F.; Slater, T. A.; Zhong, X.; Li, Y.; Liang, Y.; Liang, X.

2017-12-01

Understanding complicated spatiotemporal patterns of eco-hydrological variables at a small scale plays a profound role in improving predictability of high resolution distributed hydrological models. However, accurate and continuous monitoring of these complex patterns has become one of the main challenges in the environmental sciences. Wireless sensor networks (WSNs) have emerged as one of the most widespread potential solutions to achieve this. This study presents a spatiotemporal analysis of hydrological patterns (e.g., soil moisture, soil water potential, soil temperature and transpiration) based on observational data collected from a dense multi-hop wireless sensor network (WSN) in a steep-forested testbed located in Southwestern Pennsylvania, USA. At this WSN testbed with an approximate area of 3000 m2, environmental variables are collected from over 240 sensors that are connected to more than 100 heterogeneous motes. The sensors include the soil moisture of EC-5, soil temperature and soil water potential of MPS-1 and MPS-2, and sap flow sensors constructed in house. The motes consist of MICAz, IRIS and TelosB. In addition, several data loggers have been installed along the site to provide a comparative reference to the WSN measurements for the purpose of checking the WSN data quality. The edaphic properties monitored by the WSN sensors show strong agreement with the data logger measurements. Moreover, sap flow measurements, scaled to tree stand transpiration, are found to be reasonable. This study also investigates the feasibility and roles that these sensor measurements play in improving the performance of high-resolution distributed hydrological models. In particular, we explore this using a modified version of the Distributed Hydrological Soil Vegetation Model (DHSVM).

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).

A ground based L-band radiometer for the monitoring of soil moisture in the region of Millbrook, New York, USA

USDA-ARS?s Scientific Manuscript database

A field experiment was performed in grassland near Millbrook, New York, using a NOAA Microwave Observation Facility, which comprises a network for in situ observation of soil moisture and a mobile dual polarized L band radiometer. During the field campaign, intensive measurements of L band brightnes...

Air Monitoring Network at Tonopah Test Range: Network Description, Capabilities, and Analytical Results

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

Hartwell, William T.; Daniels, Jeffrey; Nikolich, George

2012-01-01

During the period April to June 2008, at the behest of the Department of Energy (DOE), National Nuclear Security Administration, Nevada Site Office (NNSA/NSO); the Desert Research Institute (DRI) constructed and deployed two portable environmental monitoring stations at the Tonopah Test Range (TTR) as part of the Environmental Restoration Project Soils Activity. DRI has operated these stations since that time. A third station was deployed in the period May to September 2011. The TTR is located within the northwest corner of the Nevada Test and Training Range (NTTR), and covers an area of approximately 725.20 km2 (280 mi2). The primarymore » objective of the monitoring stations is to evaluate whether and under what conditions there is wind transport of radiological contaminants from Soils Corrective Action Units (CAUs) associated with Operation Roller Coaster on TTR. Operation Roller Coaster was a series of tests, conducted in 1963, designed to examine the stability and dispersal of plutonium in storage and transportation accidents. These tests did not result in any nuclear explosive yield. However, the tests did result in the dispersal of plutonium and contamination of surface soils in the surrounding area.« less

Subsurface lateral preferential flow network revealed by time-lapse ground-penetrating radar in a hillslope

NASA Astrophysics Data System (ADS)

Guo, Li; Chen, Jin; Lin, Henry

2014-12-01

Subsurface lateral preferential flow (LPF) has been observed to contribute substantially to hillslope and catchment runoff. However, the complex nature of LPF and the lack of an appropriate investigation method have hindered direct LPF observation in the field. Thus, the initiation, persistence, and dynamics of LPF networks remain poorly understood. This study explored the application of time-lapse ground-penetrating radar (GPR) together with an artificial infiltration to shed light on the nature of LPF and its dynamics in a hillslope. Based on our enhanced field experimental setup and carefully refined GPR data postprocessing algorithms, we developed a new protocol to reconstruct LPF networks with centimeter resolution. This is the first time that a detailed LPF network and its dynamics have been revealed noninvasively along a hillslope. Real-time soil water monitoring and field soil investigation confirmed the locations of LPF mapped by time-lapse GPR surveys. Our results indicated the following: (1) Increased spatial variations of radar signals after infiltration suggested heterogeneous soil water changes within the studied soil, which reflected the generation and dynamics of LPF; (2) Two types of LPF networks were identified, the network at the location of soil permeability contrasts and that formed via a series of connected preferential flow paths; and (3) The formation and distribution of LPF networks were influenced by antecedent soil water condition. Overall, this study demonstrates clearly that carefully designed time-lapse GPR surveys with enhanced data postprocessing offer a practical and nondestructive way of mapping LPF networks in the field, thereby providing a potentially significant enhancement in our ability to study complex subsurface flow processes across the landscape.

Design of autonomous sensor nodes for remote soil monitoring in tropical banana plantation

NASA Astrophysics Data System (ADS)

Tiausas, Francis Jerome G.; Co, Jerelyn; Macalinao, Marc Joseph M.; Guico, Maria Leonora; Monje, Jose Claro; Oppus, Carlos

2017-09-01

Determining the effect of Fusarium oxysporum f. sp. cubense Tropical Race 4 on various soil parameters is essential in modeling and predicting its occurrence in banana plantations. One way to fulfill this is through a sensor network that will continuously and automatically monitor environmental conditions at suspect locations for an extended period of time. A wireless sensor network was developed specifically for this purpose. This sensor network is capable of measuring soil acidity, moisture, temperature, and conductivity. The designed prototype made use of off-the-shelf Parrot Flower Power soil sensor, pH sensor, Bluno Beetle, battery, and 3D-printed materials, catering specifically to the conditions of tropical banana plantations with consideration for sensor node size, communication, and power. Sensor nodes were tested on both simulated tropical environments and on an actual banana plantation in San Jose, General Santos City, Philippines. Challenges were resolved through iterative design and development of prototypes. Several tests including temperature and weather resilience, and structural stress tests were done to validate the design. Findings showed that the WSN nodes developed for this purpose are resilient to high tropical temperatures for up to 12 hours of continuous exposure, are able to withstand compressive forces of up to 8880.6 N, and can reliably collect data automatically from the area 47.96% of the time at an hourly frequency under actual field conditions.

A multi-scale automatic observatory of soil moisture and temperature served for satellite product validation in Tibetan Plateau

NASA Astrophysics Data System (ADS)

Tang, S.; Dong, L.; Lu, P.; Zhou, K.; Wang, F.; Han, S.; Min, M.; Chen, L.; Xu, N.; Chen, J.; Zhao, P.; Li, B.; Wang, Y.

2016-12-01

Due to the lack of observing data which match the satellite pixel size, the inversion accuracy of satellite products in Tibetan Plateau(TP) is difficult to be evaluated. Hence, the in situ observations are necessary to support the calibration and validation activities. Under the support of the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III) projec a multi-scale automatic observatory of soil moisture and temperature served for satellite product validation (TIPEX-III-SMTN) were established in Tibetan Plateau. The observatory consists of two regional scale networks, including the Naqu network and the Geji network. The Naqu network is located in the north of TP, and characterized by alpine grasslands. The Geji network is located in the west of TP, and characterized by marshes. Naqu network includes 33 stations, which are deployed in a 75KM*75KM region according to a pre-designed pattern. At Each station, soil moisture and temperature are measured by five sensors at five soil depths. One sensor is vertically inserted into 0 2 cm depth to measure the averaged near-surface soil moisture and temperature. The other four sensors are horizontally inserted at 5, 10, 20, and 30 cm depths, respectively. The data are recorded every 10 minutes. A wireless transmission system is applied to transmit the data in real time, and a dual power supply system is adopted to keep the continuity of the observation. The construction of Naqu network has been accomplished in August, 2015, and Geji network will be established before Oct., 2016. Observations acquired from TIPEX-III-SMTN can be used to validate satellite products with different spatial resolution, and TIPEX-III-SMTN can also be used as a complementary of the existing similar networks in this area, such as CTP-SMTMN (the multiscale Soil Moistureand Temperature Monitoring Network on the central TP) . Keywords: multi-scale soil moisture soil temperature, Tibetan Plateau Acknowledgments: This work was jointly supported by CMA Special Fund for Scientific Research in the Public Interest (Grant No. GYHY201406001, GYHY201206008-01), and Climate change special fund (QHBH2014)'

Possibilities of using the German Federal States' permanent soil monitoring program for the monitoring of potential effects of genetically modified organisms (GMO).

PubMed

Toschki, Andreas; Jänsch, Stephan; Roß-Nickoll, Martina; Römbke, Jörg; Züghart, Wiebke

2015-01-01

In the Directive 2001/18/EC on the deliberate release of genetically modified organisms (GMO) into the environment, a monitoring of potential risks is prescribed after their deliberate release or placing on the market. Experience and data of already existing monitoring networks should be included. The present paper summarizes the major findings of a project funded by the Federal Agency for Nature Conservation (Nutzungsmöglichkeiten der Boden-Dauerbeobachtung der Länder für das Monitoring der Umweltwirkungen gentechnisch veränderter Pflanzen. BfN Skripten, Bonn-Bad Godesberg 369, 2014). The full report in german language can be accessed on http://www.bfn.de and is available as Additional file 1. The aim of the project was to check if it is possible to use the German permanent soil monitoring program (PSM) for the monitoring of GMO. Soil organism communities are highly diverse and relevant with respect to the sustainability of soil functions. They are exposed to GMO material directly by feeding or indirectly through food chain interactions. Other impacts are possible due to their close association to soil particles. The PSM program can be considered as representative with regard to different soil types and ecoregions in Germany, but not for all habitat types relevant for soil organisms. Nevertheless, it is suitable as a basic grid for monitoring the potential effects of GMO on soil invertebrates. PSM sites should be used to derive reference values, i.e. range of abundance and presence of different relevant species of soil organisms. Based on these references, it is possible to derive threshold values to define the limit of acceptable change or impact. Therefore, a minimum set of sites and minimum set of standardized methods are needed, i.e. characterization of each site, sampling of selected soil organism groups, adequate adaptation of methods for the purpose of monitoring of potential effects of GMO. Finally, and probably most demanding, it is needed to develop a harmonized evaluation concept.

Crop yield monitoring in the Sahel using root zone soil moisture anomalies derived from SMOS soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian

2017-04-01

West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the soil water availability in the soil. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root soil moisture rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ soil moisture measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm soil moisture maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were compared to 17 years of crop yield estimates from the FAOSTAT database (1998-2014). Results showed that the 30-cm soil moisture anomalies explained 89% of the crop yield variation in Niger, 72% in Burkina Faso, 82% in Mali and 84% in Senegal.

CAOS: the nested catchment soil-vegetation-atmosphere observation platform

NASA Astrophysics Data System (ADS)

Weiler, Markus; Blume, Theresa

2016-04-01

Most catchment based observations linking hydrometeorology, ecohydrology, soil hydrology and hydrogeology are typically not integrated with each other and lack a consistent and appropriate spatial-temporal resolution. Within the research network CAOS (Catchments As Organized Systems), we have initiated and developed a novel and integrated observation platform in several catchments in Luxembourg. In 20 nested catchments covering three distinct geologies the subscale processes at the bedrock-soil-vegetation-atmosphere interface are being monitored at 46 sensor cluster locations. Each sensor cluster is designed to observe a variety of different fluxes and state variables above and below ground, in the saturated and unsaturated zone. The numbers of sensors are chosen to capture the spatial variability as well the average dynamics. At each of these sensor clusters three soil moisture profiles with sensors at different depths, four soil temperature profiles as well as matric potential, air temperature, relative humidity, global radiation, rainfall/throughfall, sapflow and shallow groundwater and stream water levels are measured continuously. In addition, most sensors also measure temperature (water, soil, atmosphere) and electrical conductivity. This setup allows us to determine the local water and energy balance at each of these sites. The discharge gauging sites in the nested catchments are also equipped with automatic water samplers to monitor water quality and water stable isotopes continuously. Furthermore, water temperature and electrical conductivity observations are extended to over 120 locations distributed across the entire stream network to capture the energy exchange between the groundwater, stream water and atmosphere. The measurements at the sensor clusters are complemented by hydrometeorological observations (rain radar, network of distrometers and dense network of precipitation gauges) and linked with high resolution meteorological models. In this presentation, we will highlight the potential of this integrated observation platform to estimate energy and water exchange between the terrestrial and aquatic systems and the atmosphere, to trace water flow pathways in the unsaturated and saturated zone, and to understand the organization of processes and fluxes and thus runoff generation at different temporal and spatial scales.

The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil.

PubMed

Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

2015-11-11

Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters.

Analysis of in situ resources for the Soil Moisture Active Passive Validation Experiments in 2015 and 2016

NASA Astrophysics Data System (ADS)

Cosh, M. H.; Jackson, T. J.; Colliander, A.; Bindlish, R.; McKee, L.; Goodrich, D. C.; Prueger, J. H.; Hornbuckle, B. K.; Coopersmith, E. J.; Holifield Collins, C.; Smith, J.

2016-12-01

With the launch of the Soil Moisture Active Passive Mission (SMAP) in 2015, a new era of soil moisture monitoring was begun. Soil moisture is available on a near daily basis at a 36 km resolution for the globe. But this dataset is only as valuable if its products are accurate and reliable. Therefore, in order to demonstrate the accuracy of the soil moisture product, NASA enacted an extensive calibration and validation program with many in situ soil moisture networks contributing data across a variety of landscape regimes. However, not all questions can be answered by these networks. As a result, two intensive field experiments were executed to provide more detailed reference points for calibration and validation. Multi-week field campaigns were conducted in Arizona and Iowa at the USDA Agricultural Research Service Walnut Gulch and South Fork Experimental Watersheds, respectively. Aircraft observations were made to provide a high resolution data product. Soil moisture, soil roughness and vegetation data were collected at high resolution to provide a downscaled dataset to compare against aircraft and satellite estimates.

Results of hydrologic monitoring on landslide-prone coastal bluffs near Mukilteo, Washington

USGS Publications Warehouse

Smith, Joel B.; Baum, Rex L.; Mirus, Benjamin B.; Michel, Abigail R.; Stark, Ben

2017-08-31

A hydrologic monitoring network was installed to investigate landslide hazards affecting the railway corridor along the eastern shore of Puget Sound between Seattle and Everett, near Mukilteo, Washington. During the summer of 2015, the U.S. Geological Survey installed monitoring equipment at four sites equipped with instrumentation to measure rainfall and air temperature every 15 minutes. Two of the four sites are installed on contrasting coastal bluffs, one landslide scarred and one vegetated. At these two sites, in addition to rainfall and air temperature, volumetric water content, pore pressure, soil suction, soil temperature, and barometric pressure were measured every 15 minutes. The instrumentation was designed to supplement landslide-rainfall thresholds developed by the U.S. Geological Survey with a long-term goal of advancing the understanding of the relationship between landslide potential and hydrologic forcing along the coastal bluffs. Additionally, the system was designed to function as a prototype monitoring system to evaluate criteria for site selection, instrument selection, and placement of instruments. The purpose of this report is to describe the monitoring system, present the data collected since installation, and describe significant events represented within the dataset, which is published as a separate data release. The findings provide insight for building and configuring larger, modular monitoring networks.

METEOPOLE-FLUX: an observatory of terrestrial water, energy, and CO2 fluxes in Toulouse

NASA Astrophysics Data System (ADS)

Calvet, Jean-Christophe; Roujean, Jean-Louis; Zhang, Sibo; Maurel, William; Piguet, Bruno; Barrié, Joël; Bouhours, Gilles; Couzinier, Jacques; Garrouste, Olivier; Girres, Sandrine; Suquia, David; Tzanos, Diane

2016-04-01

The METEOPOLE-FLUX project (http://www.cnrm.meteo.fr/spip.php?article874&lang=en) aims at monitoring a large suburban set-aside field in the city of Toulouse (43.572898 N, 1.374384 E). Since June 2012, these data contribute to the international effort to monitor terrestrial ecosystems (grasslands in particular), to the validation of land surface models, and to the near real time quality monitoring of operational weather forecast models. Various variables are monitored at a subhourly rate: wind speed, air temperature, air humidity, atmospheric pressure, precipitation, turbulent fluxes (H, LE, CO2), downwelling and upwelling solar and infrared radiation, downwelling and upwelling PAR, fraction of diffuse incoming PAR, presence of water intercepted by vegetation (rain, dew), soil moisture profile, soil temperature profile, surface albedo, transmissivity of PAR in vegetation canopy. Moreover, local observations are performed using remote sensing techniques: infrared radiometry, GNSS reflectometry, and multi-band surface reflectometry using an aerosol photometer from the AERONET network. Destructive measurements of LAI, green/brown above-ground biomass, and necromass are performed twice a year. This site is characterized by a large fraction of gravels and stones in the soil, ranging from 17% to 35% in the top soil layer (down to 0.6 m), and peaking at 81% at 0.7 m. The impact of gravels and stones on thermal and moisture fluxes in the soil has not been much addressed in the past and is not represented in most land surface models. Their impact on the available water content for plant transpiration and plant growth is not much documented so far. The long term monitoring of this site will therefore improve the knowledge on land processes. The data will be used together with urban meteorological data to characterize the urban heat island. Finally, this site will be used for the CAL/VAL of various satellite products in conjunction with the SMOSMANIA soil moisture network (http://www.cnrm.meteo.fr/spip.php?article251&lang=en). The site will be presented together a first comparison of the ISBA land surface model with the observations.

The role of metadata and strategies to detect and control temporal data bias in environmental monitoring of soil contamination.

PubMed

Desaules, André

2012-11-01

It is crucial for environmental monitoring to fully control temporal bias, which is the distortion of real data evolution by varying bias through time. Temporal bias cannot be fully controlled by statistics alone but requires appropriate and sufficient metadata, which should be under rigorous and continuous quality assurance and control (QA/QC) to reliably document the degree of consistency of the monitoring system. All presented strategies to detect and control temporal data bias (QA/QC, harmonisation/homogenisation/standardisation, mass balance approach, use of tracers and analogues and control of changing boundary conditions) rely on metadata. The Will Rogers phenomenon, due to subsequent reclassification, is a particular source of temporal data bias introduced to environmental monitoring here. Sources and effects of temporal data bias are illustrated by examples from the Swiss soil monitoring network. The attempt to make a comprehensive compilation and assessment of required metadata for soil contamination monitoring reveals that most metadata are still far from being reliable. This leads to the conclusion that progress in environmental monitoring means further development of the concept of environmental metadata for the sake of temporal data bias control as a prerequisite for reliable interpretations and decisions.

Remote Monitoring of Soil Water Content, Temperature, and Heat Flow Using Low-Cost Cellular (3G) IoT Technology

NASA Astrophysics Data System (ADS)

Ham, J. M.

2016-12-01

New microprocessor boards, open-source sensors, and cloud infrastructure developed for the Internet of Things (IoT) can be used to create low-cost monitoring systems for environmental research. This project describes two applications in soil science and hydrology: 1) remote monitoring of the soil temperature regime near oil and gas operations to detect the thermal signature associated with the natural source zone degradation of hydrocarbon contaminants in the vadose zone, and 2) remote monitoring of soil water content near the surface as part of a global citizen science network. In both cases, prototype data collection systems were built around the cellular (2G/3G) "Electron" microcontroller (www.particle.io). This device allows connectivity to the cloud using a low-cost global SIM and data plan. The systems have cellular connectivity in over 100 countries and data can be logged to the cloud for storage. Users can view data real time over any internet connection or via their smart phone. For both projects, data logging, storage, and visualization was done using IoT services like Thingspeak (thingspeak.com). The soil thermal monitoring system was tested on experimental plots in Colorado USA to evaluate the accuracy and reliability of different temperature sensors and 3D printed housings. The soil water experiment included comparison opens-source capacitance-based sensors to commercial versions. Results demonstrate the power of leveraging IoT technology for field research.

A Concept for the Development of Spatially Resolved Measurements for Soil Moisture with TEM Waveguides

NASA Astrophysics Data System (ADS)

Lapteva, Yulia; Schmidt, Felix; Bumberger, Jan

2014-05-01

Soil water content plays a leading role in delimitating water and energy fluxes at the land surface and controlling groundwater recharging. The information about water content in the soil would be very useful in overcoming the challenge of managing water resources under conditions of increasing scarcity in Southern Europe and the Mediterranean region.For collecting data about the water content in soil, it is possible to use remote sensing and groundwater monitoring, built wireless sensor networks for water monitoring. Remote sensing provides a unique capability to get the information of soil moisture at global and regional scales. Wireless environmental sensor networks enable to connect local and regional-scale soil water content observations. There exist different ground based soil moisture measurement methods such as TDR, FDR, electromagnetic waves (EW), electrical and acoustic methods. Among these methods, the time domain reflectometry (TDR) is considered to be the most important and widely used electromagnetic approach. The special techniques for the reconstruction of the layered soil with TDR are based on differential equations in the time domain and numerical optimization algorithms. However, these techniques are time- consuming and suffering from some problems, like multiple reflections at the boundary surfaces. To overcome these limitations, frequency domain measurement (FDM) techniques could be used. With devices like vector network analyzers (VNA) the accuracy of the measurement itself and of the calibration can be improved. For field applicable methods the reflection coefficient is mathematically transformed in the time domain, which can be treated like TDR-data and the same information can be obtained. There are already existed some experiments using the frequency domain data directly as an input for inversion algorithms to find the spatial distribution of the soil parameters. The model that is used represents an exact solution of the Maxwell's equations. It describes the one-dimensional wave propagation in a multi-layered medium, assuming the wave to be transverse electromagnetic (TEM). In the particular case of transmission lines with perpendicularly arranged layer transitions this assumption is very close to reality. Such waveguides and their frequency domain measurements in layered media are promising concerning a development ways working with soil moisture detection.

Subsurface event detection and classification using Wireless Signal Networks.

PubMed

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

2012-11-05

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

Subsurface Event Detection and Classification Using Wireless Signal Networks

PubMed Central

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.

2012-01-01

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

NASA Astrophysics Data System (ADS)

Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig

2008-08-01

SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

USGS Publications Warehouse

Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig

2008-01-01

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

A soil water based index as a suitable agricultural drought indicator

NASA Astrophysics Data System (ADS)

Martínez-Fernández, J.; González-Zamora, A.; Sánchez, N.; Gumuzzio, A.

2015-03-01

Currently, the availability of soil water databases is increasing worldwide. The presence of a growing number of long-term soil moisture networks around the world and the impressive progress of remote sensing in recent years has allowed the scientific community and, in the very next future, a diverse group of users to obtain precise and frequent soil water measurements. Therefore, it is reasonable to consider soil water observations as a potential approach for monitoring agricultural drought. In the present work, a new approach to define the soil water deficit index (SWDI) is analyzed to use a soil water series for drought monitoring. In addition, simple and accurate methods using a soil moisture series solely to obtain soil water parameters (field capacity and wilting point) needed for calculating the index are evaluated. The application of the SWDI in an agricultural area of Spain presented good results at both daily and weekly time scales when compared to two climatic water deficit indicators (average correlation coefficient, R, 0.6) and to agricultural production. The long-term minimum, the growing season minimum and the 5th percentile of the soil moisture series are good estimators (coefficient of determination, R2, 0.81) for the wilting point. The minimum of the maximum value of the growing season is the best estimator (R2, 0.91) for field capacity. The use of these types of tools for drought monitoring can aid the better management of agricultural lands and water resources, mainly under the current scenario of climate uncertainty.

Affordable Open-Source Data Loggers for Distributed Measurements of Sap-Flux, Stem Growth, Relative Humidity, Temperature, and Soil Water Content

NASA Astrophysics Data System (ADS)

Anderson, T.; Jencso, K. G.; Hoylman, Z. H.; Hu, J.

2015-12-01

Characterizing the mechanisms that lead to differences in forest ecosystem productivity across complex terrain remains a challenge. This difficulty can be partially attributed to the cost of installing networks of proprietary data loggers that monitor differences in the biophysical factors contributing to tree growth. Here, we describe the development and initial application of a network of open source data loggers. These data loggers are based on the Arduino platform, but were refined into a custom printed circuit board (PCB). This reduced the cost and complexity of the data loggers, which made them cheap to reproduce and reliable enough to withstand the harsh environmental conditions experienced in Ecohydrology studies. We demonstrate the utility of these loggers for high frequency, spatially-distributed measurements of sap-flux, stem growth, relative humidity, temperature, and soil water content across 36 landscape positions in the Lubrecht Experimental Forest, MT, USA. This new data logging technology made it possible to develop a spatially distributed monitoring network within the constraints of our research budget and may provide new insights into factors affecting forest productivity across complex terrain.

Environmental Monitoring Networks Optimization Using Advanced Active Learning Algorithms

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Volpi, Michele; Copa, Loris

2010-05-01

The problem of environmental monitoring networks optimization (MNO) belongs to one of the basic and fundamental tasks in spatio-temporal data collection, analysis, and modeling. There are several approaches to this problem, which can be considered as a design or redesign of monitoring network by applying some optimization criteria. The most developed and widespread methods are based on geostatistics (family of kriging models, conditional stochastic simulations). In geostatistics the variance is mainly used as an optimization criterion which has some advantages and drawbacks. In the present research we study an application of advanced techniques following from the statistical learning theory (SLT) - support vector machines (SVM) and the optimization of monitoring networks when dealing with a classification problem (data are discrete values/classes: hydrogeological units, soil types, pollution decision levels, etc.) is considered. SVM is a universal nonlinear modeling tool for classification problems in high dimensional spaces. The SVM solution is maximizing the decision boundary between classes and has a good generalization property for noisy data. The sparse solution of SVM is based on support vectors - data which contribute to the solution with nonzero weights. Fundamentally the MNO for classification problems can be considered as a task of selecting new measurement points which increase the quality of spatial classification and reduce the testing error (error on new independent measurements). In SLT this is a typical problem of active learning - a selection of the new unlabelled points which efficiently reduce the testing error. A classical approach (margin sampling) to active learning is to sample the points closest to the classification boundary. This solution is suboptimal when points (or generally the dataset) are redundant for the same class. In the present research we propose and study two new advanced methods of active learning adapted to the solution of MNO problem: 1) hierarchical top-down clustering in an input space in order to remove redundancy when data are clustered, and 2) a general method (independent on classifier) which gives posterior probabilities that can be used to define the classifier confidence and corresponding proposals for new measurement points. The basic ideas and procedures are explained by applying simulated data sets. The real case study deals with the analysis and mapping of soil types, which is a multi-class classification problem. Maps of soil types are important for the analysis and 3D modeling of heavy metals migration in soil and prediction risk mapping. The results obtained demonstrate the high quality of SVM mapping and efficiency of monitoring network optimization by using active learning approaches. The research was partly supported by SNSF projects No. 200021-126505 and 200020-121835.

Modeling Storm Water Runoff and Soil Interflow in a Managed Forest, Upper Coastal Plain of the Southeast US.

Treesearch

T.J. Callahan; J.D. Cook; Mark D. Coleman; Devendra M. Amatya; Carl C. Trettin

2004-01-01

The Forest Service-Savannah River is conducting a hectare-scale monitoring and modeling study on forest productivity in a Short Rotation Woody Crop plantation at the Savannah River Site, which is on Upper Coastal Plain of South Carolina. Detailed surveys, i.e., topography, soils, vegetation, and dainage network, of small (2-5 ha) plots have been completed in a 2 square...

The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil

PubMed Central

Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

2015-01-01

Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters. PMID:26569243

Geotechnical sensing using electromagnetic attenuation between radio transceivers

NASA Astrophysics Data System (ADS)

Ghazanfari, Ehsan; Pamukcu, Sibel; Yoon, Suk-Un; Suleiman, Muhannad T.; Cheng, Liang

2012-12-01

Monitoring the onset of a geo-event such as the intrusion of a chemical plume or a slow progressive mass slide that results in marked changes in the physical properties of the host soil could be potentially accomplished using a distributed network of embedded radio transceivers. This paper introduces a new concept of subsurface geo-event monitoring, which takes advantage of the spatial and temporal variations in signal strength of electromagnetic (EM) waves transmitted within the net of distributed radios within a sensing area. Results of experiments in the laboratory and the field demonstrated that variations in EM signal strength could be used to detect physical changes in the subsurface. Changes in selected physical properties of host soil including water content, density, and formation of discontinuities could be discerned from the changes in the signal strength of the transmitted wave between embedded radio transceivers. Good agreement was observed between a theoretical model and the experimental results for inter-transceiver distances less than 55 cm. These results demonstrated a viable new approach for distributed sensing and monitoring of subsurface hazards for civil infrastructure within a networked domain of radio transceivers.

Remarkably constant PAH concentrations in Swiss soils over the last 30 years.

PubMed

Gubler, Andreas; Wächter, Daniel; Blum, Franziska; Bucheli, Thomas D

2015-10-01

Although polycyclic aromatic hydrocarbons (PAH) are of concern due to their carcinogenic, mutagenic, and teratogenic properties and their ubiquitous occurrence in environmental compartments, only few studies assessed the temporal evolutions of PAH contents of soils over extended time periods. The Swiss Soil Monitoring Network NABO runs long-term monitoring sites resampled every five years since the 1980s. In the present study, soil (0-20 cm) samples collected from 1985 through 2013 at 25 selected monitoring sites were analysed for the 16 priority PAH according to the U.S. EPA and five PAH marker substances. We observed divergent trends for light PAH, such as naphthalene and phenanthrene, compared with heavy PAH, such as benzo[a]pyrene and benzo[ghi]perylene. Whereas the former showed decreasing concentrations since the late 1980s, no significant trends were found for the latter. Furthermore, the analyses showed that naphthalene contents decreased most strongly at rural sites featuring low population densities, while phenanthrene contents generally decreased most strongly at semi-rural sites. The deviating evolutions of light and heavy PAH were mainly attributed to their differing physico-chemical properties. Temporal evolutions in soils contradict emission inventory data suggesting PAH emissions to decline since the 1980s.

Identification of biogeochemical hot spots using time-lapse hydrogeophysics

NASA Astrophysics Data System (ADS)

Franz, T. E.; Loecke, T.; Burgin, A.

2016-12-01

The identification and monitoring of biogeochemical hot spots and hot moments is difficult using point based sampling techniques and sensors. Without proper monitoring and accounting of water, energy, and trace gas fluxes it is difficult to assess the environmental footprint of land management practices. One key limitation is optimal placement of sensors/chambers that adequately capture the point scale fluxes and thus a reasonable integration to landscape scale flux. In this work we present time-lapse hydrogeophysical imaging at an old agricultural field converted into a wetland mitigation bank near Dayton, Ohio. While the wetland was previously instrumented with a network of soil sensors and surface chambers to capture a suite of state variables and fluxes, we hypothesize that time-lapse hydrogeophysical imaging is an underutilized and critical reconnaissance tool for effective network design and landscape scaling. Here we combine the time-lapse hydrogeophysical imagery with the multivariate statistical technique of Empirical Orthogonal Functions (EOF) in order to isolate the spatial and temporal components of the imagery. Comparisons of soil core information (e.g. soil texture, soil carbon) from around the study site and organized within like spatial zones reveal statistically different mean values of soil properties. Moreover, the like spatial zones can be used to identify a finite number of future sampling locations, evaluation of the placement of existing sensors/chambers, upscale/downscale observations, all of which are desirable techniques for commercial use in precision agriculture. Finally, we note that combining the EOF analysis with continuous monitoring from point sensors or remote sensing products may provide a robust statistical framework for scaling observations through time as well as provide appropriate datasets for use in landscape biogeochemical models.

Soil moisture from ground-based networks and the North American Land Data Assimilation System Phase 2 Model: Are the right values somewhere in between?

NASA Astrophysics Data System (ADS)

Caldwell, T. G.; Scanlon, B. R.; Long, D.; Young, M.

2013-12-01

Soil moisture is the most enigmatic component of the water balance; nonetheless, it is inherently tied to every component of the hydrologic cycle, affecting the partitioning of both water and energy at the land surface. However, our ability to assess soil water storage capacity and status through measurement or modeling is challenged by error and scale. Soil moisture is as difficult to measure as it is to model, yet land surface models and remote sensing products require some means of validation. Here we compare the three major soil moisture monitoring networks across the US, including the USDA Soil Climate Assessment Network (SCAN), NOAA Climate Reference Network (USCRN), and Cosmic Ray Soil Moisture Observing System (COSMOS) to the soil moisture simulated using the North American Land Data Assimilation System (NLDAS) Phase 2. NLDAS runs in near real-time on a 0.125° (12 km) grid over the US, producing ensemble model outputs of surface fluxes and storage. We focus primarily on soil water storage (SWS) in the upper 0-0.1 m zone from the Noah Land Surface Model and secondarily on the effects of error propagation from atmospheric forcing and soil parameterization. No scaling of the observational data was attempted. We simply compared the extracted time series at the nearest grid center from NLDAS and assessed the results by standard model statistics including root mean square error (RMSE) and mean bias estimate (MBE) of the collocated ground station. Observed and modeled data were compared at both hourly and daily mean coordinated universal time steps. In all, ~300 stations were used for 2012. SCAN sites were found to be particularly troublesome at 5- and 10-cm depths. SWS at 163 SCAN sites departed significantly from Noah with a mean R2 of 0.38 × 0.0.23, a mean RMSE of 14.9 mm with a MBE of -13.5 mm. SWS at 111 USCRN sites has a mean R2 of 0.53 × 0.20, a mean RMSE of 8.2 mm with a MBE of -3.7 mm relative to Noah. Finally, 62 COSMOS sites, the instrument with the largest measurement footprint (0.03 km2), we calculated a mean R2 of 0.53 × 0.21, a mean RMSE of 9.7 mm with a MBE of -0.3 mm. Forcing errors and textural misclassifications correlate well with model biases, indicating that scale and structural errors are equally present in NLDAS. Scaling issues aside, these confounding errors make cal/val missions, such as NASA's upcoming Soil Moisture Active Passive (SMAP) mission, problematic without significant quality control and maintenance of for our monitoring networks. Land surface models, such as NLDAS-2, may provide valuable insight into our soil moisture data and somewhere in between the real values likely exist.

Detecting surface runoff location in a small catchment using distributed and simple observation method

NASA Astrophysics Data System (ADS)

Dehotin, Judicaël; Breil, Pascal; Braud, Isabelle; de Lavenne, Alban; Lagouy, Mickaël; Sarrazin, Benoît

2015-06-01

Surface runoff is one of the hydrological processes involved in floods, pollution transfer, soil erosion and mudslide. Many models allow the simulation and the mapping of surface runoff and erosion hazards. Field observations of this hydrological process are not common although they are crucial to evaluate surface runoff models and to investigate or assess different kinds of hazards linked to this process. In this study, a simple field monitoring network is implemented to assess the relevance of a surface runoff susceptibility mapping method. The network is based on spatially distributed observations (nine different locations in the catchment) of soil water content and rainfall events. These data are analyzed to determine if surface runoff occurs. Two surface runoff mechanisms are considered: surface runoff by saturation of the soil surface horizon and surface runoff by infiltration excess (also called hortonian runoff). The monitoring strategy includes continuous records of soil surface water content and rainfall with a 5 min time step. Soil infiltration capacity time series are calculated using field soil water content and in situ measurements of soil hydraulic conductivity. Comparison of soil infiltration capacity and rainfall intensity time series allows detecting the occurrence of surface runoff by infiltration-excess. Comparison of surface soil water content with saturated water content values allows detecting the occurrence of surface runoff by saturation of the soil surface horizon. Automatic records were complemented with direct field observations of surface runoff in the experimental catchment after each significant rainfall event. The presented observation method allows the identification of fast and short-lived surface runoff processes at a small spatial and temporal resolution in natural conditions. The results also highlight the relationship between surface runoff and factors usually integrated in surface runoff mapping such as topography, rainfall parameters, soil or land cover. This study opens interesting prospects for the use of spatially distributed measurement for surface runoff detection, spatially distributed hydrological models implementation and validation at a reasonable cost.

Correlation of in Vitro Cytokine Responses with the Chemical Composition of Soil-Derived Particulate Matter

PubMed Central

Veranth, John M.; Moss, Tyler A.; Chow, Judith C.; Labban, Raed; Nichols, William K.; Walton, John C.; Watson, John G.; Yost, Garold S.

2006-01-01

We treated human lung epithelial cells, type BEAS-2B, with 10–80 μg/cm2 of dust from soils and road surfaces in the western United States that contained particulate matter (PM) < 2.5 μm aerodynamic diameter. Cell viability and cytokine secretion responses were measured at 24 hr. Each dust sample is a complex mixture containing particles from different minerals mixed with biogenic and anthropogenic materials. We determined the particle chemical composition using methods based on the U.S. Environmental Protection Agency Speciation Trends Network (STN) and the National Park Service Interagency Monitoring of Protected Visual Environments (IMPROVE) network. The functionally defined carbon fractions reported by the ambient monitoring networks have not been widely used for toxicology studies. The soil-derived PM2.5 from different sites showed a wide range of potency for inducing the release of the proinflammatory cytokines interleukin-6 (IL-6) and IL-8 in vitro. Univariate regression and multivariate redundancy analysis were used to test for correlation of viability and cytokine release with the concentrations of 40 elements, 7 ions, and 8 carbon fractions. The particles showed positive correlation between IL-6 release and the elemental and pyrolyzable carbon fractions, and the strongest correlation involving crustal elements was between IL-6 release and the aluminum:silicon ratio. The observed correlations between low-volatility organic components of soil- and road-derived dusts and the cytokine release by BEAS-2B cells are relevant for investigation of mechanisms linking specific air pollution particle types with the initiating events leading to airway inflammation in sensitive populations. PMID:16507455

Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2

NASA Technical Reports Server (NTRS)

Rasool, Quazi Z.; Zhang, Rui; Lash, Benjamin; Cohan, Daniel S.; Cooter, Ellen J.; Bash, Jesse O.; Lamsal, Lok N.

2016-01-01

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

The UK Soil Observatory (UKSO) and mySoil app: crowdsourcing and disseminating soil information.

NASA Astrophysics Data System (ADS)

Robinson, David; Bell, Patrick; Emmett, Bridget; Panagos, Panos; Lawley, Russell; Shelley, Wayne

2017-04-01

Digital technologies in terms of web based data portals and mobiles apps offer a new way to provide both information to the public, and to engage the public in becoming involved in contributing to the effort of collecting data through crowdsourcing. We are part of the Landpotential.org consortium which is a global partnership committed to developing and supporting the adoption of freely available technology and tools for sustainable land use management, monitoring, and connecting people across the globe. The mySoil app was launched in 2012 and is an example of a free mobile application downloadable from iTunes and Google Play. It serves as a gateway tool to raise interest in, and awareness of, soils. It currently has over 50,000 dedicated users and has crowd sourced more than 4000 data records. Recent developments have expanded the coverage of mySoil from the United Kingdom to Europe, introduced a new user interface and provided language capability, while the UKSO displays the crowd-sourced records from across the globe. We are now trying to identify which industry, education and citizen sectors are using these platforms and how they can be improved. Please help us by providing feedback or taking the survey on the UKSO website. www.UKSO.org The UKSO is a collaboration between major UK soil-data holders to provide maps, spatial data and real-time temporal data from observing platforms such as the UK soil moisture network. Both UKSO and mySoil have crowdsourcing capability and are slowly building global citizen science maps of soil properties such as pH and texture. Whilst these data can't replace professional monitoring data, the information they provide both stimulates public interest and can act as 'soft data' that can help support the interpretation of monitoring data, or guide future monitoring, identifying areas that don't correspond with current analysis. In addition, soft data can be used to map soils with machine learning approaches, such as SoilGrids.

Remote Monitoring of Post-eruption Volcano Environment Based-On Wireless Sensor Network (WSN): The Mount Sinabung Case

NASA Astrophysics Data System (ADS)

Soeharwinto; Sinulingga, Emerson; Siregar, Baihaqi

2017-01-01

An accurate information can be useful for authorities to make good policies for preventive and mitigation after volcano eruption disaster. Monitoring of environmental parameters of post-eruption volcano provides an important information for authorities. Such monitoring system can be develop using the Wireless Network Sensor technology. Many application has been developed using the Wireless Sensor Network technology, such as floods early warning system, sun radiation mapping, and watershed monitoring. This paper describes the implementation of a remote environment monitoring system of mount Sinabung post-eruption. The system monitor three environmental parameters: soil condition, water quality and air quality (outdoor). Motes equipped with proper sensors, as components of the monitoring system placed in sample locations. The measured value from the sensors periodically sends to data server using 3G/GPRS communication module. The data can be downloaded by the user for further analysis.The measurement and data analysis results generally indicate that the environmental parameters in the range of normal/standard condition. The sample locations are safe for living and suitable for cultivation, but awareness is strictly required due to the uncertainty of Sinabung status.

A 868MHz-based wireless sensor network for ground truthing of soil moisture for a hyperspectral remote sensing campaign - design and preliminary results

NASA Astrophysics Data System (ADS)

Näthe, Paul; Becker, Rolf

2014-05-01

Soil moisture and plant available water are important environmental parameters that affect plant growth and crop yield. Hence, they are significant parameters for vegetation monitoring and precision agriculture. However, validation through ground-based soil moisture measurements is necessary for accessing soil moisture, plant canopy temperature, soil temperature and soil roughness with airborne hyperspectral imaging systems in a corresponding hyperspectral imaging campaign as a part of the INTERREG IV A-Project SMART INSPECTORS. At this point, commercially available sensors for matric potential, plant available water and volumetric water content are utilized for automated measurements with smart sensor nodes which are developed on the basis of open-source 868MHz radio modules, featuring a full-scale microcontroller unit that allows an autarkic operation of the sensor nodes on batteries in the field. The generated data from each of these sensor nodes is transferred wirelessly with an open-source protocol to a central node, the so-called "gateway". This gateway collects, interprets and buffers the sensor readings and, eventually, pushes the data-time series onto a server-based database. The entire data processing chain from the sensor reading to the final storage of data-time series on a server is realized with open-source hardware and software in such a way that the recorded data can be accessed from anywhere through the internet. It will be presented how this open-source based wireless sensor network is developed and specified for the application of ground truthing. In addition, the system's perspectives and potentials with respect to usability and applicability for vegetation monitoring and precision agriculture shall be pointed out. Regarding the corresponding hyperspectral imaging campaign, results from ground measurements will be discussed in terms of their contributing aspects to the remote sensing system. Finally, the significance of the wireless sensor network for the application of ground truthing shall be determined.

Multi-Scale Soil Moisture Monitoring and Modeling at ARS Watersheds for NASA's Soil Moisture Active Passive (SMAP) Calibration/Validation Mission

NASA Astrophysics Data System (ADS)

Coopersmith, E. J.; Cosh, M. H.

2014-12-01

NASA's SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networks. This can be achieved via the integration of NLDAS precipitation data to perform calibration of models at each ­in-situ gauge. In turn, these models and the gauges' volumetric estimations are used to generate soil moisture estimates at a 500m scale throughout a given test watershed by leveraging, at each location, the gauge-calibrated models deemed most appropriate in terms of proximity, calibration efficacy, soil-textural similarity, and topography. Four ARS watersheds, located in Iowa, Oklahoma, Georgia, and Arizona are employed to demonstrate the utility of this approach. The South Fork watershed in Iowa represents the simplest case - the soil textures and topography are relative constants and the variability of soil moisture is simply tied to the spatial variability of precipitation. The Little Washita watershed in Oklahoma adds soil textural variability (but remains topographically simple), while the Little River watershed in Georgia incorporates topographic classification. Finally, the Walnut Gulch watershed in Arizona adds a dense precipitation network to be employed for even finer-scale modeling estimates. Results suggest RMSE values at or below the 4% volumetric standard adopted for the SMAP mission are attainable over the desired spatial scales via this integration of modeling efforts and existing in-situ networks.

Gravity changes, soil moisture and data assimilation

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

USAR Robot Communication Using ZigBee Technology

NASA Astrophysics Data System (ADS)

Tsui, Charles; Carnegie, Dale; Pan, Qing Wei

This paper reports the successful development of an automatic routing wireless network for USAR (urban search and rescue) robots in an artificial rubble environment. The wireless network was formed using ZigBee modules and each module was attached to a micro-controller in order to model a wireless USAR robot. Proof of concept experiments were carried out by deploying the networked robots into artificial rubble. The rubble was simulated by connecting holes and trenches that were dug in 50 cm deep soil. The simulated robots were placed in the bottom of the holes. The holes and trenches were then covered up by various building materials and soil to simulate a real rubble environment. Experiments demonstrated that a monitoring computer placed 10 meters outside the rubble can establish proper communication with all robots inside the artificial rubble environment.

Mass fractal dimension and spectral dimension to characterize different horizons in La Herreria (Sierra de Guadarrama, Spain)

NASA Astrophysics Data System (ADS)

Inclan, Rosa Maria

2016-04-01

Knowledge on three dimensional soil pore architecture is important to improve our understanding of the factors that control a number of critical soil processes as it controls biological, chemical and physical processes at various scales. Computed Tomography (CT) images provide increasingly reliable information about the geometry of pores and solids in soils at very small scale with the benefit that is a non-invasive technique. Fractal formalism has revealed as a useful tool in these cases where highly complex and heterogeneous meda are studied. One of these quantifications is mass dimension (Dm) and spectral dimension (d) applied to describe the water and gas diffusion coefficients in soils (Tarquis et al., 2012). In this work, intact soil samples were collected from the first three horizons of La Herreria soil. This station is located in the lowland mountain area of Sierra de Guadarrama (Santolaria et al., 2015) and it represents a highly degraded type of site as a result of the livestock keeping. The 3D images, of 45.1 micro-m resolution (256x256x256 voxels), were obtained and then binarized following the singularity-CA method (Martín-Sotoca et al. 2016). Based on these images Dm and d were estimated. The results showed an statistical difference in porosity, Dm and d for each horizon. This fact has a direct implication in diffusion parameters for a pore network modeling based on both fractal dimensions. These soil parameters will constitute a basis for site characterization for further studies regarding soil degradation; determining the interaction between soil, plant and atmosphere with respect to human induced activities as well as the basis for several nitrogen and carbon cycles modeling. References Martin Sotoca; J.J. Ana M. Tarquis, Antonio Saa Requejo, and Juan B. Grau (2016). Pore detection in Computed Tomography (CT) soil 3D images using singularity map analysis. Geophysical Research Abstracts, 18, EGU2016-829. Santolaria-Canales, Edmundo and the GuMNet Consortium Team (2015). GuMNet - Guadarrama Monitoring Network. Installation and set up of a high altitude monitoring network, north of Madrid. Spain. Geophysical Research Abstracts, 17, EGU2015-13989-2. Tarquis, A. M., Sanchez, M. E., Antón, J. M., Jimenez, J., Saa-Requejo, A., Andina, D., & Crawford, J. W. (2012). Variation in spectral and mass dimension on three-dimensional soil image processing. Soil Science, 177(2), 88-97. Web: http://www.ucm.es/gumnet/

Position estimation of transceivers in communication networks

DOEpatents

Kent, Claudia A [Pleasanton, CA; Dowla, Farid [Castro Valley, CA

2008-06-03

This invention provides a system and method using wireless communication interfaces coupled with statistical processing of time-of-flight data to locate by position estimation unknown wireless receivers. Such an invention can be applied in sensor network applications, such as environmental monitoring of water in the soil or chemicals in the air where the position of the network nodes is deemed critical. Moreover, the present invention can be arranged to operate in areas where a Global Positioning System (GPS) is not available, such as inside buildings, caves, and tunnels.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Real-Time Alpine Measurement System Using Wireless Sensor Networks

PubMed Central

2017-01-01

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra’s wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape. PMID:29120376

Real-Time Alpine Measurement System Using Wireless Sensor Networks.

PubMed

Malek, Sami A; Avanzi, Francesco; Brun-Laguna, Keoma; Maurer, Tessa; Oroza, Carlos A; Hartsough, Peter C; Watteyne, Thomas; Glaser, Steven D

2017-11-09

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra's wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

Reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cui, Y.; Long, D.; Hong, Y.; Zeng, C.; Han, Z.

2016-12-01

Reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau Yaokui Cui, Di Long, Yang Hong, Chao Zeng, and Zhongying Han State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China Abstract: Soil moisture is a key variable in the exchange of water and energy between the land surface and the atmosphere, especially over the Tibetan Plateau (TP) which is climatically and hydrologically sensitive as the world's third pole. Large-scale consistent and continuous soil moisture datasets are of importance to meteorological and hydrological applications, such as weather forecasting and drought monitoring. The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product is one of relatively new passive microwave products. The FY-3B/MWRI soil moisture product is reconstructed using the back-propagation neural network (BP-NN) based on reconstructed MODIS products, i.e., LST, NDVI, and albedo using different gap-filling methods. The reconstruction method of generating the soil moisture product not only considers the relationship between the soil moisture and the NDVI, LST, and albedo, but also the relationship between the soil moisture and the four-dimensional variation using the longitude, latitude, DEM and day of year (DOY). Results show that the soil moisture could be well reconstructed with R2 larger than 0.63, and RMSE less than 0.1 cm3 cm-3 and bias less than 0.07 cm3 cm-3 for both frozen and unfrozen periods, compared with in-situ measurements in the central TP. The reconstruction method is subsequently applied to generate spatially consistent and temporally continuous surface soil moisture over the TP. The reconstructed FY-3B/MWRI soil moisture product could be valuable in studying meteorology, hydrology, and agriculture over the TP. Keywords: FY-3B/MWRI; Soil moisture; Reconstruction; Tibetan Plateau

Polycyclic aromatic hydrocarbons and polychlorinated biphenyls in soils of Mayabeque, Cuba.

PubMed

Sosa, Dayana; Hilber, Isabel; Faure, Roberto; Bartolomé, Nora; Fonseca, Osvaldo; Keller, Armin; Schwab, Peter; Escobar, Arturo; Bucheli, Thomas D

2017-05-01

Cuba is a country in transition with a considerable potential for economic growth. Soils are recipients and integrators of chemical pollution, a frequent negative side effect of increasing industrial activities. Therefore, we established a soil monitoring network to monitor polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) in soils of Mayabeque, a Cuban province southeast of Havana. Concentrations of the sum of the 16 US EPA PAHs and of the seven IRMM PCBs in soils from 39 locations ranged from 20 to 106 μg kg -1 and from 1.1 to 7.6 μg kg -1 , respectively. While such concentrations can be considered as low overall, they were in several cases correlated with the distance of sampling sites to presumed major emission sources, with some of the concomitantly investigated source diagnostic PAH ratios, and with black carbon content. The presented data adds to the limited information on soil pollution in the Caribbean region and serves as a reference time point before the onset of a possible further industrial development in Cuba. It also forms the basis to set up and adapt national environmental standards.

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.

Localization Strategies in WSNs as applied to Landslide Monitoring (Invited)

NASA Astrophysics Data System (ADS)

Massa, A.; Robol, F.; Polo, A.; Giarola, E.; Viani, F.

2013-12-01

In the last years, heterogeneous integrated smart systems based on wireless sensor network (WSN) technology have been developed at the ELEDIA Research Center of the University of Trento [1]. One of the key features of WSNs as applied to distributed monitoring is that, while the capabilities of each single sensor node is limited, the implementation of cooperative schemes throughout the whole network enables the solution of even complex tasks, as the landslide monitoring. The capability of localizing targets respect to the position of the sensor nodes turns out to be fundamental in those application fields where relative movements arise. The main properties like the target typology, the movement characteristics, and the required localization resolution are different changing the reference scenario. However, the common key issue is still the localization of moving targets within the area covered by the sensor network. Many experiences were preparatory for the challenging activities in the field of landslide monitoring where the basic idea is mostly that of detecting slight soil movements. Among them, some examples of WSN-based systems experimentally applied to the localization of people [2] and wildlife [3] have been proposed. More recently, the WSN backbone as well as the investigated sensing technologies have been customized for monitoring superficial movements of the soil. The relative positions of wireless sensor nodes deployed where high probability of landslide exists is carefully monitored to forecast dangerous events. Multiple sensors like ultrasound, laser, high precision GPS, for the precise measurement of relative distances between the nodes of the network and the absolute positions respect to reference targets have been integrated in a prototype system. The millimeter accuracy in the position estimation enables the detection of small soil modifications and to infer the superficial evolution profile of the landslide. This information locally acquired also represent a fine tuning of large scale satellite acquisitions, usually adopted for remote sensing of landslides. The integration of dense and frequent WSN data within satellite image analysis will enhance the sensing capabilities leading to a multi-resolution and an highly space-time calibrated system. The WSN-based system has been preliminary tested in controlled environments in the ELEDIA laboratories and is now installed in a real test site where an active landslide is evolving. Preliminary data are here presented to assess the feasibility of the investigated solution in landslide monitoring and event forecasting. REFERENCES [1] M. Benedetti, L. Ioriatti, M. Martinelli, and F. Viani, 'Wireless sensor network: a pervasive technology for earth observation,' in IEEE Journal of Selected Topics in App. Earth Obs. And Remote Sens., vol. 3, no. 4, pp. 488-497, 2010. [2] F. Viani, M. Donelli, P. Rocca, G. Oliveri, D. Trinchero, and A. Massa, 'Localization, tracking and imaging of targets in wireless sensor networks,' Radio Science, vol. 46, no. 5, 2011. [3] F. Viani, F. Robol, M. Salucci, E. Giarola, S. De Vigili, M. Rocca, F. Boldrini, G. Benedetti, and A. Massa, 'WSN-based early alert system for preventing wildlife-vehicle collisions in Alps regions - From the laboratory test to the real-world implementation,' 7th European Conference on Antennas and Propagation 2013 (EUCAP2013), Gothenburg, Sweden, April 8-12, 2013.

Spatial structure and scaling of macropores in hydrological process at small catchment scale

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter

2013-04-01

During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video cameras and soil moisture monitoring equipment to obtain the initial data of overland flow occurrence and soil moisture state relationships.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

[Preliminary observation on survival and reproduction of imported Oncomelania snails in water network regions: a simulated experiment].

PubMed

Tian, Jian-Guo; Zhong, Wen-Jiang; Li, Gui-Fu; Peng, Li-Xia; Xiang, Xiao-Ping

2011-04-01

To observe the survival and reproduction of exotic imported Oncomelania snails in water network regions. During a period between May 22, 2008 and August 7, 2009, a study pilot was established in a historical snail habitat in Qingpu District of Shanghai City. A total of 12 soil samples were collected from Qingpu, Jinshan and Songjiang districts and placed in the study area. Active marked adults snails without infections (with a female/male ratio of 1) were placed on soil surface, and the activity, survival and reproduction of snails on soil surface were observed. The temperature during the period of the study was recorded. During the experiment period, the highest temperature was 39 degrees C, the lowest was -3 degrees C, and the average was 20 degrees C. The activity of snails reduced significantly on the soil surface at high temperature in summer and low temperature in winter. There were 91 old snails (5.2%) that moved on soil surface in March and 73 (12.2% ) in June, 2009. A total of 26 and 59 offspring snails were found respectively in April and June, 2009, with average density of 2.17 snails/m2 (26/12) and 4.92 snails/m2 (59/12) respectively. The exotic imported snails can survive and reproduce in water network regions. Further monitoring should be strengthened on the imported snails in these regions.

Integrating Enhanced Grace Terrestrial Water Storage Data Into the U.S. and North American Drought Monitors

NASA Technical Reports Server (NTRS)

Housborg, Rasmus; Rodell, Matthew

2010-01-01

NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations nf the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including ground water. The U.S. and North American Drought Monitors are two of the premier drought monitoring products available to decision-makers for assessing and minimizing drought impacts, but they rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors hy filling this observational gap. Horizontal, vertical and temporal disaggregation of the coarse-resolution GRACE TWS data has been accomplished by assimilating GRACE TWS anomalies into the Catchment Land Surface Model using ensemble Kalman smoother. The Drought Monitors combine several short-term and long-term drought indices and indicators expressed in percentiles as a reference to their historical frequency of occurrence for the location and time of year in question. To be consistent, we are in the process of generating a climatology of estimated soil moisture and ground water based on m 60-year Catchment model simulation which will subsequently be used to convert seven years of GRACE assimilated fields into soil moisture and groundwater percentiles. for systematic incorporation into the objective blends that constitute Drought Monitor baselines. At this stage we provide a preliminary evaluation of GRACE assimilated Catchment model output against independent datasets including soil moisture observations from Aqua AMSR-E and groundwater level observations from the U.S. Geological Survey's Groundwater Climate Response Network.

Nitrogen release from forest soils containing sulfide-bearing sediments

NASA Astrophysics Data System (ADS)

Maileena Nieminen, Tiina; Merilä, Päivi; Ukonmaanaho, Liisa

2014-05-01

Soils containing sediments dominated by metal sulfides cause high acidity and release of heavy metals, when excavated or drained, as the aeration of these sediments causes formation of sulfuric acid. Consequent leaching of acidity and heavy metals can kill tree seedlings and animals such as fish, contaminate water, and corrode concrete and steel. These types of soils are called acid sulfate soils. Their metamorphic equivalents, such as sulfide rich black shales, pose a very similar risk of acidity and metal release to the environment. Until today the main focus in treatment of the acid sulfate soils has been to prevent acidification and metal toxicity to agricultural crop plants, and only limited attention has been paid to the environmental threat caused by the release of acidity and heavy metals to the surrounding water courses. Even less attention is paid on release of major nutrients, such as nitrogen, although these sediments are extremely rich in carbon and nitrogen and present a potentially high microbiological activity. In Europe, the largest cover of acid sulfate soils is found in coastal lowlands of Finland. Estimates of acid sulfate soils in agricultural use range from 1 300 to 3 000 km2, but the area in other land use classes, such as managed peatland forests, is presumably larger. In Finland, 49 500 km2 of peatlands have been drained for forestry, and most of these peatland forests will be at the regeneration stage within 10 to 30 years. As ditch network maintenance is often a prerequisite for a successful establishment of the following tree generation, the effects of maintenance operations on the quality of drainage water should be under special control in peatlands underlain by sulfide-bearing sediments. Therefore, identification of risk areas and effective prevention of acidity and metal release during drain maintenance related soil excavating are great challenges for forestry on coastal lowlands of Finland. The organic and inorganic nitrogen concentrations in drainage water from forested peatland catchments underlain by black shale bedrock have been monitored during a 5-year-period, and they show higher values compared to control areas. In addition, soil solution from seven spruce dominated forests belonging to the Finnish permanent monitoring programme of the EU-Forest Focus-FutMon / pan-European ICP forests Level II network was monitored over a 10-year-period. At one of the sites the chemical properties of the soil reflect the formation of an acid sulfate soil presenting clearly higher nitrogen concentration compared to other sites.

Representative locations from time series of soil water content using time stability and wavelet analysis.

PubMed

Rivera, Diego; Lillo, Mario; Granda, Stalin

2014-12-01

The concept of time stability has been widely used in the design and assessment of monitoring networks of soil moisture, as well as in hydrological studies, because it is as a technique that allows identifying of particular locations having the property of representing mean values of soil moisture in the field. In this work, we assess the effect of time stability calculations as new information is added and how time stability calculations are affected at shorter periods, subsampled from the original time series, containing different amounts of precipitation. In doing so, we defined two experiments to explore the time stability behavior. The first experiment sequentially adds new data to the previous time series to investigate the long-term influence of new data in the results. The second experiment applies a windowing approach, taking sequential subsamples from the entire time series to investigate the influence of short-term changes associated with the precipitation in each window. Our results from an operating network (seven monitoring points equipped with four sensors each in a 2-ha blueberry field) show that as information is added to the time series, there are changes in the location of the most stable point (MSP), and that taking the moving 21-day windows, it is clear that most of the variability of soil water content changes is associated with both the amount and intensity of rainfall. The changes of the MSP over each window depend on the amount of water entering the soil and the previous state of the soil water content. For our case study, the upper strata are proxies for hourly to daily changes in soil water content, while the deeper strata are proxies for medium-range stored water. Thus, different locations and depths are representative of processes at different time scales. This situation must be taken into account when water management depends on soil water content values from fixed locations.

Strengths and weaknesses of temporal stability analysis for monitoring and estimating grid-mean soil moisture in a high-intensity irrigated agricultural landscape

NASA Astrophysics Data System (ADS)

Ran, Youhua; Li, Xin; Jin, Rui; Kang, Jian; Cosh, Michael H.

2017-01-01

Monitoring and estimating grid-mean soil moisture is very important for assessing many hydrological, biological, and biogeochemical processes and for validating remotely sensed surface soil moisture products. Temporal stability analysis (TSA) is a valuable tool for identifying a small number of representative sampling points to estimate the grid-mean soil moisture content. This analysis was evaluated and improved using high-quality surface soil moisture data that were acquired by a wireless sensor network in a high-intensity irrigated agricultural landscape in an arid region of northwestern China. The performance of the TSA was limited in areas where the representative error was dominated by random events, such as irrigation events. This shortcoming can be effectively mitigated by using a stratified TSA (STSA) method, proposed in this paper. In addition, the following methods were proposed for rapidly and efficiently identifying representative sampling points when using TSA. (1) Instantaneous measurements can be used to identify representative sampling points to some extent; however, the error resulting from this method is significant when validating remotely sensed soil moisture products. Thus, additional representative sampling points should be considered to reduce this error. (2) The calibration period can be determined from the time span of the full range of the grid-mean soil moisture content during the monitoring period. (3) The representative error is sensitive to the number of calibration sampling points, especially when only a few representative sampling points are used. Multiple sampling points are recommended to reduce data loss and improve the likelihood of representativeness at two scales.

Aquifer sensitivity to pesticide leaching: Testing a soils and hydrogeologic index method

USGS Publications Warehouse

Mehnert, E.; Keefer, D.A.; Dey, W.S.; Wehrmann, H.A.; Wilson, S.D.; Ray, C.

2005-01-01

For years, researchers have sought index and other methods to predict aquifer sensitivity and vulnerability to nonpoint pesticide contamination. In 1995, an index method and map were developed to define aquifer sensitivity to pesticide leaching based on a combination of soil and hydrogeologic factors. The soil factor incorporated three soil properties: hydraulic conductivity, amount of organic matter within individual soil layers, and drainage class. These properties were obtained from a digital soil association map. The hydrogeologic factor was depth to uppermost aquifer material. To test this index method, a shallow ground water monitoring well network was designed, installed, and sampled in Illinois. The monitoring wells had a median depth of 7.6 m and were located adjacent to corn and soybean fields where the only known sources of pesticides were those used in normal agricultural production. From September 1998 through February 2001, 159 monitoring wells were sampled for 14 pesticides but no pesticide metabolites. Samples were collected and analyzed to assess the distribution of pesticide occurrence across three units of aquifer sensitivity. Pesticides were detected in 18% of all samples and nearly uniformly from samples from the three units of aquifer sensitivity. The new index method did not predict pesticide occurrence because occurrence was not dependent on the combined soil and hydrogeologic factors. However, pesticide occurrence was dependent on the tested hydrogeologic factor and was three times higher in areas where the depth to the uppermost aquifer was <6 m than in areas where the depth to the uppermost aquifer was 6 to <15 m. Copyright ?? 2005 National Ground Water Association.

Development of a Three Dimensional Wireless Sensor Network for Terrain-Climate Research in Remote Mountainous Environments

NASA Astrophysics Data System (ADS)

Kavanagh, K.; Davis, A.; Gessler, P.; Hess, H.; Holden, Z.; Link, T. E.; Newingham, B. A.; Smith, A. M.; Robinson, P.

2011-12-01

Developing sensor networks that are robust enough to perform in the world's remote regions is critical since these regions serve as important benchmarks compared to human-dominated areas. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. We aim to overcome these challenges by developing a three-dimensional sensor network arrayed across a topoclimatic gradient (1100-1800 meters) in a wilderness area in central Idaho. Development of this sensor array builds upon advances in sensing, networking, and power supply technologies coupled with experiences of the multidisciplinary investigators in conducting research in remote mountainous locations. The proposed gradient monitoring network will provide near real-time data from a three-dimensional (3-D) array of sensors measuring biophysical parameters used in ecosystem process models. The network will monitor atmospheric carbon dioxide concentration, humidity, air and soil temperature, soil water content, precipitation, incoming and outgoing shortwave and longwave radiation, snow depth, wind speed and direction, tree stem growth and leaf wetness at time intervals ranging from seconds to days. The long-term goal of this project is to realize a transformative integration of smart sensor networks adaptively communicating data in real-time to ultimately achieve a 3-D visualization of ecosystem processes within remote mountainous regions. Process models will be the interface between the visualization platforms and the sensor network. This will allow us to better predict how non-human dominated terrestrial and aquatic ecosystems function and respond to climate dynamics. Access to the data will be ensured as part of the Northwest Knowledge Network being developed at the University of Idaho, through ongoing Idaho NSF-funded cyber infrastructure initiatives, and existing data management systems funded by NSF, such as the CUAHSI Hydrologic Information System (HIS). These efforts will enhance cross-disciplinary understanding of natural and anthropogenic influences on ecosystem function and ultimately inform decision-making.

Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

USGS Publications Warehouse

Gu, Yingxin; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, Jesslyn F.; Verdin, J.P.

2008-01-01

The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

[Evaluation of environmental conditions: air, water and soil in areas of mining activity in Boyacá, Colombia].

PubMed

Agudelo-Calderón, Carlos A; Quiroz-Arcentales, Leonardo; García-Ubaque, Juan C; Robledo-Martínez, Rocío; García-Ubaque, Cesar A

2016-02-01

Objectives To determine concentrations of PM10, mercury and lead in indoor air of homes, water sources and soil in municipalities near mining operations. Method 6 points were evaluated in areas of influence and 2 in control areas. For measurements of indoor air, we used the NIOSH 600 method (PM10), NIOSH 6009 (mercury) and NIOSH 7300 (lead). For water analysis we used the IDEAM Guide for monitoring discharges. For soil analysis, we used the cold vapor technique (mercury) and atomic absorption (lead). Results In almost all selected households, the average PM10 and mercury concentrations in indoor air exceeded applicable air quality standards. Concentrations of lead were below standard levels. In all water sources, high concentrations of lead were found and in some places within the mining areas, high levels of iron, aluminum and mercury were also found. In soil, mercury concentrations were below the detection level and for lead, differences between the monitored points were observed. Conclusions The results do not establish causal relationships between mining and concentration of these pollutants in the evaluated areas because of the multiplicity of sources in the area. However, such studies provide important information, useful to agents of the environmental health system and researchers. Installation of networks for environmental monitoring to obtain continuous reports is suggested.

Designing a national soil erosion monitoring network for England and Wales

NASA Astrophysics Data System (ADS)

Lark, Murray; Rawlins, Barry; Anderson, Karen; Evans, Martin; Farrow, Luke; Glendell, Miriam; James, Mike; Rickson, Jane; Quine, Timothy; Quinton, John; Brazier, Richard

2014-05-01

Although soil erosion is recognised as a significant threat to sustainable land use and may be a priority for action in any forthcoming EU Soil Framework Directive, those responsible for setting national policy with respect to erosion are constrained by a lack of robust, representative, data at large spatial scales. This reflects the process-orientated nature of much soil erosion research. Recognising this limitation, The UK Department for Environment, Food and Rural Affairs (Defra) established a project to pilot a cost-effective framework for monitoring of soil erosion in England and Wales (E&W). The pilot will compare different soil erosion monitoring methods at a site scale and provide statistical information for the final design of the full national monitoring network that will: provide unbiased estimates of the spatial mean of soil erosion rate across E&W (tonnes ha-1 yr-1) for each of three land-use classes - arable and horticultural grassland upland and semi-natural habitats quantify the uncertainty of these estimates with confidence intervals. Probability (design-based) sampling provides most efficient unbiased estimates of spatial means. In this study, a 16 hectare area (a square of 400 x 400 m) positioned at the centre of a 1-km grid cell, selected at random from mapped land use across E&W, provided the sampling support for measurement of erosion rates, with at least 94% of the support area corresponding to the target land use classes. Very small or zero erosion rates likely to be encountered at many sites reduce the sampling efficiency and make it difficult to compare different methods of soil erosion monitoring. Therefore, to increase the proportion of samples with larger erosion rates without biasing our estimates, we increased the inclusion probability density in areas where the erosion rate is likely to be large by using stratified random sampling. First, each sampling domain (land use class in E&W) was divided into strata; e.g. two sub-domains within which, respectively, small or no erosion rates, and moderate or larger erosion rates are expected. Each stratum was then sampled independently and at random. The sample density need not be equal in the two strata, but is known and is accounted for in the estimation of the mean and its standard error. To divide the domains into strata we used information on slope angle, previous interpretation of erosion susceptibility of the soil associations that correspond to the soil map of E&W at 1:250 000 (Soil Survey of England and Wales, 1983), and visual interpretation of evidence of erosion from aerial photography. While each domain could be stratified on the basis of the first two criteria, air photo interpretation across the whole country was not feasible. For this reason we used a two-phase random sampling for stratification (TPRS) design (de Gruijter et al., 2006). First, we formed an initial random sample of 1-km grid cells from the target domain. Second, each cell was then allocated to a stratum on the basis of the three criteria. A subset of the selected cells from each stratum were then selected for field survey at random, with a specified sampling density for each stratum so as to increase the proportion of cells where moderate or larger erosion rates were expected. Once measurements of erosion have been made, an estimate of the spatial mean of the erosion rate over the target domain, its standard error and associated uncertainty can be calculated by an expression which accounts for the estimated proportions of the two strata within the initial random sample. de Gruijter, J.J., Brus, D.J., Biekens, M.F.P. & Knotters, M. 2006. Sampling for Natural Resource Monitoring. Springer, Berlin. Soil Survey of England and Wales. 1983 National Soil Map NATMAP Vector 1:250,000. National Soil Research Institute, Cranfield University.

Enhanced representation of soil NO emissions in the ...

EPA Pesticide Factsheets

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12 km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and

Soil and geomorphological parameters to characterize natural environmental and human induced changes within the Guadarrama Range (Central Spain)

NASA Astrophysics Data System (ADS)

Schmid, Thomas; Inclán-Cuartas, Rosa M.; Santolaria-Canales, Edmundo; Saa, Antonio; Rodríguez-Rastrero, Manuel; Tanarro-Garcia, Luis M.; Luque, Esperanza; Pelayo, Marta; Ubeda, Jose; Tarquis, Ana; Diaz-Puente, Javier; De Marcos, Javier; Rodriguez-Alonso, Javier; Hernandez, Carlos; Palacios, David; Gallardo-Díaz, Juan; Fidel González-Rouco, J.

2016-04-01

Mediterranean mountain ecosystems are often complex and remarkably diverse and are seen as important sources of biological diversity. They play a key role in the water and sediment cycle for lowland regions as well as preventing and mitigating natural hazards especially those related to drought such as fire risk. However, these ecosystems are fragile and vulnerable to changes due to their particular and extreme climatic and biogeographic conditions. Some of the main pressures on mountain biodiversity are caused by changes in land use practices, infrastructure and urban development, unsustainable tourism, overexploitation of natural resources, fragmentation of habitats, particularly when located close to large population centers, as well as by pressures related toclimate change. The objective of this work is to select soil and geomorphological parameters in order to characterize natural environmental and human induced changes within the newly created National Park of the Sierra de Guadarrama in Central Spain, where the presence of the Madrid metropolitan area is the main factor of impact. This is carried out within the framework of the Guadarrama Monitoring Network (GuMNet) of the Campus de ExcelenciaInternacionalMoncloa, where long-term monitoring of the atmosphere, soil and bedrock are priority. This network has a total of ten stations located to the NW of Madrid and in this case, three stations have been selected to represent different ecosystems that include: 1) an alluvial plain in a lowland pasture area (La Herreria at 920 m a.s.l.), 2) mid mountain pine-forested and pasture area (Raso del Pino at 1801 m a.s.l.) and 3) high mountain grassland and rock area (Dos Hermanas at 2225 m a.s.l.). At each station a site geomorphological description, soil profile description and sampling was carried out. In the high mountain area information was obtained for monitoring frost heave activity and downslope soil movement. Basic soil laboratory analyses have been carried out to determine the physical and chemical soil properties. The parent material is gneiss andassociated deposits and, as a result, soils are acid. The soils have a low to medium organic matter content and are non-saline. They are moderately to well drained soils and have no or slight evidence of erosion. The soil within the high mountain area has clear evidence of frost heave that has a vertical displacement of the surface in the centimeter range. The stations within the lowland and mid mountain areas represent the most degraded sites as a result of the livestock keeping, whereas the high mountain area is mainly influenced by natural environmental conditions. These soil and geomorphological parameters will constitute a basis for site characterization in future studies regarding soil degradation; determining the interaction between soil, vegetation and atmosphere with respect to human induced activities (e.g. atmospheric contamination and effects of fires); determining the nitrogen and carbon cycles; and the influence of heavy metal contaminants in the soils.

Spatial-temporal variability of soil moisture and its estimation across scales

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2010-02-01

The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most "representative" field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the "nonrepresentative" fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.

Measuring ecological function on California's rangelands

NASA Astrophysics Data System (ADS)

Porzig, E.

2016-12-01

There is a need for a better understanding of ecosystem processes on rangelands and how management decisions influence these processes on scales that are both ecologically and socially relevant. Point Blue Conservation Science's Rangeland Monitoring Network is a coordinated effort to collect standardized data on birds, vegetation, and soils on rangelands throughout California. We work with partners, including private landowners, land trusts, state and federal agencies, and others, to measure bird and plant abundance and diversity and three soil dynamic properties (water infiltration, bulk density, and organic carbon). Here, we present data from our first two years of monitoring on over 50 ranches in 17 counties. By collecting data on the scope and scale of variation in ecological function across rangelands and the relationship with management practices, we aim to advance rangeland management, restoration, and conservation.

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.

Satellite Radar Interferometry For Risk Management Of Gas Pipeline Networks

NASA Astrophysics Data System (ADS)

Ianoschi, Raluca; Schouten, Mathijs; Bas Leezenberg, Pieter; Dheenathayalan, Prabu; Hanssen, Ramon

2013-12-01

InSAR time series analyses can be fine-tuned for specific applications, yielding a potential increase in benchmark density, precision and reliability. Here we demonstrate the algorithms developed for gas pipeline monitoring, enabling operators to precisely pinpoint unstable locations. This helps asset management in planning, prioritizing and focusing in-situ inspections, thus reducing maintenance costs. In unconsolidated Quaternary soils, ground settlement contributes to possible failure of brittle cast iron gas pipes and their connections to houses. Other risk factors include the age and material of the pipe. The soil dynamics have led to a catastrophic explosion in the city of Amsterdam, which triggered an increased awareness for the significance of this problem. As the extent of the networks can be very wide, InSAR is shown to be a valuable source of information for identifying the hazard regions. We monitor subsidence affecting an urban gas transportation network in the Netherlands using both medium and high resolution SAR data. Results for the 2003-2010 period provide clear insights on the differential subsidence rates in the area. This enables characterization of underground motion that affects the integrity of the pipeline. High resolution SAR data add extra detail of door-to-door pipeline connections, which are vulnerable due to different settlements between house connections and main pipelines. The rates which we measure represent important input in planning of maintenance works. Managers can decide the priority and timing for inspecting the pipelines. The service helps manage the risk and reduce operational cost in gas transportation networks.

Regional Evapotranspiration Estimation by Using Wireless Sap Flow and Soil Moisture Measurement Systems

NASA Astrophysics Data System (ADS)

Kuo, C.; Yu, P.; Yang, T.; Davis, T. W.; Liang, X.; Tseng, C.; Cheng, C.

2011-12-01

The objective of this study proposed herein is to estimate regional evapotranspiration via sap flow and soil moisture measurements associated with wireless sensor network in the field. Evapotranspiration is one of the important factors in water balance computation. Pan evaporation collected from the meteorological station can only be accounted as a single-point scale measurement rather than the water loss of the entire region. Thus, we need a multiple-site measurement for understanding the regional evapotranspiration. Applying sap flow method with self-made probes, we could calculate transpiration. Soil moisture measurement was used to monitor the daily soil moisture variety for evaporation. Sap flow and soil moisture measurements in multiple sites are integrated by using wireless sensor network (WSN). Then, the measurement results of each site were scaled up and combined into the regional evapotranspiration. This study used thermal dissipation method to measure sap flow in trees to represent the plant transpiration. Sap flow was measured by using the self-made sap probes which needed to be calibrated before setting up at the observation field. Regional transpiration was scaled up through the Leaf Area Index (LAI). The LAI of regional scale was from the MODIS image calculated at 1km X 1km grid size. The soil moistures collected from areas outside the distributing area of tree roots and tree canopy were used to represent the evaporation. The observation was undertaken to collect soil moisture variety from five different soil depths of 10, 20, 30, 40 and 50 cm respectively. The regional evaporation can be estimated by averaging the variation of soil moisture from each site within the region. The result data measured by both sap flow and soil moisture measurements of each site were collected through the wireless sensor network. The WSN performs the functions of P2P and mesh networking. That can collect data in multiple locations simultaneously and has less power consumption. WSN is the best way for collecting sap flow and soil moisture data in this study. Since the data were collected through the radio in the field, there may have some noise randomly. The weighted least-squares method was used to filter the raw data. Through collecting the observation data by WSN and transferring them into regional scale, we could get regional evapotranspiration.

NY-uHMT: A dense hydro-meteorological network to characterize urban land-atmosphere interactions

NASA Astrophysics Data System (ADS)

Ramamurthy, P.; Lakhankar, T.; Khanbilvardi, R.; Devineni, N.

2016-12-01

Most people in the US live in large Metropolitan areas that have a dense urban core in the center, dominated by built surfaces and surrounded by residential/suburban areas that consist a mix of built, vegetated and permeable surfaces. This creates a gradient in the hydro-meteorological environment giving rise to complex land-atmosphere interactions. Current modeling platforms and observational techniques like tower measurements do not adequately account for the underlying heterogeneity. To address this critical gap in our understanding we have instituted a dense network of sensors in the New York Metropolitan area. This unique urban sensor network consists of instrumentation to monitor soil moisture at multiple depths along with air temperature, relative humidity and precipitation, with room to add additional sensors in the future. The network is autonomous and connected to a centralized server using cellular towers. Apart from describing the spatial variability in hydro-meteorological quantities the network will also aid in conducting high-resolution numerical simulations to study and forecast urban weather and climate. In one such simulation conducted to partition the influence of storage flux, wind pattern and circulation and soil moisture deficit on urban heat island intensity (UHI), we found that the daily variability in UHI in NYC was sensitive to available energy and wind pattern. The long-term trend in UHI was however related to soil moisture deficit. In fact a prolonged heat wave period witnessed during summer 2006 correlated well with an extended dry period and the daily UHI in NYC almost doubled. Moreover, the urban soils also suffered from high degree of dessication, owing to drier urban boundary layer.

Identifying and closing gaps in environmental monitoring by means of metadata, ecological regionalization and geostatistics using the UNESCO biosphere reserve Rhoen (Germany) as an example.

PubMed

Schröder, Winfried; Pesch, Roland; Schmidt, Gunther

2006-03-01

In Germany, environmental monitoring is intended to provide a holistic view of the environmental condition. To this end the monitoring operated by the federal states must use harmonized, resp., standardized methods. In addition, the monitoring sites should cover the ecoregions without any geographical gaps, the monitoring design should have no gaps in terms of ecologically relevant measurement parameters, and the sample data should be spatially without any gaps. This article outlines the extent to which the Rhoen Biosphere Reserve, occupying a part of the German federal states of Bavaria, Hesse and Thuringia, fulfills the listed requirements. The investigation considered collection, data banking and analysis of monitoring data and metadata, ecological regionalization and geostatistics. Metadata on the monitoring networks were collected by questionnaires and provided a complete inventory and description of the monitoring activities in the reserve and its surroundings. The analysis of these metadata reveals that most of the monitoring methods are harmonized across the boundaries of the three federal states the Rhoen is part of. The monitoring networks that measure precipitation, surface water levels, and groundwater quality are particularly overrepresented in the central ecoregions of the biosphere reserve. Soil monitoring sites are more equally distributed within the ecoregions of the Rhoen. The number of sites for the monitoring of air pollutants is not sufficient to draw spatially valid conclusions. To fill these spatial gaps, additional data on the annual average values of the concentrations of air pollutants from monitoring sites outside of the biosphere reserve had therefore been subject to geostatistical analysis and estimation. This yields valid information on the spatial patterns and temporal trends of air quality. The approach illustrated is applicable to similar cases, as, for example, the harmonization of international monitoring networks.

Forest vegetation monitoring protocol for National Parks in the North Coast and Cascades Network

Treesearch

Andrea Woodward; Karen M. Hutten; John R. Boetsch; Steven A. Acker; Regina M. Rochefort; Mignonne M. Bivin; Laurie L. Kurth

2009-01-01

Plant communities are the foundation for terrestrial trophic webs and animal habitat, and their structure and species composition are an integrated result of biological and physical drivers (Gates, 1993). Additionally, they have a major role in geologic, geomorphologic and soil development processes (Jenny, 1941; Stevens and Walker, 1970). Throughout most of the...

Analysis of spatiotemporal soil moisture patterns at the catchment scale using a wireless sensor network

NASA Astrophysics Data System (ADS)

Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry

2010-05-01

Soil water content plays a key role in partitioning water and energy fluxes and controlling the pattern of groundwater recharge. Despite the importance of soil water content, it is not yet measured in an operational way at larger scales. The aim of this paper is to present the potential of real-time monitoring for the analysis of soil moisture patterns at the catchment scale using the recently developed wireless sensor network SoilNet [1], [2]. SoilNet is designed to measure soil moisture, salinity and temperature in several depths (e.g. 5, 20 and 50 cm). Recently, a small forest catchment Wüstebach (~27 ha) has been instrumented with 150 sensor nodes and more than 1200 soil sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories). From August to November 2009, more than 6 million soil moisture measurements have been performed. We will present first results from a statistical and geostatistical analysis of the data. The observed spatial variability of soil moisture corresponds well with the 800-m scale variability described in [3]. The very low scattering of the standard deviation versus mean soil moisture plots indicates that sensor network data shows less artificial soil moisture variations than soil moisture data originated from measurement campaigns. The variograms showed more or less the same nugget effect, which indicates that the sum of the sub-scale variability and the measurement error is rather time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil water content, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to lateral and vertical water fluxes. Topographic features showed the strongest correlation with soil moisture during dry periods, indicating that the control of topography on the soil moisture pattern depends on the soil water status. Interpolation using the external drift kriging method demonstrated that the high sampling density allows capturing the key patterns of soil moisture variation in the Wüstebach catchment. References: [1] Bogena, H.R., J.A. Huisman, C. Oberdörster, H. Vereecken (2007): Evaluation of a low-cost soil water content sensor for wireless network applications. Journal of Hydrology: 344, 32- 42. [2] Rosenbaum, U., Huisman, J.A., Weuthen, A., Vereecken, H. and Bogena, H.R. (2010): Quantification of sensor-to-sensor variability of the ECH2O EC-5, TE and 5TE sensors in dielectric liquids. Accepted for publication in Vadose Zone Journal (09/2009). [3] Famiglietti J.S., D. Ryu, A. A. Berg, M. Rodell and T. J. Jackson (2008), Field observations of soil moisture variability across scales, Water Resour. Res. 44, W01423, doi:10.1029/2006WR005804.

Hydrologic and geochemical data collected near Skewed Reservoir, an impoundment for coal-bed natural gas produced water, Powder River Basin, Wyoming

USGS Publications Warehouse

Healy, Richard W.; Rice, Cynthia A.; Bartos, Timothy T.

2012-01-01

The Powder River Structural Basin is one of the largest producers of coal-bed natural gas (CBNG) in the United States. An important environmental concern in the Basin is the fate of groundwater that is extracted during CBNG production. Most of this produced water is disposed of in unlined surface impoundments. A 6-year study of groundwater flow and subsurface water and soil chemistry was conducted at one such impoundment, Skewed Reservoir. Hydrologic and geochemical data collected as part of that study are contained herein. Data include chemistry of groundwater obtained from a network of 21 monitoring wells and three suction lysimeters and chemical and physical properties of soil cores including chemistry of water/soil extracts, particle-size analyses, mineralogy, cation-exchange capacity, soil-water content, and total carbon and nitrogen content of soils.

Multi-model perspectives and inter-comparison of soil moisture and evapotranspiration in East Africa—an application of Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS)

NASA Astrophysics Data System (ADS)

Pervez, M. S.; McNally, A.; Arsenault, K. R.

2017-12-01

Convergence of evidence from different agro-hydrologic sources is particularly important for drought monitoring in data sparse regions. In Africa, a combination of remote sensing and land surface modeling experiments are used to evaluate past, present and future drought conditions. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) routinely simulates daily soil moisture, evapotranspiration (ET) and other variables over Africa using multiple models and inputs. We found that Noah 3.3, Variable Infiltration Capacity (VIC) 4.1.2, and Catchment Land Surface Model based FLDAS simulations of monthly soil moisture percentile maps captured concurrent drought and water surplus episodes effectively over East Africa. However, the results are sensitive to selection of land surface model and hydrometeorological forcings. We seek to identify sources of uncertainty (input, model, parameter) to eventually improve the accuracy of FLDAS outputs. In absence of in situ data, previous work used European Space Agency Climate Change Initiative Soil Moisture (CCI-SM) data measured from merged active-passive microwave remote sensing to evaluate FLDAS soil moisture, and found that during the high rainfall months of April-May and November-December Noah-based soil moisture correlate well with CCI-SM over the Greater Horn of Africa region. We have found good correlations (r>0.6) for FLDAS Noah 3.3 ET anomalies and Operational Simplified Surface Energy Balance (SSEBop) ET over East Africa. Recently, SSEBop ET estimates (version 4) were improved by implementing a land surface temperature correction factor. We re-evaluate the correlations between FLDAS ET and version 4 SSEBop ET. To further investigate the reasons for differences between models we evaluate FLDAS soil moisture with Advanced Scatterometer and SMAP soil moisture and FLDAS outputs with MODIS and AVHRR normalized difference vegetation index. By exploring longer historic time series and near-real time products we will be aiding convergence of evidence for better understanding of historic drought, improved monitoring and forecasting, and better understanding of uncertainties of water availability estimation over Africa

40 CFR 265.278 - Unsaturated zone (zone of aeration) monitoring.

Code of Federal Regulations, 2012 CFR

2012-07-01

... soils nearby; this background monitoring must be conducted before or in conjunction with the monitoring... a minimum: (1) Soil monitoring using soil cores, and (2) Soil-pore water monitoring using devices... demonstrate in his unsaturated zone monitoring plan that: (1) The depth at which soil and soil-pore water...

40 CFR 265.278 - Unsaturated zone (zone of aeration) monitoring.

Code of Federal Regulations, 2011 CFR

2011-07-01

... soils nearby; this background monitoring must be conducted before or in conjunction with the monitoring... a minimum: (1) Soil monitoring using soil cores, and (2) Soil-pore water monitoring using devices... demonstrate in his unsaturated zone monitoring plan that: (1) The depth at which soil and soil-pore water...

40 CFR 265.278 - Unsaturated zone (zone of aeration) monitoring.

Code of Federal Regulations, 2010 CFR

2010-07-01

... soils nearby; this background monitoring must be conducted before or in conjunction with the monitoring... a minimum: (1) Soil monitoring using soil cores, and (2) Soil-pore water monitoring using devices... demonstrate in his unsaturated zone monitoring plan that: (1) The depth at which soil and soil-pore water...

40 CFR 265.278 - Unsaturated zone (zone of aeration) monitoring.

Code of Federal Regulations, 2014 CFR

2014-07-01

... soils nearby; this background monitoring must be conducted before or in conjunction with the monitoring... a minimum: (1) Soil monitoring using soil cores, and (2) Soil-pore water monitoring using devices... demonstrate in his unsaturated zone monitoring plan that: (1) The depth at which soil and soil-pore water...

40 CFR 265.278 - Unsaturated zone (zone of aeration) monitoring.

Code of Federal Regulations, 2013 CFR

2013-07-01

... soils nearby; this background monitoring must be conducted before or in conjunction with the monitoring... a minimum: (1) Soil monitoring using soil cores, and (2) Soil-pore water monitoring using devices... demonstrate in his unsaturated zone monitoring plan that: (1) The depth at which soil and soil-pore water...

Basal area growth of sugar maple in relation to acid deposition, stand health, and soil nutrients.

PubMed

Duchesne, Louis; Ouimet, Rock; Houle, Daniel

2002-01-01

Previous studies have shown in noncalcareous soils that acid deposition may have increased soil leaching of basic cations above the input rate from soil weathering and atmospheric depositions. This phenomenon may have increased soil acidity levels, and, as a consequence, may have reduced the availability of these essential nutrients for forest growth. Fourteen plots of the Forest Ecosystem Research and Monitoring Network in Québec were used to examine the relation between post-industrial growth trends of sugar maple (Acer saccharum Marsh.) and acid deposition (N and S), stand decline rate, and soil exchangeable nutrient concentrations. Atmospheric N and S deposition and soil exchangeable acidity were positively associated with stand decline rate, and negatively with the average tree basal area increment trend. The growth rate reduction reached on average 17% in declining stands compared with healthy ones. The results showed a significant sugar maple growth rate reduction since 1960 on acid soils. The appearance of the forest decline phenomenon in Québec can be attributed, at least partially, to soil acidification and acid deposition levels.

Airborne Detection and Tracking of Geologic Leakage Sites

NASA Astrophysics Data System (ADS)

Jacob, Jamey; Allamraju, Rakshit; Axelrod, Allan; Brown, Calvin; Chowdhary, Girish; Mitchell, Taylor

2014-11-01

Safe storage of CO2 to reduce greenhouse gas emissions without adversely affecting energy use or hindering economic growth requires development of monitoring technology that is capable of validating storage permanence while ensuring the integrity of sequestration operations. Soil gas monitoring has difficulty accurately distinguishing gas flux signals related to leakage from those associated with meteorologically driven changes of soil moisture and temperature. Integrated ground and airborne monitoring systems are being deployed capable of directly detecting CO2 concentration in storage sites. Two complimentary approaches to detecting leaks in the carbon sequestration fields are presented. The first approach focuses on reducing the requisite network communication for fusing individual Gaussian Process (GP) CO2 sensing models into a global GP CO2 model. The GP fusion approach learns how to optimally allocate the static and mobile sensors. The second approach leverages a hierarchical GP-Sigmoidal Gaussian Cox Process for airborne predictive mission planning to optimally reducing the entropy of the global CO2 model. Results from the approaches will be presented.

Approach of regionalisation c-stocks in forest soils on a national level

NASA Astrophysics Data System (ADS)

Wellbrock, Nicole; Höhle, Juliane; Dühnelt, Petra; Holzhausen, Marieanna

2010-05-01

Introduction In December 2006, the German government decided to manage forests as carbon sinks to reduce greenhouse gas emissions in accordance with Article 3.4 of the Kyoto Protocol. The National Forest Monitoring data contribute to the fulfilment of these reporting commitments. In Germany, National Forest Monitoring includes the systematical extensive National Soil Condition Survey (BZE) and the detailed case studies (Level-II) which determine the processes within forests. This complex monitoring system is appropriate to Germany's greenhouse gas reporting (THG 2008 to 2012). The representative BZE plots can be used to obtain regional data for the National Carbon Stock Inventory. Here, an approach adopting a combination of geostatistics and regression analysis is preferred. The difficulty of showing the statistical significance of expected small changes while carbon stocks are generally high is one of the major challenges in carbon stock monitoring. However, through intensive preparation and cooperation with the forestry authorities of each federal state, the errors uncured in determining changes in carbon stocks in forest soils, which must be stipulated in greenhouse gas monitoring, could be minimised. In contrast to the detailed soil case studies, in which essentially the sources of error occur repeatedly in carbon stock change calculations, the BZE data can be stratified to form plots with homogenous properties, thereby reducing the standard error of estimate. Subsequently, the results of the stratification are projected across Germany, the reporting unit for greenhouse gas monitoring. National Forest Monitoring The BZE represents a national, systematic sampling inventory of the condition of forest soils. The first BZE inventory (BZE I: 1987 to 1993) was carried out on a systematic 8 x 8 km grid on the same sampling plots adopted in the Forest Condition Survey (WZE). In some areas the network of sampling plots involves 1900 grid points. The first BZE I survey was repeated after 15 years, between 2006 and 2008, by the national and the state authorities in cooperation. Afterwards, extensive laboratory and statistical analyses were conducted. Necessary parameters are listed in table 1. Upscaling approach There are different approaches for presenting extensive carbon stock data (Baritz et al., 2006). The availability of georeference plots means one can merge the point data with map data. In Germany, an approach was tested that used homogenous soil areas und plot-information from the national soil inventory. For every soil area c-stocks were regionalised. Only information form BZE-plots were involved which were characteristic for the soil area. The indicators were soil type and substrate class. For every soil area the forest areas were taken in account to calculate c-stock per forest area. The sum of every c-stock per soil area is the c-stock in forest soils of Germany. Tab.1: List of parameters for the carbon inventory (BZE II) Components Parameters Point level Field sampling Width of depth classes, Fine roots, humus (< 2 cm), dry bulk density, stone content, area of humus layer sampled, height a.s.l., litterfall, deadwood (from 10 cm) Analysis C content, fine soil fraction, weight of humus layer, Carbon stock calculations Carbon stock Regional Level Plot Soil type, parent material, vegetation type or forest Regionalisation Soil and land use maps, statistical models, ecological regions, digital elevation models, climate regions

GENASIS national and international monitoring networks for persistent organic pollutants

NASA Astrophysics Data System (ADS)

Brabec, Karel; Dušek, Ladislav; Holoubek, Ivan; Hřebíček, Jiří; Kubásek, Miroslav; Urbánek, Jaroslav

2010-05-01

Persistent organic pollutants (POPs) remain in the centre of scientific attention due to their slow rates of degradation, their toxicity, and potential for both long-range transport and bioaccumulation in living organisms. This group of compounds covers large number of various chemicals from industrial products, such as polychlorinated biphenyls, etc. The GENASIS (Global Environmental Assessment and Information System) information system utilizes data from national and international monitoring networks to obtain as-complete-as-possible set of information and a representative picture of environmental contamination by persistent organic pollutants (POPs). There are data from two main datasets on POPs monitoring: 1.Integrated monitoring of POPs in Košetice Observatory (Czech Republic) which is a long term background site of the European Monitoring and Evaluation Programme (EMEP) for the Central Europe; the data reveals long term trends of POPs in all environmental matrices. The Observatory is the only one in Europe where POPs have been monitored not only in ambient air, but also in wet atmospheric deposition, surface waters, sediments, soil, mosses and needles (integrated monitoring). Consistent data since the year 1996 are available, earlier data (up to 1998) are burdened by high variability and high detection limits. 2.MONET network is ambient air monitoring activities in the Central and Eastern European region (CEEC), Central Asia, Africa and Pacific Islands driven by RECETOX as the Regional Centre of the Stockholm Convention for the region of Central and Eastern Europe under the common name of the MONET networks (MONitoring NETwork). For many of the participating countries these activities generated first data on the atmospheric levels of POPs. The MONET network uses new technologies of air passive sampling, which was developed, tested, and calibrated by RECETOX in cooperation with Environment Canada and Lancaster University, and was originally launched as a model monitoring network providing public administration, private subject, and general public information about air pollution by POPs that had not been previously regularly monitored and whose measurement is further required by global monitoring plan of the Stockholm Convention. The MONET network is international project with many participants. Monitoring in the MONET-CZ network started in 2004 with the pilot project and continues to the current days, MONET CEEC started in 2006 and continues nowadays, MONET Africa started in 2008. The database of the GENASIS systems currently covers MONET-CZ data until the year 2008. The MONET network currently covers 37 countries in the Europe, Asia and Africa with more than 350 sampling sites. The paper will discuss about following topics * Data Fusion in GENASIS: how can GENASIS maximize the value and accuracy of the information gathered from heterogeneous data sources? * Sensor types in GENASIS: which POPs can be measured; what are the physical limitations to achievable accuracy, reliability, and long-term stability of miniaturized sensors; which applications can (not) be realized within these limitations?

Validation and reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cui, Yaokui; Long, Di; Hong, Yang; Zeng, Chao; Zhou, Jie; Han, Zhongying; Liu, Ronghua; Wan, Wei

2016-12-01

Soil moisture is a key variable in the exchange of water and energy between the land surface and the atmosphere, especially over the Tibetan Plateau (TP) which is climatically and hydrologically sensitive as the Earth's 'third pole'. Large-scale spatially consistent and temporally continuous soil moisture datasets are of great importance to meteorological and hydrological applications, such as weather forecasting and drought monitoring. The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product is a relatively new passive microwave product, with the satellite being launched on November 5, 2010. This study validates and reconstructs FY-3B/MWRI soil moisture across the TP. First, the validation is performed using in situ measurements within two in situ soil moisture measurement networks (1° × 1° and 0.25° × 0.25°), and also compared with the Essential Climate Variable (ECV) soil moisture product from multiple active and passive satellite soil moisture products using new merging procedures. Results show that the ascending FY-3B/MWRI product outperforms the descending product. The ascending FY-3B/MWRI product has almost the same correlation as the ECV product with the in situ measurements. The ascending FY-3B/MWRI product has better performance than the ECV product in the frozen season and under the lower NDVI condition. When the NDVI is higher in the unfrozen season, uncertainty in the ascending FY-3B/MWRI product increases with increasing NDVI, but it could still capture the variability in soil moisture. Second, the FY-3B/MWRI soil moisture product is subsequently reconstructed using the back-propagation neural network (BP-NN) based on reconstructed MODIS products, i.e., LST, NDVI, and albedo. The reconstruction method of generating the soil moisture product not only considers the relationship between the soil moisture and NDVI, LST, and albedo, but also the relationship between the soil moisture and four-dimensional variations using the longitude, latitude, DEM and day of year (DOY). Results show that the soil moisture could be well reconstructed with R2 higher than 0.56, RMSE less than 0.1 cm3 cm-3, and Bias less than 0.07 cm3 cm-3 for both frozen and unfrozen seasons, compared with the in situ measurements at the two networks. Third, the reconstruction method is applied to generate surface soil moisture over the TP. Both original and reconstructed FY-3B/MWRI soil moisture products could be valuable in studying meteorology, hydrology, and ecosystems over the TP.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Static sampling of dynamic processes - a paradox?

NASA Astrophysics Data System (ADS)

Mälicke, Mirko; Neuper, Malte; Jackisch, Conrad; Hassler, Sibylle; Zehe, Erwin

2017-04-01

Environmental systems monitoring aims at its core at the detection of spatio-temporal patterns of processes and system states, which is a pre-requisite for understanding and explaining their baffling heterogeneity. Most observation networks rely on distributed point sampling of states and fluxes of interest, which is combined with proxy-variables from either remote sensing or near surface geophysics. The cardinal question on the appropriate experimental design of such a monitoring network has up to now been answered in many different ways. Suggested approaches range from sampling in a dense regular grid using for the so-called green machine, transects along typical catenas, clustering of several observations sensors in presumed functional units or HRUs, arrangements of those cluster along presumed lateral flow paths to last not least a nested, randomized stratified arrangement of sensors or samples. Common to all these approaches is that they provide a rather static spatial sampling, while state variables and their spatial covariance structure dynamically change in time. It is hence of key interest how much of our still incomplete understanding stems from inappropriate sampling and how much needs to be attributed to an inappropriate analysis of spatial data sets. We suggest that it is much more promising to analyze the spatial variability of processes, for instance changes in soil moisture values, than to investigate the spatial variability of soil moisture states themselves. This is because wetting of the soil, reflected in a soil moisture increase, is causes by a totally different meteorological driver - rainfall - than drying of the soil. We hence propose that the rising and the falling limbs of soil moisture time series belong essentially to different ensembles, as they are influenced by different drivers. Positive and negative temporal changes in soil moisture need, hence, to be analyzed separately. We test this idea using the CAOS data set as a benchmark. Specifically, we expect the covariance structure of the positive temporal changes of soil moisture to be dominated by the spatial structure of rain- and through-fall and saturated hydraulic conductivity. The covariance in temporarily decreasing soil moisture during radiation driven conditions is expect to be dominated by the spatial structure of retention properties and plant transpiration. An analysis of soil moisture changes has furthermore the advantage that those are free from systematic measurement errors.

High-resolution Mapping of Permafrost and Soil Freeze/thaw Dynamics in the Tibetan Plateau Based on Multi-sensor Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, W.; Yi, Y.; Yang, K.; Kimball, J. S.

2016-12-01

The Tibetan Plateau (TP) is underlain by the world's largest extent of alpine permafrost ( 2.5×106 km2), dominated by sporadic and discontinuous permafrost with strong sensitivity to climate warming. Detailed permafrost distributions and patterns in most of the TP region are still unknown due to extremely sparse in-situ observations in this region characterized by heterogeneous land cover and large temporal dynamics in surface soil moisture conditions. Therefore, satellite-based temperature and moisture observations are essential for high-resolution mapping of permafrost distribution and soil active layer changes in the TP region. In this study, we quantify the TP regional permafrost distribution at 1-km resolution using a detailed satellite data-driven soil thermal process model (GIPL2). The soil thermal model is calibrated and validated using in-situ soil temperature/moisture observations from the CAMP/Tibet field campaign (9 sites: 0-300 cm soil depth sampling from 1997-2007), a multi-scale soil moisture and temperature monitoring network in the central TP (CTP-SMTMN, 57 sites: 5-40 cm, 2010-2014) and across the whole plateau (China Meteorology Administration, 98 sites: 0-320 cm, 2000-2015). Our preliminary results using the CAMP/Tibet and CTP-SMTMN network observations indicate strong controls of surface thermal and soil moisture conditions on soil freeze/thaw dynamics, which vary greatly with underlying topography, soil texture and vegetation cover. For regional mapping of soil freeze/thaw and permafrost dynamics, we use the most recent soil moisture retrievals from the NASA SMAP (Soil Moisture Active Passive) sensor to account for the effects of temporal soil moisture dynamics on soil thermal heat transfer, with surface thermal conditions defined by MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature records. Our study provides the first 1-km map of spatial patterns and recent changes of permafrost conditions in the TP.

Distinct respiratory responses of soils to complex organic substrate are governed predominantly by soil architecture and its microbial community.

PubMed

Fraser, F C; Todman, L C; Corstanje, R; Deeks, L K; Harris, J A; Pawlett, M; Whitmore, A P; Ritz, K

2016-12-01

Factors governing the turnover of organic matter (OM) added to soils, including substrate quality, climate, environment and biology, are well known, but their relative importance has been difficult to ascertain due to the interconnected nature of the soil system. This has made their inclusion in mechanistic models of OM turnover or nutrient cycling difficult despite the potential power of these models to unravel complex interactions. Using high temporal-resolution respirometery (6 min measurement intervals), we monitored the respiratory response of 67 soils sampled from across England and Wales over a 5 day period following the addition of a complex organic substrate (green barley powder). Four respiratory response archetypes were observed, characterised by different rates of respiration as well as different time-dependent patterns. We also found that it was possible to predict, with 95% accuracy, which type of respiratory behaviour a soil would exhibit based on certain physical and chemical soil properties combined with the size and phenotypic structure of the microbial community. Bulk density, microbial biomass carbon, water holding capacity and microbial community phenotype were identified as the four most important factors in predicting the soils' respiratory responses using a Bayesian belief network. These results show that the size and constitution of the microbial community are as important as physico-chemical properties of a soil in governing the respiratory response to OM addition. Such a combination suggests that the 'architecture' of the soil, i.e. the integration of the spatial organisation of the environment and the interactions between the communities living and functioning within the pore networks, is fundamentally important in regulating such processes.

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.

Accessibility, searchability, transparency and engagement of soil carbon data: The International Soil Carbon Network

NASA Astrophysics Data System (ADS)

Harden, Jennifer W.; Hugelius, Gustaf; Koven, Charlie; Sulman, Ben; O'Donnell, Jon; He, Yujie

2016-04-01

Soils are capacitors for carbon and water entering and exiting through land-atmosphere exchange. Capturing the spatiotemporal variations in soil C exchange through monitoring and modeling is difficult in part because data are reported unevenly across spatial, temporal, and management scales and in part because the unit of measure generally involves destructive harvest or non-recurrent measurements. In order to improve our fundamental basis for understanding soil C exchange, a multi-user, open source, searchable database and network of scientists has been formed. The International Soil Carbon Network (ISCN) is a self-chartered, member-based and member-owned network of scientists dedicated to soil carbon science. Attributes of the ISCN include 1) Targeted ISCN Action Groups which represent teams of motivated researchers that propose and pursue specific soil C research questions with the aim of synthesizing seminal articles regarding soil C fate. 2) Datasets to date contributed by institutions and individuals to a comprehensive, searchable open-access database that currently includes over 70,000 geolocated profiles for which soil C and other soil properties. 3) Derivative products resulting from the database, including depth attenuation attributes for C concentration and storage; C storage maps; and model-based assessments of emission/sequestration for future climate scenarios. Several examples illustrate the power of such a database and its engagement with the science community. First, a simplified, data-constrained global ecosystem model estimated a global sensitivity of permafrost soil carbon to climate change (g sensitivity) of -14 to -19 Pg C °C-1 of warming on a 100 years time scale. Second, using mathematical characterizations of depth profiles for organic carbon storage, C at the soil surface reflects Net Primary Production (NPP) and its allotment as moss or litter, while e-folding depths are correlated to rooting depth. Third, storage of deep C is highly correlated with bulk density and porosity of the rock/sediment matrix. Thus C storage is most stable at depth, yet is susceptible to changes in tillage, rooting depths, and erosion/sedimentation. Fourth, current ESMs likely overestimate the turnover time of soil organic carbon and subsequently overestimate soil carbon sequestration, thus datasets combined with other soil properties will help constrain the ESM predictions. Last, analysis of soil horizon and carbon data showed that soils with a history of tillage had significantly lower carbon concentrations in both near-surface and deep layers, and that the effect persisted even in reforested areas. In addition to the opportunities for empirical science using a large database, the database has great promise for evaluation of biogeochemical and earth system models. The preservation of individual soil core measurements avoids issues with spatial averaging while facilitating evaluation of advanced model processes such as depth distributions of soil carbon, land use impacts, and spatial heterogeneity.

Revisiting hydraulic hysteresis based on long-term monitoring of hydraulic states in lysimeters

NASA Astrophysics Data System (ADS)

Hannes, M.; Wollschläger, U.; Wöhling, T.; Vogel, H.-J.

2016-05-01

Hysteretic processes have been recognized for decades as an important characteristic of soil hydraulic behavior. Several studies confirmed that wetting and drying periods cannot be described by a simple functional relationship, and that some nonequilibrium of the water retention characteristics has to be taken into account. A large number of models describing the hysteresis of the soil water retention characteristic were successfully tested on soil cores under controlled laboratory conditions. However, its relevance under field conditions under natural forcings has rarely been investigated. In practice, the modeling of field soils usually neglects the hysteretic nature of soil hydraulic properties. In this study, long-term observations of water content and matric potential in lysimeters of the lysimeter network TERENO-SoilCan are presented, clearly demonstrating the hysteretic behavior of field soils. We propose a classification into three categories related to different time scales. Based on synthetic and long-term monitoring data, three different models of hysteresis were applied to data sets showing different degrees of hysteresis. We found no single model to be superior to the others. The model ranking depended on the degree of hysteresis. All models were able to reflect the general structure of hysteresis in most cases but failed to reproduce the detailed trajectories of state variables especially under highly transient conditions. As an important result we found that the temporal dynamics of wetting and drying significantly affects these trajectories which should be accounted for in future model concepts.

Agricultural management explains historic changes in regional soil carbon stocks

PubMed Central

van Wesemael, Bas; Paustian, Keith; Meersmans, Jeroen; Goidts, Esther; Barancikova, Gabriela; Easter, Mark

2010-01-01

Agriculture is considered to be among the economic sectors having the greatest greenhouse gas mitigation potential, largely via soil organic carbon (SOC) sequestration. However, it remains a challenge to accurately quantify SOC stock changes at regional to national scales. SOC stock changes resulting from SOC inventory systems are only available for a few countries and the trends vary widely between studies. Process-based models can provide insight in the drivers of SOC changes, but accurate input data are currently not available at these spatial scales. Here we use measurements from a soil inventory dating from the 1960s and resampled in 2006 covering the major soil types and agricultural regions in Belgium together with region-specific land use and management data and a process-based model. The largest decreases in SOC stocks occurred in poorly drained grassland soils (clays and floodplain soils), consistent with drainage improvements since 1960. Large increases in SOC in well drained grassland soils appear to be a legacy effect of widespread conversion of cropland to grassland before 1960. SOC in cropland increased only in sandy lowland soils, driven by increasing manure additions. Modeled land use and management impacts accounted for more than 70% of the variation in observed SOC changes, and no bias could be demonstrated. There was no significant effect of climate trends since 1960 on observed SOC changes. SOC monitoring networks are being established in many countries. Our results demonstrate that detailed and long-term land management data are crucial to explain the observed SOC changes for such networks. PMID:20679194

40 CFR 264.278 - Unsaturated zone monitoring.

Code of Federal Regulations, 2011 CFR

2011-07-01

... or operator must monitor the soil and soil-pore liquid to determine whether hazardous constituents... unsaturated zone monitoring system that includes soil monitoring using soil cores and soil-pore liquid... the quality of background soil-pore liquid quality and the chemical make-up of soil that has not been...

40 CFR 264.278 - Unsaturated zone monitoring.

Code of Federal Regulations, 2014 CFR

2014-07-01

... or operator must monitor the soil and soil-pore liquid to determine whether hazardous constituents... unsaturated zone monitoring system that includes soil monitoring using soil cores and soil-pore liquid... the quality of background soil-pore liquid quality and the chemical make-up of soil that has not been...

40 CFR 264.278 - Unsaturated zone monitoring.

Code of Federal Regulations, 2012 CFR

2012-07-01

... or operator must monitor the soil and soil-pore liquid to determine whether hazardous constituents... unsaturated zone monitoring system that includes soil monitoring using soil cores and soil-pore liquid... the quality of background soil-pore liquid quality and the chemical make-up of soil that has not been...

40 CFR 264.278 - Unsaturated zone monitoring.

Code of Federal Regulations, 2013 CFR

2013-07-01

... or operator must monitor the soil and soil-pore liquid to determine whether hazardous constituents... unsaturated zone monitoring system that includes soil monitoring using soil cores and soil-pore liquid... the quality of background soil-pore liquid quality and the chemical make-up of soil that has not been...

40 CFR 264.278 - Unsaturated zone monitoring.

Code of Federal Regulations, 2010 CFR

2010-07-01

... or operator must monitor the soil and soil-pore liquid to determine whether hazardous constituents... unsaturated zone monitoring system that includes soil monitoring using soil cores and soil-pore liquid... the quality of background soil-pore liquid quality and the chemical make-up of soil that has not been...

AMMA-CATCH a Hydrological, Meteorological and Ecological Long Term Observatory on West Africa : Some Recent Results

NASA Astrophysics Data System (ADS)

Galle, S.; Grippa, M.; Peugeot, C.; Bouzou Moussa, I.; Cappelaere, B.; Demarty, J.; Mougin, E.; Lebel, T.; Chaffard, V.

2015-12-01

AMMA-CATCH is a multi-scale observation system dedicated to long-term monitoring of the water cycle, the vegetation dynamics and their interaction with climate and water resources in West Africa. In the context of the global change, long-term observations are required to i) gain understanding in eco-hydrological processes over this highly contrasted region, ii) help their representation in Earth System Models, and iii) detect trends and infer their impacts on water resources and living conditions. It is made of three meso-scale sites (~ 1°x1°) in Mali, Niger and Benin, extending along the West African eco-climatic gradient. Within this regional window (5° by 9°), each of the three sites comprises a multi-scale set-up which helps documenting the components of the hydrologic budget and the evolutions of the surface conditions over a range of time scales: raingages, piezometers, river discharge stations, soil moisture and temperature profiles, turbulent fluxes measurements, LAI/biomass monitoring. This observation system has been continuously generating coherent datasets for 10 to 25 years depending on the datasets. It is jointly operated by French and African (Mali, Niger and Benin) research institutions. The data-base is available to the community through the website (www.amma-catch.org). AMMA-CATCH is a member of the French critical zone observatory network "Réseau des Bassins Versants", (RBV). AMMA-CATH participates to several global or regional observation networks, such as FluxNet, CarboAfrica, International Soil Moisture Networks (ISMN) and to calibration/validation campaigns for satellite missions such as SMOS (CNES, ESA), MEGHA-TROPIQUES (France/India) or SWAP(NASA). AMMA-CATCH fills a gap over a region, West Africa, where environmental data are largely lacking, and thus, it can usefully contribute to the international networking effort for environmental monitoring and research. Recent results on regional evolution of land cover, rainfall intensity and their consequences on eco-hydrological processes and hydrosystems will be presented.

Soil Moisture Sensing Using Reflected GPS Signals: Description of the GPS Soil Moisture Product.

NASA Astrophysics Data System (ADS)

Larson, Kristine; Small, Eric; Chew, Clara

2015-04-01

As first demonstrated by the GPS reflections group in 2008, data from GPS networks can be used to monitor multiple parameters of the terrestrial water cycle. The GPS L-band signals take two paths: (1) the "direct" signal travels from the satellite to the antenna, which is typically located 2-3 meters above the ground; (2) the reflected signal interacts with the Earth's surface before traveling to the antenna. The direct signal is used by geophysicists and surveyors to measure the position of the antenna, while the effects of reflected signals are a source of error. If one focuses on the reflected signal rather than the positioning observables, one has a method that is sensitive to surface soil moisture (top 5 cm), vegetation water content, and snow depth. This method - known as GPS Interferometric Reflectometry (GPS-IR) - has a footprint of ~1000 m2 for most GPS sites. This is intermediate in scale to most in situ and satellite observations. A significant advantage of GPS-IR is that data from existing GPS networks can be used without any changes to the instrumentation. This means that there is a new source of cost-effective instrumentation for satellite validation and climate studies. This presentation will provide an overview of the GPS-IR methodology with an emphasis on the soil moisture product. GPS water cycle products are currently produced on a daily basis for a network of ~500 sites in the western United States; results are freely available at http://xenon.colorado.edu/portal. Plans to expand the GPS-IR method to the network of international GPS sites will also be discussed.

Integrated monitoring technologies for the management of a Soil-Aquifer-Treatment (SAT) system.

NASA Astrophysics Data System (ADS)

Papadopoulos, Alexandros; Kallioras, Andreas; Kofakis, Petros; Bumberger, Jan; Schmidt, Felix; Athanasiou, Georgios; Uzunoglou, Nikolaos; Amditis, Angelos; Dietrich, Peter

2016-04-01

Artificial recharge of groundwater has an important role to play in water reuse as treated wastewater effluent can be infiltrated into the ground for aquifer recharge. As the effluent moves through the soil and the aquifer, it undergoes significant quality improvements through physical, chemical, and biological processes in the underground environment. Collectively, these processes and the water quality improvement obtained are called soil-aquifer-treatment (SAT) or geopurification. The pilot site of Lavrion Technological & Cultural Park (LTCP) of the National Technical University of Athens (NTUA), involves the employment of plot infiltration basins at experimental scale, which will be using waters of impaired quality as a recharge source, and hence acting as a Soil-Aquifer-Treatment, SAT, system. Τhe LTCP site will be employed as a pilot SAT system complemented by new technological developments, which will be providing continuous monitoring of the quantitative and qualitative characteristics of infiltrating groundwater through all hydrologic zones (i.e. surface, unsaturated and saturated zone). This will be achieved by the development and installation of an integrated system of prototype sensing technologies, installed on-site, and offering a continuous evaluation of the performance of the SAT system. An integrated approach of the performance evaluation of any operating SAT system should aim at parallel monitoring of all hydrologic zones, proving the sustainability of all involved water quality treatment processes within unsaturated and saturated zone. Hence a prototype system of Time and Frequency Domain Reflectometry (TDR & FDR) sensors is developed and will be installed, in order to achieve continuous quantitative monitoring of the unsaturated zone through the entire soil column down to significant depths below the SAT basin. Additionally, the system contains two different radar-based sensing systems that will be offering (i) identification of preferential flow effects of the TDR/FDR sensors and (ii) monitoring of the water table within the shallow karst aquifer layer. The above technique will offer continuous monitoring of infiltration rates and identify possible mechanical or biological clogging effects. The monitoring system will be connected to an ad-hoc wireless network for continuous data transfer within the SAT facilities. It is envisaged that the development and combined application of all the above technologies will provide an integrated monitoring platform for the evaluation of SAT system performance.

Results from twelve years of continuous monitoring of the soil CO2 flux at the Ketzin CO2 storage pilot site, Germany

NASA Astrophysics Data System (ADS)

Szizybalski, Alexandra; Zimmer, Martin; Pilz, Peter; Liebscher, Axel

2017-04-01

Under the coordination of the GFZ German Research Centre for Geosciences the complete life-cycle of a geological storage site for CO2 has been investigated and studied in detail over the past 12 years at Ketzin near Berlin, Germany. The test site is located at the southern flank of an anticlinal structure. Beginning with an exploration phase in 2004, drilling of the first three wells took place in 2007. From June 2008 to August 2013 about 67 kt of CO2 were injected into Upper Triassic sandstones at a depth of 630 to 650 m overlain by more than 165 m of shaley cap rocks. A comprehensive operational and scientific monitoring program forms the central part of the Ketzin project targeting at the reservoir itself, its overburden or above-zone and the surface. The surface monitoring is done by continuous soil CO2 flux measurements. These already started in 2005, more than three years prior to the injection phase using a survey chamber from LI-COR Inc. Twenty sampling locations were selected in the area of the anticline covering about 3 x 3 km. In order to obtain information on seasonal trends, measurements are performed at least once a month. The data set obtained prior to the injection serves as a basis for comparison with all further measurements during the injection and storage operations [Zimmer et al., 2010]. To refine the monitoring network, eight automatic, permanent soil CO2 flux stations were additionally installed in 2011 in the direct vicinity of the boreholes. Using this system, the CO2 soil flux is measured on an hourly basis. Over the whole monitoring time, soil temperature and moisture are recorded simultaneously and soil samples down to 70 cm depth were studied for their structure, carbon and nitrogen content. ver the whole monitoring time. Both, diurnal and seasonal flux variations can be detected and hence, provide a basis for interpretation of the measured data. Detailed analysis of the long-term monitoring at each station clearly reveals the influence of the soil composition. As most of the sampling positions are located next to agricultural roads and fields, the use of chemicals and harvesting may have an influence on the soil structure and the biology. Soil temperature, rain events and dry periods additionally affect the CO2 flux. Moreover, the microbial controlled increased CO2 production in early fall is also observed to depend on the actual location. Annual mean values of CO2 fluxes range from 10 to 82 t ha-1 a-1. As the CO2 flux measurements significantly reflect the specific site conditions, which can vary locally and over time, long-term trends must be carefully interpreted. Hence, complementary measurements of the soil gas composition were performed at selected locations. Zimmer, M., Pilz, P., Erzinger, J. (2011): Long-term surface carbon dioxide flux monitoring at the Ketzin carbon dioxide storage test site. Environmental Geosciences, 18, 119-130, doi:10.1306/eg.11181010017.

Environmental Monitoring Using Sensor Networks

NASA Astrophysics Data System (ADS)

Yang, J.; Zhang, C.; Li, X.; Huang, Y.; Fu, S.; Acevedo, M. F.

2008-12-01

Environmental observatories, consisting of a variety of sensor systems, computational resources and informatics, are important for us to observe, model, predict, and ultimately help preserve the health of the nature. The commoditization and proliferation of coin-to-palm sized wireless sensors will allow environmental monitoring with unprecedented fine spatial and temporal resolution. Once scattered around, these sensors can identify themselves, locate their positions, describe their functions, and self-organize into a network. They communicate through wireless channel with nearby sensors and transmit data through multi-hop protocols to a gateway, which can forward information to a remote data server. In this project, we describe an environmental observatory called Texas Environmental Observatory (TEO) that incorporates a sensor network system with intertwined wired and wireless sensors. We are enhancing and expanding the existing wired weather stations to include wireless sensor networks (WSNs) and telemetry using solar-powered cellular modems. The new WSNs will monitor soil moisture and support long-term hydrologic modeling. Hydrologic models are helpful in predicting how changes in land cover translate into changes in the stream flow regime. These models require inputs that are difficult to measure over large areas, especially variables related to storm events, such as soil moisture antecedent conditions and rainfall amount and intensity. This will also contribute to improve rainfall estimations from meteorological radar data and enhance hydrological forecasts. Sensor data are transmitted from monitoring site to a Central Data Collection (CDC) Server. We incorporate a GPRS modem for wireless telemetry, a single-board computer (SBC) as Remote Field Gateway (RFG) Server, and a WSN for distributed soil moisture monitoring. The RFG provides effective control, management, and coordination of two independent sensor systems, i.e., a traditional datalogger-based wired sensor system and the WSN-based wireless sensor system. The RFG also supports remote manipulation of the devices in the field such as the SBC, datalogger, and WSN. Sensor data collected from the distributed monitoring stations are stored in a database (DB) Server. The CDC Server acts as an intermediate component to hide the heterogeneity of different devices and support data validation required by the DB Server. Daemon programs running on the CDC Server pre-process the data before it is inserted into the database, and periodically perform synchronization tasks. A SWE-compliant data repository is installed to enable data exchange, accepting data from both internal DB Server and external sources through the OGC web services. The web portal, i.e. TEO Online, serves as a user-friendly interface for data visualization, analysis, synthesis, modeling, and K-12 educational outreach activities. It also provides useful capabilities for system developers and operators to remotely monitor system status and remotely update software and system configuration, which greatly simplifies the system debugging and maintenance tasks. We also implement Sensor Observation Services (SOS) at this layer, conforming to the SWE standard to facilitate data exchange. The standard SensorML/O&M data representation makes it easy to integrate our sensor data into the existing Geographic Information Systems (GIS) web services and exchange the data with other organizations.

A regional-scale network for geoid monitoring and satellite gravimetry validation

NASA Astrophysics Data System (ADS)

Winester, D.; Pool, D.; Kennedy, J.

2010-12-01

In the past two decades, improved measurements of acceleration due to gravity have allowed for accurate detection of temporal gravity change. Terrestrial absolute gravimeters (for example, Micro-g LaCoste FG5 or A-10) can sense changes of gravity induced by elevation or mass changes, including local effects that may bias regional studies. Satellite instrumentation (e.g. GRACE) can detect large scale mass changes on a regular basis. However, the Nyquist wave number for satellite observations is often much too small for the size of regional studies. Also, satellites are limited by their life of deployment. Both techniques are used to (in)validate change models generated from other geophysical observations including water storage(underground and glacial), geoid definition, isostatic adjustments and tectonic(magmatic and faulting)activity. The gap between terrestrial and satellite gravity observations (and between satellite missions) might be bridged by developing a terrestrial network of sites of various observation techniques that define a representative sample of a given, regional study area. This information could then be statistically extrapolated to the extent of the region. The Southern High Plains Aquifer is such a region, since it has widespread relatively uniform geology, has relatively flat topography, and is well monitored for groundwater levels and soil moisture. Each site would have extensive instrumentation for monitoring, at a minimum, gravity (periodic and continuous) using absolute and tidal gravimeters, soil moisture, precipitation, depths to water in wells, evapotranspiration, air pressure, and land surface (GPS). Where possible, the network would build upon existing, data collection infrastructure. Preferably, the region would also have seismic tomography or crustal seismic reflection observations to characterize Moho-depth mass changes and have regional Bouguer anomaly mapping. In addition to information on local hydrology and geology, data collection would allow for characterization of local seasonal corrections, earth tides, atmospheric loading and episodic slip. No test network has yet been funded, but cost and man-power can be estimated. Such a network would rely on co-operation between various federal, state, local and university groups.

Fire modifies the phylogenetic structure of soil bacterial co-occurrence networks.

PubMed

Pérez-Valera, Eduardo; Goberna, Marta; Faust, Karoline; Raes, Jeroen; García, Carlos; Verdú, Miguel

2017-01-01

Fire alters ecosystems by changing the composition and community structure of soil microbes. The phylogenetic structure of a community provides clues about its main assembling mechanisms. While environmental filtering tends to reduce the community phylogenetic diversity by selecting for functionally (and hence phylogenetically) similar species, processes like competitive exclusion by limiting similarity tend to increase it by preventing the coexistence of functionally (and phylogenetically) similar species. We used co-occurrence networks to detect co-presence (bacteria that co-occur) or exclusion (bacteria that do not co-occur) links indicative of the ecological interactions structuring the community. We propose that inspecting the phylogenetic structure of co-presence or exclusion links allows to detect the main processes simultaneously assembling the community. We monitored a soil bacterial community after an experimental fire and found that fire altered its composition, richness and phylogenetic diversity. Both co-presence and exclusion links were more phylogenetically related than expected by chance. We interpret such a phylogenetic clustering in co-presence links as a result of environmental filtering, while that in exclusion links reflects competitive exclusion by limiting similarity. This suggests that environmental filtering and limiting similarity operate simultaneously to assemble soil bacterial communities, widening the traditional view that only environmental filtering structures bacterial communities. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Unlocking the Physiochemical Controls on Organic Carbon Dynamics from the Soil Pore- to Core-Scale

NASA Astrophysics Data System (ADS)

Smith, A. P.; Tfaily, M. M.; Bond-Lamberty, B. P.; Todd-Brown, K. E.; Bailey, V. L.

2015-12-01

The physical organization of soil includes pore networks of varying size and connectivity. These networks control microbial access to soil organic carbon (C) by spatially separating microorganisms and C by both distance and size exclusion. The extent to which this spatially isolated C is vulnerable to microbial transformation under hydrologically dynamic conditions is unknown, and limits our ability to predict the source and sink capacity of soils. We investigated the effects of shifting hydrologic connectivity and soil structure on greenhouse gas C emissions from surface soils collected from the Disney Wilderness Preserve (Florida, USA). We subjected intact soil cores and re-packed homogenized soil cores to simulated groundwater rise or precipitation, monitoring their CO2 and CH4 emissions over 24 hours. Soil pore water was then extracted from each core using different suctions to sample water retained by pore throats of different sizes and then characterized by Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry. Greater respiration rates were observed from homogenized cores compared to intact cores, and from soils wet from below, in which the wetting front is driven by capillary forces, filling fine pores first. This suggests that C located in fine pores may turn over via diffusion processes that lead to the colocation of this C with other resources and microorganisms. Both the complexity and concentration of soluble-C increased with decreasing pore size domains. Pore water extracted from homogenized cores had greater C concentrations than from intact cores, with the greatest concentrations in pore waters sampled from very fine pores, highlighting the importance of soil structure in physically protecting C. These results suggest that the spatial separation of decomposers from C is a key mechanism stabilizing C in these soils. Further research is ongoing to accurately represent this protection mechanism, and the conditions under which it breaks down, in new and improved Earth system models.

Remote Sensing of Terrestrial Water Storage and Application to Drought Monitoring

NASA Technical Reports Server (NTRS)

Rodell, Matt

2007-01-01

Terrestrial water storage (TWS) consists of groundwater, soil moisture and permafrost, surface water, snow and ice, and wet biomass. TWS variability tends to be dominated by snow and ice in polar and alpine regions, by soil moisture in mid-latitudes, and by surface water in wet, tropical regions such as the Amazon (Rodell and Famiglietti, 2001; Bates et al., 2007). Drought may be defined as a period of abnormally dry weather long enough to cause significant deficits in one or more of the TWS components. Thus, along with observations of the agricultural and socioeconomic impacts, measurements of TWS and its components enable quantification of drought severity. Each of the TWS components exhibits significant spatial variability, while installation and maintenance of sufficiently dense monitoring networks is costly and labor-intensive. Thus satellite remote sensing is an appealing alternative to traditional measurement techniques. Several current remote sensing instruments are able to detect variations in one or more TWS variables, including the Advanced Microwave Scanning Radiometer (AMSR) on NASA's Aqua satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua. Future satellite missions have been proposed to improve this capability, including the European Space Agency's Soil Moisture Ocean Salinity mission (SMOS) and the Soil Moisture Active Passive (SMAP), Surface Water Ocean Topography (SWOT), and Snow and Cold Land Processes (SCLP) missions recommended by the US National Academy of Science's Decadal Survey for Earth Science (NRC, 2007). However, only one remote sensing technology is able to monitor changes in TWS from the land surface to the base of the deepest aquifer: satellite gravimetry. This paper focuses on NASA's Gravity Recovery and Climate Experiment mission (GRACE; http://www.csr.utexas.edu/grace/) and its potential as a tool for drought monitoring.

An integrated monitoring network for hydrologic, geochemical, and sediment fluxes to characterize carbon-mineral fate in the Christina River Basin Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Sawyer, A. H.; Karwan, D. L.; Lazareva, O.

2011-12-01

Organic carbon (C) -mineral complexation mechanism plays an important role in C sequestration within watersheds. The primary goal of the Christina River Basin Critical Zone Observatory in SE Pennsylvania and N Delaware, USA (one of six National Science Foundation-funded observatories) is to quantify net carbon sink or source due to mineral production and transport and its dependence on land use. This effort requires an interdisciplinary understanding of carbon and mineral fluxes across interfaces between soil, aquifer, floodplain, and river. We have established a monitoring network that targets hydrologic, geochemical, and sedimentological transport processes across channel-floodplain-aquifer interfaces within White Clay Creek Watershed. Within the channel, suspended material is sampled and analyzed for organic and mineral composition as well as geochemical fingerprints. Surface water and groundwater are analyzed for C, Fe, and Mn chemistry. Within the floodplain, in-situ sensors monitor soil moisture, pressure, temperature, conductivity, and redox potential. Integrated data analysis should yield estimates of water and solute fluxes between the vadose zone, riparian aquifer, and stream. Our preliminary data show that storm events are important for carbon and mineral fluxes-suspended material in surface water changes in source and composition throughout the storm. Meanwhile, the variation in stream stage drives surface water-groundwater exchange, facilitating changes in redox potential and providing opportunity for enhanced transport and reactions involving C, Fe, and Mn in the riparian aquifer.

Validating Large Scale Networks Using Temporary Local Scale Networks

USDA-ARS?s Scientific Manuscript database

The USDA NRCS Soil Climate Analysis Network and NOAA Climate Reference Networks are nationwide meteorological and land surface data networks with soil moisture measurements in the top layers of soil. There is considerable interest in scaling these point measurements to larger scales for validating ...

Monitoring of resistivity and IP: The Syscal Monitoring Unit (SMU), a new system dedicated for remote control of the Syscal Pro resistivimeter

NASA Astrophysics Data System (ADS)

Gance, Julien; Leite, Orlando; Texier, Benoît; Bernard, Jean; Truffert, Catherine

2017-04-01

All matter, gas, fluids and energy transfer at soil/atmosphere interface govern soil, rock and life evolution in the critical zone. Near surface electrical resistivity and chargeability modifications with time are distinguishable and process related enough for bringing to geoscientist relevant clue within this highly studied zone. Such non-invasive measurements are directly sensitive to a wide range of remarkable parameters (soil water content, temperature, soil water conductivity, clay content, etc.). In order to increase physical, chemical and biological processes understanding, resistivity and IP monitoring remain the less costly and the more powerful method among others. Indeed, these methods are the most suitable to image 2D/3D and 4D processes in an automated way. Whether such geophysical survey are for academic knowledge, waste landfill leakage or landslide monitoring purpose, it has to be done during medium to long period of time (from days to years). Nevertheless, operators don't need to be on site all the survey long. So, equipment manufacturers had to propose them suitable solutions for their needs. Syscal Pro resistivimeter is well adapted to observe the critical zone down to 100 m depth with its 10 channels and 250 watts. Its high speed recording (up to 1000 records/min) ability is also suited to apprehend expected kinetics of studied phenomena. In this context, IRIS Instruments developed a dedicated remote unit able to remote control Syscal Pro resistivimeter. It allows to change acquisition parameters (sequences), to check the main constant (battery levels, internal temperature) and to alert in case of any recording troubles. Data can be sent directly to FTP or SSH server or by mail for an easy and constant access to the data. Alert functionalities sent by mail in case of low battery or too many outliers present in the data are welcome to check the dimensioning of the energy source and for easily maintaining the long-term acquisition necessary for such applications. This paper present the device and how it can be easily used, connected directly to the internet network, to the 3G/4G mobile network or not. A large field of application is then now accessible to geoscientist.

GuMNet - Guadarrama Monitoring Network initiative (Madrid,Spain)

NASA Astrophysics Data System (ADS)

Santolaria-Canales, Edmundo

2017-04-01

The Guadarrama Monitoring Network initiative (GuMNet) is an observational infrastructure focused on monitoring the state of the atmosphere, surface and subsurface in the Sierra de Guadarrama, 50 km NW of the city of Madrid. The network is composed of 10 automatic real time weather stations ranging from low altitude (ca. 900 m.a.s.l) to high mountain areas (ca. 2400 m.a.s.l). The GuMNet infrastructure consists in 10 real time automatic weather stations with instrumentation for observing the state of the atmosphere, surface and the subsurface at the Sierra de Guadarrama, just 50 km north-northwest of the city of Madrid. GuMNet lays the foundations of a research network on weather, soil thermodynamics, boundary layer physics, climate and ecosystem oriented impacts, air pollutions, etc. in the Sierra de Guadarrama. GuMNet represents a first step to provide a unique observational network in an environment of high protection to be used as a laboratory serving a wide range of scientific and educational interests. High altitude sites are focused on periglacial areas and lower altitude sites have emphasis on pastures. One of the low altitude sites is equipped with a 10 m high anemometric tower with a 3D sonic anemometer at the top jointly with a CO2/H2O analyzer that will allow sampling of wind profiles and H2O and CO2 eddy covariance fluxes, important for soil respiration and CO2 and water vapor exchange. A portable station has also a 3D sonic anemometer with CO2/H2O analyzer, this 4 meters-high portable tower is designed for comparison with other soil terrain fluxes. The network is connected via general packet radio service (GPRS) to the central lab in the Campus of Excellence of Moncloa and a management software has been developed to handle the operation of the infrastructure. The deployment of instrumentation and connection of sites to the network was finished in 2016. GuMNet is currently in the process of becoming operational. Conceptually, GuMNet intends to convert a well known space such as the Sierra de Guadarrama into a laboratory for interdisciplinary research. On one hand, a space for exchange of observational and scientific discussion among researchers. On the other hand, online platforms and various informative materials will allow the public to access the results generated by different research lines with a focus on this region. GuMNet is part of the MRI initiative and as well as ongoing collaboration with the Global Precipitation Measurements (NASA). This initiative is supported and developed by research groups integrating the GuMNet Consortium from the Complutense and Polytechnical Universities of Madrid (UCM and UPM), the Energetic Environmental and Technological Research Centre (CIEMAT), the Spanish meteorological agency, AEMET, the National Park Sierra de Guadarrama (PNSG) and the National Research Council (CSIC). Web and contact: http://www.ucm.es/gumnet/

Studying and understanding the environmental impacts of the Three Gorges Dam in China

NASA Astrophysics Data System (ADS)

Schönbrodt-Stitt, Sarah; Stumpf, Felix; Schmidt, Karsten; Althaus, Paul; Bi, Renneng; Bieger, Katrin; Buzzo, Giovanni; Dumperth, Christian; Fohrer, Nicola; Rohn, Joachim; Strehmel, Alexander; Udelhoven, Thomas; Wei, Xiang; Zimmermann, Karsten; Scholten, Thomas

2013-04-01

Since its planning phase and its completion and start of operation in 2009, the Three Gorges Dam (TGD) at the Yangtze River, has been discussed in a controversial manner. Due to considerable resettlements along with the associated expansion of the infrastructure network and large-scale shifts in land use and management, the TGD in Central China is among the most prominent human-induced examples for large-scale environmental impacts. As a consequence of the rapid ecosystem changes, the region is largely characterized by an enormous boost of typical geo-risks such as soil erosion, mass movements, and diffuse sediment and matter fluxes into the reservoir. Within the joint research project YANGTZE-GEO, Chinese and German scientists jointly focus on the human-induced environmental changes in the reservoir of the TGD after the impoundment of the Yangtze River and its tributaries. An integrative approach was set up in order to combine multi-scale investigation methods and state-of-the-art techniques from soil science, geology, hydrology, geophysics, geodesy, remote sensing, and data survey and monitoring. By means of eco-hydrological and soil erosion modeling, geo-statistical approaches such as digital soil mapping and Artificial Neuronal Networks, spatially and temporally differentiated simulation of the water budget as well as the balance of diffuse matter such as phosphorus and sediment, three-dimensional dynamic modeling, seismoacoustics and terrestrial radarinterferometry, multi-temporal land use classification from recent and historical remote sensing data and laser scanning, the research aims at (i) the understanding of the mechanisms and anthropogenic and environmental control factors of the environmental changes in the highly dynamic region and (ii) the development of spatially explicit land use options and recommendations for a sustainable land use management. Finally, based on the integrate modelling, we aim at the conception of a monitoring- and measuring network and early-warning system including local and regional authorities. Thus, the studies will contribute to a better understanding of the dimensions and dynamics of the ecological consequences of such large dam projects at the Yangtze River and worldwide.

Comparing soil moisture anomalies from multiple independent sources over different regions across the globe

NASA Astrophysics Data System (ADS)

Cammalleri, Carmelo; Vogt, Jürgen V.; Bisselink, Bernard; de Roo, Ad

2017-12-01

Agricultural drought events can affect large regions across the world, implying the need for a suitable global tool for an accurate monitoring of this phenomenon. Soil moisture anomalies are considered a good metric to capture the occurrence of agricultural drought events, and they have become an important component of several operational drought monitoring systems. In the framework of the JRC Global Drought Observatory (GDO, http://edo.jrc.ec.europa.eu/gdo/), the suitability of three datasets as possible representations of root zone soil moisture anomalies has been evaluated: (1) the soil moisture from the Lisflood distributed hydrological model (namely LIS), (2) the remotely sensed Land Surface Temperature data from the MODIS satellite (namely LST), and (3) the ESA Climate Change Initiative combined passive/active microwave skin soil moisture dataset (namely CCI). Due to the independency of these three datasets, the triple collocation (TC) technique has been applied, aiming at quantifying the likely error associated with each dataset in comparison to the unknown true status of the system. TC analysis was performed on five macro-regions (namely North America, Europe, India, southern Africa and Australia) detected as suitable for the experiment, providing insight into the mutual relationship between these datasets as well as an assessment of the accuracy of each method. Even if no definitive statement on the spatial distribution of errors can be provided, a clear outcome of the TC analysis is the good performance of the remote sensing datasets, especially CCI, over dry regions such as Australia and southern Africa, whereas the outputs of LIS seem to be more reliable over areas that are well monitored through meteorological ground station networks, such as North America and Europe. In a global drought monitoring system, the results of the error analysis are used to design a weighted-average ensemble system that exploits the advantages of each dataset.

A data management and publication workflow for a large-scale, heterogeneous sensor network.

PubMed

Jones, Amber Spackman; Horsburgh, Jeffery S; Reeder, Stephanie L; Ramírez, Maurier; Caraballo, Juan

2015-06-01

It is common for hydrology researchers to collect data using in situ sensors at high frequencies, for extended durations, and with spatial distributions that produce data volumes requiring infrastructure for data storage, management, and sharing. The availability and utility of these data in addressing scientific questions related to water availability, water quality, and natural disasters relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into usable data products. It also depends on the ability of researchers to share and access the data in useable formats. In this paper, we describe a data management and publication workflow and software tools for research groups and sites conducting long-term monitoring using in situ sensors. Functionality includes the ability to track monitoring equipment inventory and events related to field maintenance. Linking this information to the observational data is imperative in ensuring the quality of sensor-based data products. We present these tools in the context of a case study for the innovative Urban Transitions and Aridregion Hydrosustainability (iUTAH) sensor network. The iUTAH monitoring network includes sensors at aquatic and terrestrial sites for continuous monitoring of common meteorological variables, snow accumulation and melt, soil moisture, surface water flow, and surface water quality. We present the overall workflow we have developed for effectively transferring data from field monitoring sites to ultimate end-users and describe the software tools we have deployed for storing, managing, and sharing the sensor data. These tools are all open source and available for others to use.

Evaluation of uncertainty in field soil moisture estimations by cosmic-ray neutron sensing

NASA Astrophysics Data System (ADS)

Scheiffele, Lena Maria; Baroni, Gabriele; Schrön, Martin; Ingwersen, Joachim; Oswald, Sascha E.

2017-04-01

Cosmic-ray neutron sensing (CRNS) has developed into a valuable, indirect and non-invasive method to estimate soil moisture at the field scale. It provides continuous temporal data (hours to days), relatively large depth (10-70 cm), and intermediate spatial scale measurements (hundreds of meters), thereby overcoming some of the limitations in point measurements (e.g., TDR/FDR) and of remote sensing products. All these characteristics make CRNS a favorable approach for soil moisture estimation, especially for applications in cropped fields and agricultural water management. Various studies compare CRNS measurements to soil sensor networks and show a good agreement. However, CRNS is sensitive to more characteristics of the land-surface, e.g. additional hydrogen pools, soil bulk density, and biomass. Prior to calibration the standard atmospheric corrections are accounting for the effects of air pressure, humidity and variations in incoming neutrons. In addition, the standard calibration approach was further extended to account for hydrogen in lattice water and soil organic material. Some corrections were also proposed to account for water in biomass. Moreover, the sensitivity of the probe was found to decrease with distance and a weighting procedure for the calibration datasets was introduced to account for the sensors' radial sensitivity. On the one hand, all the mentioned corrections showed to improve the accuracy in estimated soil moisture values. On the other hand, they require substantial additional efforts in monitoring activities and they could inherently contribute to the overall uncertainty of the CRNS product. In this study we aim (i) to quantify the uncertainty in the field soil moisture estimated by CRNS and (ii) to understand the role of the different sources of uncertainty. To this end, two experimental sites in Germany were equipped with a CRNS probe and compared to values of a soil moisture network. The agricultural fields were cropped with winter wheat (Pforzheim, 2013) and maize (Braunschweig, 2014) and differ in soil type and management. The results confirm a general good agreement between soil moisture estimated by CRNS and the soil moisture network. However, several sources of uncertainty were identified i.e., overestimation of dry conditions, strong effects of the additional hydrogen pools and an influence of the vertical soil moisture profile. Based on that, a global sensitivity analysis based on Monte Carlo sampling can be performed and evaluated in terms of soil moisture and footprint characteristics. The results allow quantifying the role of the different factors and identifying further improvements in the method.

Trace metal concentrations in forest and lawn soils of Paris region (France) along a gradient of urban pressure

NASA Astrophysics Data System (ADS)

Ludovic, Foti

2017-04-01

Urban soils differ greatly from natural ones as they are located in areas of intense anthropogenic activity (e.g. pollution, physical disturbance, surface transformation). Urban soils are a crucial component of urban ecosystems, especially in public green spaces, and contribute to many ecosystem services from the mitigation of urban heat island to recreational services. In the last decade, the study of urban soils has emerged as an important frontier in environmental research, at least because of their impact on the quality of life of urban populations, because of the services they deliver and because they are more and more recognized as a valuable resource. One of the key issues is the pollution of urban soils because they receive a variety of deposits from local (vehicle emissions, industrial discharges, domestic heating, waste incineration and other anthropogenic activities) and from remote sources (through atmospheric transport). Typical contaminants include persistent toxic substances, such as trace metals (TMs) that have drawn wide attention due to their long persistence in the environment, their tendency to bioaccumulate in the food chain and their toxicity for humans and other organisms. Concentrations, spatial distributions, dynamics, impacts and sources of TMs (e.g. industry or fossil fuels combustion) have attracted a global interest in urban soils and are the subject of ongoing research (e.g. ecotoxicological urban ecology). Some studies have already documented soil pollution with TMs at both the town and regional scales. So far, several monitoring programs (e.g. National Network for the long term Monitoring of Forest Ecosystem, Regional Monitoring Quality of Soil in France) and studies have been carried out on a national scale to measure the ranges of TM concentrations and natural background values in French soils. These studies have focused on French agricultural and forest soils and have not tackled urban soils. No study has described TM concentrations and subsequent risks in soils of Paris and Paris region (Île-de-France). Our study aims at filling this knowledge gap, focusing on contamination and pollution by TMs in lawns and forests that constitute the main types of vegetation in urban areas of Paris region. Considering the rational described above, the aims of the present study were (i) to examine the concentration of eight selected TMs (As, Cd, Cr, Cu, Fe, Ni, Pb, Zn) in soils of two land-uses (public lawns and woods) along an urban pressure gradient in Paris region, (ii) to distinguish origins and sources of contamination or pollution, (iii) to evaluate the individual and overall TM contamination degree as well as the individual and overall TM pollution degree, (iiii) to use soil characteristics to better understand soil origins and histories along the urban pressure gradient and the relationship between these characteristics and TM concentrations. Ultimately, this study provides a baseline TM assessment for the long-term monitoring of the evolution of TM soil contents in urban area of the Paris region.

Comparison of Three Soil Moisture Sensor Types Under Field Conditions Based on the Marena, Oklahoma, In Situ Sensor Testbed (MOISST)

NASA Astrophysics Data System (ADS)

Zhang, N.; Quiring, S. M.; Ochsner, T. E.

2017-12-01

Each soil moisture monitoring network commonly adopts different sensor technologies. This results in different measurement units, depths and impedes large-scale soil moisture applications that seek to integrate data from multiple networks. Therefore, a comprehensive comparison of different sensors to identify the best approach for integrating and homogenizing measurements from different sensors is required. This study compares three commonly used sensors, including Stevens Water Hydra Probes, Campbell Scientific CS616 TDR and CS 229-L heat dissipation sensors based on data from May 2010 to December 2012 from the Marena, Oklahoma, In Situ Sensor Testbed (MOISST). All sensors are installed at common depths of 5, 10, 20, 50, 100 cm. The results reveal that the differences between the three sensors tends to increase with depth. The CDF plots showed CS 229 is most sensitive to moisture variation in dry condition and most easily saturated in wet condition, followed by Hydra probe and CS616. Our results show that calculating percentiles is a good normalization method for standardizing measurements from different sensors. Our preliminary results demonstrate that CDF matching can be used to convert measurements from one sensor to another.

Remote sensing of an agricultural soil moisture network in Walnut Creek, Iowa

USDA-ARS?s Scientific Manuscript database

The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Usually soil moisture sensors are added to existing precipitation networks which have as a singular requiremen...

Drought Indicators Based on Model Assimilated GRACE Terrestrial Water Storage Observations

NASA Technical Reports Server (NTRS)

Houborg, Rasmus; Rodell, Matthew; Li, Bailing; Reichle, Rolf; Zaitchik, Benjamin F.

2012-01-01

The Gravity Recovery and Climate Experiment (GRACE) twin satellites observe time variations in Earth's gravity field which yield valuable information about changes in terrestrial water storage (TWS). GRACE is characterized by low spatial (greater than 150,000 square kilometers) and temporal (greater than 10 day) resolution but has the unique ability to sense water stored at all levels (including groundwater) systematically and continuously. The GRACE Data Assimilation System (GRACE-DAS), based on the Catchment Land Surface Model (CLSM) enhances the value of the GRACE water storage data by enabling spatial and temporal downscaling and vertical decomposition into moisture 39 components (i.e. groundwater, soil moisture, snow), which individually are more useful for scientific applications. In this study, GRACE-DAS was applied to North America and GRACE-based drought indicators were developed as part of a larger effort that investigates the possibility of more comprehensive and objective identification of drought conditions by integrating spatially, temporally and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors. Previously, the Drought Monitors lacked objective information on deep soil moisture and groundwater conditions, which are useful indicators of drought. Extensive datasets of groundwater storage from USGS monitoring wells and soil moisture from the Soil Climate Analysis Network (SCAN) were used to assess improvements in the hydrological modeling skill resulting from the assimilation of GRACE TWS data. The results point toward modest, but statistically significant, improvements in the hydrological modeling skill across major parts of the United States, highlighting the potential value of GRACE assimilated water storage field for improving drought detection.

Environmental technology demonstrations involving explosives contamination at the Volunteer Site

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

Walker, A.J.; Broder, M.F.; Jayne, E.A.

1997-08-01

Managed by the US Army Environmental Center, the Army`s test site at Volunteer Army Ammunition Plant encompasses a 300-acre area formerly used for batch production of TNT. Soil and groundwater contamination in the test area is well characterized. A network of monitoring wells and detailed information regarding the volume, location, and concentration of soil contamination is available to potential demonstrators. On-site field and laboratory support is provided by ICI Americas Incorporated, the facility`s operator. Four demonstrations have been conducted at the test site and several are scheduled for 1997. Preliminary findings from the four demonstrations discussed will be available sometimemore » in 1997.« less

Mobility and bio-availability of heavy metals in anthropogenically contaminated alluvial (deluvial) meadow soils (EUTRIC FLUVISOLS)

NASA Astrophysics Data System (ADS)

Dinev, Nikolai; Hristova, Mariana; Tzolova, Venera

2015-04-01

The total content of heavy metals is not sufficient to assess the pollution and the risk for environment as it does not provide information for the type and solubility of heavy metals' compounds in soils. The purpose was to study and determine the mobility of heavy metals in anthropogenically contaminated alluvial (delluvial) meadow soils spread around the non-ferrous plant near the town of Asenovgrad in view of risk assessment for environment pollution. Soil samples from monitoring network (1x1 km) was used. The sequential extraction procedure described by Zein and Brummer (1989) was applied. Results showed that the easily mobilizable cadmium compounds predominate in both contaminated and not contaminated soils. The stable form of copper (associated with silicate minerals, carbonates or amorphous and crystalline oxide compounds) predominates only in non polluted soils and reviles the risk of the environment contamination. Lead spreads and accumulates as highly soluble (mobile) compounds and between 72.3 and 99.6 percent of the total lead is bioavailable in soils. The procedure is very suitable for studying the mobility of technogenic lead and copper in alluvial soils with neutral medium reaction and in particular at the high levels of cadmium contamination. In soils with alkaline reaction - polluted and unpolluted the error of analysis increases for all studied elements.

A review of the impacts of degradation threats on soil properties in the UK.

PubMed

Gregory, A S; Ritz, K; McGrath, S P; Quinton, J N; Goulding, K W T; Jones, R J A; Harris, J A; Bol, R; Wallace, P; Pilgrim, E S; Whitmore, A P

2015-10-01

National governments are becoming increasingly aware of the importance of their soil resources and are shaping strategies accordingly. Implicit in any such strategy is that degradation threats and their potential effect on important soil properties and functions are defined and understood. In this paper, we aimed to review the principal degradation threats on important soil properties in the UK, seeking quantitative data where possible. Soil erosion results in the removal of important topsoil and, with it, nutrients, C and porosity. A decline in soil organic matter principally affects soil biological and microbiological properties, but also impacts on soil physical properties because of the link with soil structure. Soil contamination affects soil chemical properties, affecting nutrient availability and degrading microbial properties, whilst soil compaction degrades the soil pore network. Soil sealing removes the link between the soil and most of the 'spheres', significantly affecting hydrological and microbial functions, and soils on re-developed brownfield sites are typically degraded in most soil properties. Having synthesized the literature on the impact on soil properties, we discuss potential subsequent impacts on the important soil functions, including food and fibre production, storage of water and C, support for biodiversity, and protection of cultural and archaeological heritage. Looking forward, we suggest a twin approach of field-based monitoring supported by controlled laboratory experimentation to improve our mechanistic understanding of soils. This would enable us to better predict future impacts of degradation processes, including climate change, on soil properties and functions so that we may manage soil resources sustainably.

Relationship between forest clearing and biophysical factors in tropical environments: Implications for the design of a forest change monitoring approach. [Costa Rica

NASA Technical Reports Server (NTRS)

Sader, S. A.; Joyce, A. T.

1984-01-01

The relationship between forest clearing, biophysical factors (e.g, ecological zones, slope gradient, soils), and transportation network in Costa Rica was analyzed. The location of forested areas at four reference datas (1940, 1950, 1961, and 1977) as derived from aerial photography and LANDSAT MSS data was digitilized and entered into a geographically-referenced data base. Ecological zones as protrayed by the Holdridge Life Zone Ecology System, and the location of roads and railways were also digitized from maps of the entire country as input to the data base. Information on slope gradient and soils was digitized from maps of a 21,000 square kilometer area. The total area of forest cleared over four decades are related to biophysical factors was analyzed within the data base and deforestation rates and trends were tabulated. The relatiohship between forest clearing and ecological zone and the influence of topography, sils, and transportation network are presented and discussed.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Topographical controls on soil moisture distribution and runoff response in a first order alpine catchment

NASA Astrophysics Data System (ADS)

Penna, Daniele; Gobbi, Alberto; Mantese, Nicola; Borga, Marco

2010-05-01

Hydrological processes driving runoff generation in mountain basins depend on a wide number of factors which are often strictly interconnected. Among them, topography is widely recognized as one of the dominant controls influencing soil moisture distribution in the root zone, depth to water table and location and extent of saturated areas possibly prone to runoff production. Morphological properties of catchments are responsible for the alternation between steep slopes and relatively flat areas which have the potentials to control the storage/release of water and hence the hydrological response of the whole watershed. This work aims to: i) identify the role of topography as the main factor controlling the spatial distribution of near-surface soil moisture; ii) evaluate the possible switch in soil moisture spatial organization between wet and relatively dry periods and the stability of patterns during triggering of surface/subsurface runoff; iii) assess the possible connection between the develop of an ephemeral river network and the groundwater variations, examining the influence of the catchment topographical properties on the hydrological response. Hydro-meteorological data were collected in a small subcatchment (Larch Creek Catchment, 0.033 km²) of Rio Vauz basin (1.9 km²), in the eastern Italian Alps. Precipitation, discharge, water table level over a net of 14 piezometric wells and volumetric soil moisture at 0-30 cm depth were monitored continuously during the late spring-early autumn months in 2007 and 2008. Soil water content at 0-6 and 0-20 cm depth was measured manually during 22 field surveys in summer 2007 over a 44-sampling point experimental plot (approximately 3000 m²). In summer 2008 the sampling grid was extended to 64 points (approximately 4500 m²) and 28 field surveys were carried out. The length of the ephemeral stream network developed during rainfall events was assessed by a net of 24 Overland Flow Detectors (OFDs), which are able to detect the presence/absence of surface runoff. Results show a significant correlation between plot-averaged soil moisture at 0-20 cm depth, local slope and local curvature, while poor correlations were found with aspect and solar radiation: this suggests a sharp control of the catchment topological architecture (likely coupled with soil properties) on soil moisture distribution. This was also confirmed by the visual inspection of interpolated maps which reveal the persistence of high values of soil moisture in hollow areas and, conversely, of low values over the hillslopes. Moreover, a strong correlation between plot-averaged soil moisture patterns over time, with no decline after rainfall events, indicates a good temporal stability of water content distribution and its independence from the triggering of surface flow and transient lateral subsurface flow during wet conditions. The analysis of the time lag between storm centroid and piezometric peak shows an increasing delay of water table reaction with increasing distance from the stream, revealing different groundwater dynamics between the near-stream and the hillslope zone. Furthermore, the significant correlation between groundwater time lag monitored for the net of piezometers and the local slope suggests a topographical influence on the temporal and spatial variability of subsurface runoff. Finally, the extent of the ephemeral stream network was clearly dependent on the amount of precipitation but a different percentage of active OFDs and piezometers for the same rainfall event suggests a decoupling between patterns of surface and subsurface flows in the study area. Key words: topographical controls, soil moisture patterns, groundwater level, overland flow.

Scientific background for soil monitoring on National Forests and Rangelands: workshop proceedings; April 29-30, 2008; Denver, CO

Treesearch

Deborah Page-Dumroese; Daniel Neary; Carl Trettin

2010-01-01

This workshop was developed to determine the state-of-the-science for soil monitoring on National Forests and Rangelands. We asked international experts in the field of soil monitoring, soil monitoring indicators, and basic forest soil properties to describe the limits of our knowledge and the ongoing studies that are providing new information. This workshop and the...

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.

Application of Terrestrial Ecosystem Monitoring under the CAFF Circumpolar Biodiversity Monitoring Program: Designing and Implementing Terrestrial Monitoring to Establish the Canadian High Arctic Research Station as a Flagship Arctic Environmental Monitoring Site

NASA Astrophysics Data System (ADS)

McLennan, D.; Kehler, D.

2016-12-01

The Canadian High Arctic Research Station (CHARS) is scheduled for completion in July 2017 and is the northern science component of Polar Knowledge Canada (POLAR). A mandated goal for POLAR is to establish the adjacent Experimental and Reference Area (ERA) as an Arctic Flagship monitoring site that will track change in Arctic terrestrial, freshwater and marine ecosystems. Situated in the community of Cambridge Bay, CHARS provides the opportunity to draw on the Indigenous Knowledge of local residents to help design and conduct the monitoring, and to operate 12 months a year. Monitoring at CHARS will be linked to networks nationally and internationally, and is being designed so that change in key indicators can be understood in terms of drivers and processes, modeled and scaled up regionally, and used to predict important changes in critical indicators. As a partner in the Circumpolar Biodiversity Monitoring Program (CBMP), the monitoring design for terrestrial ecosystems follows approaches outlined by the CBMP Terrestrial Expert Monitoring Group, who have listed key monitoring questions and identified a list of important Focal Ecosystem Components (FECs). To link drivers to FECs we are proposing a multi-scaled approach: 1) an Intensive Monitoring Area to establish replicated monitoring plots that track change in snow depth and condition, active layer depth, soil temperature, soil moisture, and soil solution chemistry that are spatially and temporally linked to changes in microbiological activity, CO2/CH4 net ecosystem flux, vegetation relative frequency, species composition, growth and foliar nutrient concentration, arthropod abundance, lemming abundance and health, and shorebird/songbird abundance and productivity. 2) These intensive observations are supported by watershed scale measures that will monitor, during the growing season, lemming winter nest abundance, songbird, shorebird and waterfowl staging and nesting, and other observations; in the winter we will monitor muskoxen, caribou, Arctic hare, wolf and Arctic fox using tracks and DNA analysis of fresh scat. 3) Ground measures will be supported by aerial flights and satellite remote sensing approaches to reach out with regional calibration-validation. Feedback is being sought at this time on project design, implementation and scope.

CTFS/ForestGEO: A global network to monitor forest interactions with a changing climate

NASA Astrophysics Data System (ADS)

Anderson-Teixeira, K. J.; Muller-Landau, H.; McMahon, S.; Davies, S. J.

2013-12-01

Forests are an influential component of the global carbon cycle and strongly influence Earth's climate. Climate change is altering the dynamics of forests globally, which may result in significant climate feedbacks. Forest responses to climate change entail both short-term ecophysiological responses and longer-term directional shifts in community composition. These short- and long-term responses of forest communities to climate change may be better understood through long-term monitoring of large forest plots globally using standardized methodology. Here, we describe a global network of forest research plots (CTFS/ForestGEO) of utility for understanding forest responses to climate change and consequent feedbacks to the climate system. CTFS/ForestGEO is an international network consisting of 51 sites ranging in size from 2-150 ha (median size: 25 ha) and spanning from 25°S to 52°N latitude. At each site, every individual > 1cm DBH is mapped and identified, and recruitment, growth, and mortality are monitored every 5 years. Additional measurements include aboveground productivity, carbon stocks, soil nutrients, plant functional traits, arthropod and vertebrates monitoring, DNA barcoding, airborne and ground-based LiDAR, micrometeorology, and weather monitoring. Data from this network are useful for understanding how forest ecosystem structure and function respond to spatial and temporal variation in abiotic drivers, parameterizing and evaluating ecosystem and earth system models, aligning airborne and ground-based measurements, and identifying directional changes in forest productivity and composition. For instance, CTFS/ForestGEO data have revealed that solar radiation and night-time temperature are important drivers of aboveground productivity in moist tropical forests; that tropical forests are mixed in terms of productivity and biomass trends over the past couple decades; and that the composition of Panamanian forests has shifted towards more drought-tolerant species. Ongoing monitoring will be vital to understanding global forest dynamics in an era of climate change.

Geostatistical assessment of Pb in soil around Paris, France.

PubMed

Saby, N; Arrouays, D; Boulonne, L; Jolivet, C; Pochot, A

2006-08-15

This paper presents a survey on soil Pb contamination around Paris (France) using the French soil monitoring network. The first aim of this study is to estimate the total amount of anthropogenic Pb inputs in soils and to distinguish Pb due to diffuse pollution from geochemical background Pb. Secondly, this study tries to find the main controlling factors of the spatial distribution of anthropogenic Pb. We used the technique of relative topsoil enhancement to evaluate the anthropogenic stock of Pb and we performed lognormal kriging to map Pb regional distribution. The results show a strong gradient of anthropogenic stock of Pb around the urban Paris area. We estimate a total amount of anthropogenic stock of Pb close to 143,000 metric tons, which corresponds to an average accumulation of 5.9 t km(-2). Our study suggests that a grid-based survey can help to quantify diffuse Pb contamination by using robust techniques of calculation and that it might also be used to validate predictions of deposition models.

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.

Study On The Application Of CBERS-02B To Quantitative Soil Erosion Monitoring

NASA Astrophysics Data System (ADS)

Shi, Mingchang; Xu, Jing; Wang, Lei; Wang, Xiaoyun; Mu, Jing

2010-10-01

Currently, the reduction of soil erosion is an important prerequisite for achieving ecological security. Since real-time and quantitative evaluation on regional soil erosion plays a significant role in reducing the soil erosion, soil erosion models are more and more widely used. Based on RUSLE model, this paper carries out the quantitative soil erosion monitoring in the Xi River Basin and its surrounding areas by using CBERS-02B CCD, DEM, TRMM and other data. Besides, it performs the validation for monitoring results by using remote sensing investigation results in 2005. The monitoring results show that in 2009, the total amount of soil erosion in the study area was 1.94×106t, the erosion area was 2055.2km2 (54.06% of the total area), and the average soil erosion modulus was 509.7t km-2 a-1. As a case using CBERS-02B data for quantitative soil erosion monitoring, this study provides experience on the application of CBERS-02B data in the field of quantitative soil erosion monitoring and also for local soil erosion management.

Long-Term Persistence of Pesticides and TPs in Archived Agricultural Soil Samples and Comparison with Pesticide Application.

PubMed

Chiaia-Hernandez, Aurea C; Keller, Armin; Wächter, Daniel; Steinlin, Christine; Camenzuli, Louise; Hollender, Juliane; Krauss, Martin

2017-09-19

For polar and more degradable pesticides, not many data on long-term persistence in soil under field conditions and real application practices exist. To assess the persistence of pesticides in soil, a multiple-compound screening method (log K ow 1.7-5.5) was developed based on pressurized liquid extraction, QuEChERS and LC-HRMS. The method was applied to study 80 polar pesticides and >90 transformation products (TPs) in archived topsoil samples from the Swiss Soil Monitoring Network (NABO) from 1995 to 2008 with known pesticide application patterns. The results reveal large variations between crop type and field sites. For the majority of the sites 10-15 pesticides were identified with a detection rate of 45% at concentrations between 1 and 330 μg/kg dw in soil. Furthermore, TPs were detected in 47% of the cases where the "parent-compound" was applied. Overall, residues of about 80% of all applied pesticides could be detected with half of these found as TPs with a persistence of more than a decade.

Smart Rocks for Bridge Scour Monitoring: Design and Localization Using Electromagnetic Techniques and Embedded Orientation Sensors

NASA Astrophysics Data System (ADS)

Radchenko, Andro

River bridge scour is an erosion process in which flowing water removes sediment materials (such as sand, rocks) from a bridge foundation, river beds and banks. As a result, the level of the river bed near a bridge pier is lowering such that the bridge foundation stability can be compromised, and the bridge can collapse. The scour is a dynamic process, which can accelerate rapidly during a flood event. Thus, regular monitoring of the scour progress is necessary to be performed at most river bridges. Present techniques are usually expensive, require large man/hour efforts, and often lack the real-time monitoring capabilities. In this dissertation a new method--'Smart Rocks Network for bridge scour monitoring' is introduced. The method is based on distributed wireless sensors embedded in ground underwater nearby the bridge pillars. The sensor nodes are unconstrained in movement, are equipped with years-lasting batteries and intelligent custom designed electronics, which minimizes power consumption during operation and communication. The electronic part consists of a microcontroller, communication interfaces, orientation and environment sensors (such as are accelerometer, magnetometer, temperature and pressure sensors), supporting power supplies and circuitries. Embedded in the soil nearby a bridge pillar the Smart Rocks can move/drift together with the sediments, and act as the free agent probes transmitting the unique signature signals to the base-station monitors. Individual movement of a Smart Rock can be remotely detected processing the orientation sensors reading. This can give an indication of the on-going scour progress, and set a flag for the on-site inspection. The map of the deployed Smart Rocks Network can be obtained utilizing the custom developed in-network communication protocol with signals intensity (RSSI) analysis. Particle Swarm Optimization (PSO) is applied for map reconstruction. Analysis of the map can provide detailed insight into the scour progress and topology. Smart Rocks Network wireless communication is based on the magnetoinductive (MI) link, at low (125 KHz) frequency, allowing for signal to penetrate through the water, rocks, and the bridge structure. The dissertation describes the Smart Rocks Network implementation, its electronic design and the electromagnetic/computational intelligence techniques used for the network mapping.

Ground Control Point - Wireless System Network for UAV-based environmental monitoring applications

NASA Astrophysics Data System (ADS)

Mejia-Aguilar, Abraham

2016-04-01

In recent years, Unmanned Aerial Vehicles (UAV) have seen widespread civil applications including usage for survey and monitoring services in areas such as agriculture, construction and civil engineering, private surveillance and reconnaissance services and cultural heritage management. Most aerial monitoring services require the integration of information acquired during the flight (such as imagery) with ground-based information (such as GPS information or others) for improved ground truth validation. For example, to obtain an accurate 3D and Digital Elevation Model based on aerial imagery, it is necessary to include ground-based information of coordinate points, which are normally acquired with surveying methods based on Global Position Systems (GPS). However, GPS surveys are very time consuming and especially for longer time series of monitoring data repeated GPS surveys are necessary. In order to improve speed of data collection and integration, this work presents an autonomous system based on Waspmote technologies build on single nodes interlinked in a Wireless Sensor Network (WSN) star-topology for ground based information collection and later integration with surveying data obtained by UAV. Nodes are designed to be visible from the air, to resist extreme weather conditions with low-power consumption. Besides, nodes are equipped with GPS as well as Inertial Measurement Unit (IMU), accelerometer, temperature and soil moisture sensors and thus provide significant advantages in a broad range of applications for environmental monitoring. For our purpose, the WSN transmits the environmental data with 3G/GPRS to a database on a regular time basis. This project provides a detailed case study and implementation of a Ground Control Point System Network for UAV-based vegetation monitoring of dry mountain grassland in the Matsch valley, Italy.

Performance of MODIS satellite and mesoscale model based land surface temperature for soil moisture deficit estimation using Neural Network

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Petropoulos, George P.; Gupta, Manika; Islam, Tanvir

2015-04-01

Soil Moisture Deficit (SMD) is a key variable in the water and energy exchanges that occur at the land-surface/atmosphere interface. Monitoring SMD is an alternate method of irrigation scheduling and represents the use of the suitable quantity of water at the proper time by combining measurements of soil moisture deficit. In past it is found that LST has a strong relation to SMD, which can be estimated by MODIS or numerical weather prediction model such as WRF (Weather Research and Forecasting model). By looking into the importance of SMD, this work focused on the application of Artificial Neural Network (ANN) for evaluating its capabilities towards SMD estimation using the LST data estimated from MODIS and WRF mesoscale model. The benchmark SMD estimated from Probability Distribution Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the calibration and validation experiments. The performances between observed and simulated SMD are assessed in terms of the Nash-Sutcliffe Efficiency (NSE), the Root Mean Square Error (RMSE) and the percentage of bias (%Bias). The application of the ANN confirmed a high capability WRF and MODIS LST for prediction of SMD. Performance during the ANN calibration and validation showed a good agreement between benchmark and estimated SMD with MODIS LST information with significantly higher performance than WRF simulated LST. The work presented showed the first comprehensive application of LST from MODIS and WRF mesoscale model for hydrological SMD estimation, particularly for the maritime climate. More studies in this direction are recommended to hydro-meteorological community, so that useful information will be accumulated in the technical literature domain for different geographical locations and climatic conditions. Keyword: WRF, Land Surface Temperature, MODIS satellite, Soil Moisture Deficit, Neural Network

Mountainous Ecosystem Sensor Array (MESA): a mesh sensor network for climate change research in remote mountainous environments

NASA Astrophysics Data System (ADS)

Robinson, P. W.; Neal, D.; Frome, D.; Kavanagh, K.; Davis, A.; Gessler, P. E.; Hess, H.; Holden, Z. A.; Link, T. E.; Newingham, B. A.; Smith, A. M.

2013-12-01

Developing sensor networks robust enough to perform unattended in the world's remote regions is critical since these regions serve as important benchmarks that lack anthropogenic influence. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. The MESA (Mountainous Ecosystem Sensor Array) project has faced these challenges and developed a wireless mesh sensor network across a 660 m topoclimatic gradient in a wilderness area in central Idaho. This sensor array uses advances in sensing, networking, and power supply technologies to provide near real-time synchronized data covering a suite of biophysical parameters used in ecosystem process models. The 76 sensors in the network monitor atmospheric carbon dioxide concentration, humidity, air and soil temperature, soil water content, precipitation, incoming and outgoing shortwave and longwave radiation, snow depth, wind speed and direction, and leaf wetness at synchronized time intervals ranging from two minutes to two hours and spatial scales from a few meters to two kilometers. We present our novel methods of placing sensors and network nodes above, below, and throughout the forest canopy without using meteorological towers. In addition, we explain our decision to use different forms of power (wind and solar) and the equipment we use to control and integrate power harvesting. Further, we describe our use of the network to sense and quantify its own power use. Using examples of environmental data from the project, we discuss how these data may be used to increase our understanding of the effects of climate change on ecosystem processes in mountainous environments. MESA sensor locations across a 700 m topoclimatic gradient at the University of Idaho Taylor Wilderness Research Station.

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.

Monitoring, analysis and classification of vegetation and soil data collected by a small and lightweight hyperspectral imaging system

NASA Astrophysics Data System (ADS)

Mönnig, Carsten

2014-05-01

The increasing precision of modern farming systems requires a near-real-time monitoring of agricultural crops in order to estimate soil condition, plant health and potential crop yield. For large sized agricultural plots, satellite imagery or aerial surveys can be used at considerable costs and possible time delays of days or even weeks. However, for small to medium sized plots, these monitoring approaches are cost-prohibitive and difficult to assess. Therefore, we propose within the INTERREG IV A-Project SMART INSPECTORS (Smart Aerial Test Rigs with Infrared Spectrometers and Radar), a cost effective, comparably simple approach to support farmers with a small and lightweight hyperspectral imaging system to collect remotely sensed data in spectral bands in between 400 to 1700nm. SMART INSPECTORS includes the whole remote sensing processing chain of small scale remote sensing from sensor construction, data processing and ground truthing for analysis of the results. The sensors are mounted on a remotely controlled (RC) Octocopter, a fixed wing RC airplane as well as on a two-seated Autogyro for larger plots. The high resolution images up to 5cm on the ground include spectra of visible light, near and thermal infrared as well as hyperspectral imagery. The data will be analyzed using remote sensing software and a Geographic Information System (GIS). The soil condition analysis includes soil humidity, temperature and roughness. Furthermore, a radar sensor is envisaged for the detection of geomorphologic, drainage and soil-plant roughness investigation. Plant health control includes drought stress, vegetation health, pest control, growth condition and canopy temperature. Different vegetation and soil indices will help to determine and understand soil conditions and plant traits. Additional investigation might include crop yield estimation of certain crops like apples, strawberries, pasture land, etc. The quality of remotely sensed vegetation data will be tested with ground truthing tools like a spectrometer, visual inspection and ground control panel. The soil condition will also be monitored with a wireless sensor network installed on the examined plots of interest. Provided with this data, a farmer can respond immediately to potential threats with high local precision. In this presentation, preliminary results of hyperspectral images of distinctive vegetation cover and soil on different pasture test plots are shown. After an evaluation period, the whole processing chain will offer farmers a unique, near real- time, low cost solution for small to mid-sized agricultural plots in order to easily assess crop and soil quality and the estimation of harvest. SMART INSPECTORS remotely sensed data will form the basis for an input in a decision support system which aims to detect crop related issues in order to react quickly and efficiently, saving fertilizer, water or pesticides.

Long-term SMOS soil moisture products: A comprehensive evaluation across scales and methods in the Duero Basin (Spain)

NASA Astrophysics Data System (ADS)

González-Zamora, Ángel; Sánchez, Nilda; Martínez-Fernández, José; Gumuzzio, Ángela; Piles, María; Olmedo, Estrella

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) Level 2 soil moisture and the new L3 product from the Barcelona Expert Center (BEC) were validated from January 2010 to June 2014 using two in situ networks in Spain. The first network is the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS), which has been extensively used for validating remotely sensed observations of soil moisture. REMEDHUS can be considered a small-scale network that covers a 1300 km2 region. The second network is a large-scale network that covers the main part of the Duero Basin (65,000 km2). At an existing meteorological network in the Castilla y Leon region (Inforiego), soil moisture probes were installed in 2012 to provide data until 2014. Comparisons of the temporal series using different strategies (total average, land use, and soil type) as well as using the collocated data at each location were performed. Additionally, spatial correlations on each date were computed for specific days. Finally, an improved version of the Triple Collocation (TC) method, i.e., the Extended Triple Collocation (ETC), was used to compare satellite and in situ soil moisture estimates with outputs of the Soil Water Balance Model Green-Ampt (SWBM-GA). The results of this work showed that SMOS estimates were consistent with in situ measurements in the time series comparisons, with Pearson correlation coefficients (R) and an Agreement Index (AI) higher than 0.8 for the total average and the land-use averages and higher than 0.85 for the soil-texture averages. The results obtained at the Inforiego network showed slightly better results than REMEDHUS, which may be related to the larger scale of the former network. Moreover, the best results were obtained when all networks were jointly considered. In contrast, the spatial matching produced worse results for all the cases studied. These results showed that the recent reprocessing of the L2 products (v5.51) improved the accuracy of soil moisture retrievals such that they are now suitable for developing new L3 products, such as the presented in this work. Additionally, the validation based on comparisons between dense/sparse networks and satellite retrievals at a coarse resolution showed that temporal patterns in the soil moisture are better reproduced than spatial patterns.

Quantifying the Influence of Near-Surface Water-Energy Budgets on Soil Thermal Properties Using a Network of Coupled Meteorological and Vadose Zone Instrument Arrays in Indiana, USA

NASA Astrophysics Data System (ADS)

Naylor, S.; Gustin, A. R.; Ellett, K. M.

2012-12-01

Weather stations that collect reliable, sustained meteorological data sets are becoming more widely distributed because of advances in both instrumentation and data server technology. However, sites collecting soil moisture and soil temperature data remain sparse with even fewer locations where complete meteorological data are collected in conjunction with soil data. Thanks to the advent of sensors that collect continuous in-situ thermal properties data for soils, we have gone a step further and incorporated thermal properties measurements as part of hydrologic instrument arrays in central and northern Indiana. The coupled approach provides insights into the variability of soil thermal conductivity and diffusivity attributable to geologic and climatological controls for various hydrogeologic settings. These data are collected to facilitate the optimization of ground-source heat pumps (GSHPs) in the glaciated Midwest by establishing publicly available data that can be used to parameterize system design models. A network of six monitoring sites was developed in Indiana. Sensors that determine thermal conductivity and diffusivity using radial differential temperature measurements around a heating wire were installed at 1.2 meters below ground surface— a typical depth for horizontal GSHP systems. Each site also includes standard meteorological sensors for calculating reference evapotranspiration following the methods by the Food and Agriculture Organization (FAO) of the United Nations. Vadose zone instrumentation includes time domain reflectometry soil-moisture and temperature sensors installed at 0.3-meter depth intervals down to a 1.8-meter depth, in addition to matric potential sensors at 0.15, 0.3, 0.6, and 1.2 meters. Cores collected at 0.3-meter intervals were analyzed in a laboratory for grain size distribution, bulk density, thermal conductivity, and thermal diffusivity. Our work includes developing methods for calibrating thermal properties sensors based on known standards and comparing measurements from transient line heat source devices. Transform equations have been developed to correct in-situ measurements of thermal conductivity and comparing these results with soil moisture data indicates that thermal conductivity can increase by as much as 25 percent during wetting front propagation. Thermal dryout curves have also been modeled based on laboratory conductivity data collected from core samples to verify field measurements, and alternatively, temperature profile data are used to calibrate near-surface temperature gradient models. We compare data collected across various spatial scales to assess the potential for upscaling near-surface thermal regimes based on available soils data. A long-term goal of the monitoring effort is to establish continuous data sets that determine the effect of climate variability on soil thermal properties such that expected ranges in thermal conductivity can be used to determine optimal ground-coupling loop lengths for GSHP systems.

Deploying temporary networks for upscaling of sparse network stations

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Kelly, Victoria; Hall, Mark; Palecki, Michael A.; Temimi, Marouane

2016-10-01

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.

Planning for execution monitoring on a planetary rover

NASA Technical Reports Server (NTRS)

Gat, Erann; Firby, R. James; Miller, David P.

1990-01-01

A planetary rover will be traversing largely unknown and often unknowable terrain. In addition to geometric obstacles such as cliffs, rocks, and holes, it may also have to deal with non-geometric hazards such as soft soil and surface breakthroughs which often cannot be detected until rover is in imminent danger. Therefore, the rover must monitor its progress throughout a traverse, making sure to stay on course and to detect and act on any previously unseen hazards. Its onboard planning system must decide what sensors to monitor, what landmarks to take position readings from, and what actions to take if something should go wrong. The planning systems being developed for the Pathfinder Planetary Rover to perform these execution monitoring tasks are discussed. This system includes a network of planners to perform path planning, expectation generation, path analysis, sensor and reaction selection, and resource allocation.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Road-networks, a practical indicator of human impacts on biodiversity in Tropical forests

NASA Astrophysics Data System (ADS)

Hosaka, T.; Yamada, T.; Okuda, T.

2014-02-01

Tropical forests sustain the most diverse plants and animals in the world, but are also being lost most rapidly. Rapid assessment and monitoring using remote sensing on biodiversity of tropical forests is needed to predict and evaluate biodiversity loss by human activities. Identification of reliable indicators of forest biodiversity and/or its loss is an urgent issue. In the present paper, we propose the density of road networks in tropical forests can be a good and practical indicator of human impacts on biodiversity in tropical forests through reviewing papers and introducing our preliminary survey in peninsular Malaysia. Many previous studies suggest a strong negative impact of forest roads on biodiversity in tropical rainforests since they changes microclimate, soil properties, drainage patterns, canopy openness and forest accessibility. Moreover, our preliminary survey also showed that even a narrow logging road (6 m wide) significantly lowered abundance of dung beetles (well-known bio-indicator in biodiversity survey in tropical forests) near the road. Since these road networks are readily to be detected with remote sensing approach such as aerial photographs and Lider, regulation and monitoring of the road networks using remote sensing techniques is a key to slow down the rate of biodiversity loss due to forest degradation in tropical forests.

Is the soil quality monitoring an effective tool in consumers' protection of agricultural crops from cadmium soil contamination?-a case of the Silesia region (Poland).

PubMed

Piekut, Agata; Baranowska, Renata; Marchwińska-Wyrwał, Ewa; Ćwieląg-Drabek, Małgorzata; Hajok, Ilona; Dziubanek, Grzegorz; Grochowska-Niedworok, Elżbieta

2017-12-16

The monitoring of soil quality should be a control tool used to reduce the adverse health effects arising from exposure to toxic chemicals in soil through cultivated crop absorption. The aim of the study was to evaluate the effectiveness of the monitoring and control system of soil quality in Poland, in terms of consumer safety, for agricultural plants cultivated in areas with known serious cadmium contamination, such as Silesia Province. To achieve the objective, the contents of cadmium in soils and vegetables in the Silesia administrative area were examined. The obtained results were compared with the results of soil contamination from the quality monitoring of arable soil in Poland. The studies show a significant exceedance of the permissible values of cadmium in soil samples and the vegetables cultivated on that soil. The threat to consumer health is a valid concern, although this threat was not indicated by the results of the national monitoring of soil quality. The results indicated an unequal distribution of risk to consumers resulting from contaminated soil. Moreover, the monitoring systems should be designed at the local or regional scale to guarantee the safety of consumers of edible plants cultivated in the areas contaminated with cadmium.

SoilSCAPE in-Situ Observations of Soil Moisture for SMAP Validation: Pushing the Envelopes of Spatial Coverage and Energy Efficiency in Sparse Wireless Sensor Networks (Invited)

NASA Astrophysics Data System (ADS)

Moghaddam, M.; Silva, A.; Clewley, D.; Akbar, R.; Entekhabi, D.

2013-12-01

Soil Moisture Sensing Controller and oPtimal Estimator (SoilSCAPE) is a wireless in-situ sensor network technology, developed under the support of NASA ESTO/AIST program, for multi-scale validation of soil moisture retrievals from the Soil Moisture Active and Passive (SMAP) mission. The SMAP sensor suite is expected to produce soil moisture retrievals at 3 km scale from the radar instrument, at 36 km from the radiometer, and at 10 km from the combination of the two sensors. To validate the retrieved soil moisture maps at any of these scales, it is necessary to perform in-situ observations at multiple scales (ten, hundreds, and thousands of meters), representative of the true spatial variability of soil moisture fields. The most recent SoilSCAPE network, deployed in the California central valley, has been designed, built, and deployed to accomplish this goal, and is expected to become a core validation site for SMAP. The network consists of up to 150 sensor nodes, each comprised of 3-4 soil moisture sensors at various depths, deployed over a spatial extent of 36 km by 36 km. The network contains multiple sub-networks, each having up to 30 nodes, whose location is selected in part based on maximizing the land cover diversity within the 36 km cell. The network has achieved unprecedented energy efficiency, longevity, and spatial coverage using custom-designed hardware and software protocols. The network architecture utilizes a nested strategy, where a number of end devices (EDs) communicate to a local coordinator (LC) using our recently developed hardware with ultra-efficient circuitry and best-effort-timeslot allocation communication protocol. The LCs in turn communicates with the base station (BS) via text messages and a new compression scheme. The hardware and software technologies required to implement this latest deployment of the SoilSCAPE network will be presented in this paper, and several data sets resulting from the measurements will be shown. The data are available publicly in near-real-time from the project web site, and are also available and searchable via an extensive set of metadata fields through the ORNL-DAAC.

Leaching of Br-, metolachlor, alachlor, atrazine, deethylatrazine and deisopropylatrazine in clayey vadoze zone: a field scale experiment in north-east Greece.

PubMed

Vryzas, Zisis; Papadakis, Emmanuel Nikolaos; Papadopoulou-Mourkidou, E

2012-04-15

An extensive four-year research program has been carried out to explore and acquire knowledge about the fundamental agricultural practices and processes affecting the mobility and bioavailability of pesticides in soils under semi-arid Mediterranean conditions. Pesticide leaching was studied under field conditions at five different depths using suction cups. Monitoring of metolachlor, alachlor, atrazine, deethylatrazine (DEA), deisopropylatrazine (DIA), and bromide ions in soil water, as well as dye patterns made apparent the significant role of preferential flow to the mobility of the studied compounds. Irrespective to their adsorption capacities and degradation rates, atrazine, metolachlor and bromide ions were simultaneously detected to 160 cm depth. Following 40 mm irrigation, just after their application, both alachlor and atrazine were leached to 160 cm depth within 18 h, giving maximum concentrations of 211 and 199 μg L(-1), respectively. Metolachlor was also detected in all depth when its application was followed by a rainfall event (50 mm) two weeks after its application. The greatest concentrations of atrazine, alachlor and metolachlor in soil water were 1795, 1166 and 845 μg L(-1), respectively. The greatest concentrations of atrazine's degradation products (both DEA and DIA) appeared later in the season compared to the parent compound. Metolachlor exhibited the greatest persistence with concentrations up to 10 μg L(-1) appearing in soil water 18 months after its application. Brilliant blue application followed by 40 mm irrigation clearly depict multi-branching network of preferential flow paths allowing the fast flow of the dye down to 150 cm within 24 h. This network was created by soil cracks caused by shrinking of dry soils, earthworms and plant roots. Chromatographic flow of the stained soil solution was evident only in the upper 10-15 cm of soil. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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.

Development and validation of a runoff and erosion model for lowland drained catchments

NASA Astrophysics Data System (ADS)

Grangeon, Thomas; Cerdan, Olivier; Vandromme, Rosalie; Landemaine, Valentin; Manière, Louis; Salvador-Blanes, Sébastien; Foucher, Anthony; Evrard, Olivier

2017-04-01

Modelling water and sediment transfer in lowland catchments is complex as both hortonian and saturation excess-flow occur in these environments. Moreover, their dynamics was complexified by the installation of tile drainage networks or stream redesign. To the best of our knowledge, few models are able to simulate saturation runoff as well as hortonian runoff in tile-drained catchments. Most of the time, they are used for small scale applications due to their high degree of complexity. In this context, a model of intermediate complexity was developed to simulate the hydrological and erosion processes at the catchment scale in lowland environments. This GIS-based, spatially distributed and lumped model at the event scale uses a theoretical hydrograph to approximate within-event temporal variations. It comprises two layers used to represent surface and subsurface transfers. Observations of soil surface characteristics (i.e. vegetation density, soil crusting and roughness) were used to document spatial variations of physical soil characteristics (e.g. infiltration capacity). Flow was routed depending on the local slope, using LIDAR elevation data. Both the diffuse and the gully erosion are explicitly described. The model ability to simulate water and sediment dynamics at the catchment scale was evaluated using the monitoring of a selection of flood events in a small, extensively cultivated catchment (the Louroux catchment, Loire River basin, central France; 25 km2). In this catchment, five monitoring stations were equipped with water level sensors, turbidity probes, and automatic samplers. Discharge and suspended sediment concentration were deduced from field measurements. One station was installed at the outlet of a tile drain and was used to parameterize fluxes supplied by the drainage network. The selected floods were representative of various rainfall and soil surface conditions (e.g. low-intensity rainfall occurring on saturated soils as well as intense rainfall occurring on dry soils in spring). The model was able to reproduce the runoff volumes for these different situations, and performed well, especially in winter (the relationship between observed and modeled values has R2=0.72) when most of the sediment are transferred. Therefore, future work will evaluate the model ability to reproduce the erosion and sediment dynamics in this catchment in order to provide a tool for sediment management in these lowland environments draining agricultural land where river siltation is problematic.

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Determining soil hydrologic characteristics on a remote forest watershed by continuous monitoring of soil water pressures, rainfall and runoff.

Treesearch

L.R. Ahuja; S. A. El-Swaify

1979-01-01

Continuous monitoring of soil-water pressures, rainfall and runoff under natural conditions was tested as a technique for determining soil hydrologic characteristics of a remote forest watershed plot. A completely battery-powered (and thus portable) pressure transducer–scanner–recorder system was assembled for monitoring of soil-water pressures in...

Mapping and predictive variations of soil bacterial richness across France

PubMed Central

Dequietd, Samuel; Saby, Nicolas P. A.; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition. PMID:29059218

Mapping and predictive variations of soil bacterial richness across France.

PubMed

Terrat, Sébastien; Horrigue, Walid; Dequiedt, Samuel; Saby, Nicolas P A; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

Impact of Vegetation Cover Fraction Parameterization schemes on Land Surface Temperature Simulation in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Lv, M.; Li, C.; Lu, H.; Yang, K.; Chen, Y.

2017-12-01

The parameterization of vegetation cover fraction (VCF) is an important component of land surface models. This paper investigates the impacts of three VCF parameterization schemes on land surface temperature (LST) simulation by the Common Land Model (CoLM) in the Tibetan Plateau (TP). The first scheme is a simple land cover (LC) based method; the second one is based on remote sensing observation (hereafter named as RNVCF) , in which multi-year climatology VCFs is derived from Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI (Normalized Difference Vegetation Index); the third VCF parameterization scheme derives VCF from the LAI simulated by LSM and clump index at every model time step (hereafter named as SMVCF). Simulated land surface temperature(LST) and soil temperature by CoLM with three VCF parameterization schemes were evaluated by using satellite LST observation and in situ soil temperature observation, respectively, during the period of 2010 to 2013. The comparison against MODIS Aqua LST indicates that (1) CTL produces large biases for both four seasons in early afternoon (about 13:30, local solar time), while the mean bias in spring reach to 12.14K; (2) RNVCF and SMVCF reduce the mean bias significantly, especially in spring as such reduce is about 6.5K. Surface soil temperature observed at 5 cm depth from three soil moisture and temperature monitoring networks is also employed to assess the skill of three VCF schemes. The three networks, crossing TP from West to East, have different climate and vegetation conditions. In the Ngari network, located in the Western TP with an arid climate, there are not obvious differences among three schemes. In Naqu network, located in central TP with a semi-arid climate condition, CTL shows a severe overestimates (12.1 K), but such overestimations can be reduced by 79% by RNVCF and 87% by SMVCF. In the third humid network (Maqu in eastern TP), CoLM performs similar to Naqu. However, at both Naqu and Maqu networks, RNVCF shows significant overestimation in summer, perhaps due to RNVCF ignores the growing characteristics of vegetation (mainly grass) in these two regions. Our results demonstrate that VCF schemes have significant influence on LSM performance, and indicate that it is important to consider vegetation growing characteristics in VCF schemes for different LCs.

A new detailed map of total phosphorus stocks in Australian soil.

PubMed

Viscarra Rossel, Raphael A; Bui, Elisabeth N

2016-01-15

Accurate data are needed to effectively monitor environmental condition, and develop sound policies to plan for the future. Globally, current estimates of soil total phosphorus (P) stocks are very uncertain because they are derived from sparse data, with large gaps over many areas of the Earth. Here, we derive spatially explicit estimates, and their uncertainty, of the distribution and stock of total P in Australian soil. Data from several sources were harmonized to produce the most comprehensive inventory of total P in soil of the continent. They were used to produce fine spatial resolution continental maps of total P in six depth layers by combining the bootstrap, a decision tree with piecewise regression on environmental variables and geostatistical modelling of residuals. Values of percent total P were predicted at the nodes of a 3-arcsecond (approximately 90 m) grid and mapped together with their uncertainties. We combined these predictions with those for bulk density and mapped the total soil P stock in the 0-30 cm layer over the whole of Australia. The average amount of P in Australian topsoil is estimated to be 0.98 t ha(-1) with 90% confidence limits of 0.2 and 4.2 t ha(-1). The total stock of P in the 0-30 cm layer of soil for the continent is 0.91 Gt with 90% confidence limits of 0.19 and 3.9 Gt. The estimates are the most reliable approximation of the stock of total P in Australian soil to date. They could help improve ecological models, guide the formulation of policy around food and water security, biodiversity and conservation, inform future sampling for inventory, guide the design of monitoring networks, and provide a benchmark against which to assess the impact of changes in land cover, land use and management and climate on soil P stocks and water quality in Australia. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

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.

A New Framework for Adptive Sampling and Analysis During Long-Term Monitoring and Remedial Action Management

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

Minsker, Barbara

2005-06-01

Yonas Demissie, a research assistant supported by the project, has successfully created artificial data and assimilated it into coupled Modflow and artificial neural network models. His initial findings show that the neural networks help correct errors in the Modflow models. Abhishek Singh has used test cases from the literature to show that performing model calibration with an interactive genetic algorithm results in significantly improved parameter values. Meghna Babbar, the third research assistant supported by the project, has found similar results when applying an interactive genetic algorithms to long-term monitoring design. She has also developed new types of interactive genetic algorithmsmore » that significantly improve performance. Gayathri Gopalakrishnan, the last research assistant who is partially supported by the project, has shown that sampling branches of phytoremediation trees is an accurate approach to estimating soil and groundwater contaminations in areas surrounding the trees at the Argonne 317/319 site.« less

PM2.5 Source Apportionment: Reconciling Receptor Models for U.S. Nonurban and Urban Long-Term Networks.

PubMed

Chen, L-W Antony; Watson, John G; Chow, Judith C; DuBois, Dave W; Herschberger, Lisa

2011-11-01

Chemical mass balance (CMB) and trajectory receptor models were applied to speciated particulate matter with aerodynamic diameter ≤2.5 μm (PM 2.5 ) measurements from Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network across the state of Minnesota as part of the Minnesota PM 2.5 Source Apportionment Study (MPSAS). CMB equations were solved by the Unmix, positive matrix factorization (PMF), and effective variance (EV) methods, giving collective source contribution and uncertainty estimates. Geological source profiles developed from local dust materials were either incorporated into the EV-CMB model or used to verify factors derived from Unmix and PMF. Common sources include soil dust, calcium (Ca)-rich dust, diesel and gasoline vehicle exhausts, biomass burning, secondary sulfate, and secondary nitrate. Secondary sulfate and nitrate aerosols dominate PM 2.5 mass (50-69%). Mobile sources outweigh area sources at urban sites, and vice versa at rural sites due to traffic emissions. Gasoline and diesel contributions can be separated using data from the STN, despite significant uncertainties. Major differences between MPSAS and earlier studies on similar environments appear to be the type and magnitude of stationary sources, but these sources are generally minor (<7%) in this and other studies. Ensemble back-trajectory analysis shows that the lower Midwestern states are the predominant source region for secondary ammoniated sulfate in Minnesota. It also suggests substantial contributions of biomass burning and soil dust from out-of-state on occasions, although a quantitative separation of local and regional contributions was not achieved in the current study. Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for a summary of input data, Unmix and PMF factor profiles, and additional maps. [Box: see text].

A High Space-Time Resolution Dataset Linking Meteorological Forcing and Hydro-Sedimentary Response in a Mesoscale Mediterranean Catchment (Auzon) of the Ardèche Region, France

NASA Astrophysics Data System (ADS)

Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.

2014-12-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.

A High Space-Time Resolution Dataset Linking Meteorological Forcing and Hydro-Sedimentary Response in a Mesoscale Mediterranean Catchment (Auzon) of the Ardèche Region, France

NASA Astrophysics Data System (ADS)

Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.

2015-12-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.

Monitoring groundwater storage changes in the highly seasonal humid tropics: Validation of GRACE measurements in the Bengal Basin

NASA Astrophysics Data System (ADS)

Shamsudduha, M.; Taylor, R. G.; Longuevergne, L.

2012-02-01

Satellite monitoring of changes in terrestrial water storage provides invaluable information regarding the basin-scale dynamics of hydrological systems where ground-based records are limited. In the Bengal Basin of Bangladesh, we test the ability of satellite measurements under the Gravity Recovery and Climate Experiment (GRACE) to trace both the seasonality and trend in groundwater storage associated with intensive groundwater abstraction for dry-season irrigation and wet-season (monsoonal) recharge. We show that GRACE (CSR, GRGS) datasets of recent (2003 to 2007) groundwater storage changes (ΔGWS) correlate well (r = 0.77 to 0.93, p value < 0.0001) with in situ borehole records from a network of 236 monitoring stations and account for 44% of the total variation in terrestrial water storage (ΔTWS); highest correlation (r = 0.93, p value < 0.0001) and lowest root-mean-square error (<4 cm) are realized using a spherical harmonic product of CSR. Changes in surface water storage estimated from a network of 298 river gauging stations and soil-moisture derived from Land Surface Models explain 22% and 33% of ΔTWS, respectively. Groundwater depletion estimated from borehole hydrographs (-0.52 ± 0.30 km3 yr-1) is within the range of satellite-derived estimates (-0.44 to -2.04 km3 yr-1) that result from uncertainty associated with the simulation of soil moisture (CLM, NOAH, VIC) and GRACE signal-processing techniques. Recent (2003 to 2007) estimates of groundwater depletion are substantially greater than long-term (1985 to 2007) mean (-0.21 ± 0.03 km3 yr-1) and are explained primarily by substantial increases in groundwater abstraction for the dry-season irrigation and public water supplies over the last two decades.

Monitoring water cycle elements using GNSS geodetic receivers at the field research station Marquardt, Germany

NASA Astrophysics Data System (ADS)

Simeonov, Tzvetan; Vey, Sibylle; Alshawaf, Fadwa; Dick, Galina; Guerova, Guergana; Güntner, Andreas; Hohmann, Christian; Kunwar, Ajeet; Trost, Benjamin; Wickert, Jens

2017-04-01

Water storage variations in the atmosphere and in soils are among the most dynamic within the Earth's water cycle. The continuous measurement of water storage in these media with a high spatial and temporal resolution is a challenging task, not yet completely solved by various observation techniques. With the development of the Global Navigation Satellite Systems (GNSS) a new approach for atmospheric water vapor estimation in the atmosphere and in parallel of soil moisture in the vicinity of GNSS ground stations was established in the recent years with several key advantages compared to traditional techniques. Regional and global GNSS networks are nowadays operationally used to provide the Integrated Water Vapor (IWV) information with high temporal resolution above the individual stations. Corresponding data products are used to improve the day-by-day weather prediction of leading forecast centers. Selected stations from these networks can be used to additionally derive the soil moisture in the vicinity of the receivers. Such parallel measurement of IWV and soil moisture using a single measuring device provides a unique possibility to analyze water fluxes between the atmosphere and the land surface. We installed an advanced experimental GNSS setup for hydrology at the field research station of the Leibniz Institute for Agricultural Engineering and Bioeconomy in Marquardt, around 30km West of Berlin, Germany. The setup includes several GNSS receivers, various Time Domain Reflectometry (TDR) sensors at different depths for soil moisture measurement and an meteorological station. The setup was mainly installed to develop and improve GNSS based techniques for soil moisture determination and to analyze GNSS IWV and SM in parallel on a long-term perspective. We introduce initial results from more than two years of measurements. The comparison in station Marquardt shows good agreement (correlation 0.79) between the GNSS derived soil moisture and the TDR measurements. A detailed study for several periods with different GNSS settings, vegetation and soil conditions in the vicinity of the station is presented with emphasis on the behavior of GNSS derived soil moisture, compared to TDR. Case studies of intense rainfall events and lasting dry periods show the interaction between the IWV and soil moisture.

Toward a standardized soil carbon database platform in the US Critical Zone Observatory Network

NASA Astrophysics Data System (ADS)

Filley, T. R.; Marini, L.; Todd-Brown, K. E.; Malhotra, A.; Harden, J. W.; Kumar, P.

2017-12-01

Within the soil carbon community of the US Critical Zone Observatory (CZO) Network, efforts are underway to promote network-level data syntheses and modeling projects and to identify barriers to data intercomparability. This represents a challenging goal given the diversity of soil carbon sampling methodologies, spatial and vertical resolution, carbon pool isolation protocols, subsequent measurement techniques, and matrix terminology. During the last annual meeting of the CZO SOC Working Group, Dec 11, 2016, it was decided that integration with, and potentially adoption of, a widely used, active, and mature data aggregation, archival, and visualization platform was the easiest route to achieve this ultimate goal. Additionally, to assess the state of deep and shallow soil C data among the CZO sites it was recommended that a comprehensive survey must be undertaken to identify data gaps and catalog the various soil sampling and analysis methodologies. The International Soil Carbon Network (ISCN) has a long history of leadership in the development of soil C data aggregation, archiving, and visualization tools and currently houses data for over 70,000 soil cores contributed from international soil carbon community. Over the past year, members of the CZO network and the ISCN have met to discuss logistics of adopting the ISCN template within the CZO. Collaborative efforts among all of the CZO site data managers, led by the Intensively Managed Landscapes CZO, will evaluate feasibility of adoption of the ISCN template, or some modification thereof, and distribution to the appropriate soil scientists for data upload and aggregation. Partnering with ISCN also ensures that soil characteristics from the US CZO are placed in a developing global soil context and paves the way for future integration of data from other international CZO networks. This poster will provide an update of this overall effort along with a summary of data products, partnering networks, and recommendations for data language template and the future CZO APIs.

In-situ soil loss monitoring in a small Mediterranean catchment to assess the siltation risk of a limno-reservoir

NASA Astrophysics Data System (ADS)

Molina-Navarro, E.; Bienes-Allas, R.; Martínez-Pérez, S.; Sastre-Merlín, A.

2012-04-01

The existence of large reservoirs under Mediterranean climate causes some negative impacts. The construction of small dams in the riverine zone of these reservoirs is an innovative idea designed to counteract some of those impacts, generating a body of water with a constant level which we have termed "limno-reservoirs". Pareja Limno-reservoir, located in the influence area of the Entrepeñas Reservoir (Guadalajara) is among the first limno-reservoirs built in Spain, and the first having a double function: environmental and recreational. The limno-reservoir basin (85.5 Km2) enjoys a Mediterranean climate, however, cold temperatures prevail in winter and maximum annual variation may be around 50 °C. Average annual precipitation is 600 mm, with high variability too. Most of the basin is dominated by a high limestone plateau, while a more erodible lithology surfaces in the hillsides of the Ompólveda River and its tributaries. These characteristics make the basin representative of central Spain. Despite the unquestionable interest of the initiative, it construction has raised some issues about its environmental viability. One of them is related to its siltation risk, as the area shows signs of high erosion rates that have been contrasted in previous empirical studies. An in-situ soil loss monitoring network has been installed in order to determine the soil loss and deposition rates in the limno-reservoir basin (85.5 km2). It includes 15 sampling plots for inter-rill erosion and 8 for sedimentation, each one containing 16 erosion sticks. Rill erosion was studied monitoring 8 rills with a needle micro-profiler, quantifying the sediment deposition in their terminal zone with sticks. These control points have been located in places where the soil type, land use and slope present are representative of the basin, in order to extrapolate the results to similar areas. In-situ monitoring has been performed for three years, starting in 2009 and carrying out sampling every 3 months. Soil samples have been taken in the different areas monitored in order to obtain bulk density values. First results suggest that average soil loss rates have ranged from 3 to 75 T ha-1 year-1, while average deposition rates have been between 0 and 220 T ha-1 year-1. Maximum soil loss rates has been seen in hillsades of clayey lithology and low vegetation coverage, representing a serious erosion risk. These results, extrapolated to different areas of the basin, have allowed estimating yield rates in the limno-reservoir. To check the degree of fit of these predictions, we proceeded to measure the thickness of sediments deposited in the limno-reservoir by taking of witnesses.

Monitoring of Carbon Dioxide and Methane Plumes from Combined Ground-Airborne Sensors

NASA Astrophysics Data System (ADS)

Jacob, Jamey; Mitchell, Taylor; Honeycutt, Wes; Materer, Nicholas; Ley, Tyler; Clark, Peter

2016-11-01

A hybrid ground-airborne sensing network for real-time plume monitoring of CO2 and CH4 for carbon sequestration is investigated. Conventional soil gas monitoring has difficulty in distinguishing gas flux signals from leakage with those associated with meteorologically driven changes. A low-cost, lightweight sensor system has been developed and implemented onboard a small unmanned aircraft and is combined with a large-scale ground network that measures gas concentration. These are combined with other atmospheric diagnostics, including thermodynamic data and velocity from ultrasonic anemometers and multi-hole probes. To characterize the system behavior and verify its effectiveness, field tests have been conducted with simulated discharges of CO2 and CH4 from compressed gas tanks to mimic leaks and generate gaseous plumes, as well as field tests over the Farnsworth CO2-EOR site in the Anadarko Basin. Since the sensor response time is a function of vehicle airspeed, dynamic calibration models are required to determine accurate location of gas concentration in space and time. Comparisons are made between the two tests and results compared with historical models combining both flight and atmospheric dynamics. Supported by Department of Energy Award DE-FE0012173.

Effects of the soil pore network architecture on the soil's physical functionalities

NASA Astrophysics Data System (ADS)

Smet, Sarah; Beckers, Eléonore; Léonard, Angélique; Degré, Aurore

2017-04-01

The soil fluid movement's prediction is of major interest within an agricultural or environmental scope because many processes depend ultimately on the soil fluids dynamic. It is common knowledge that the soil microscopic pore network structure governs the inner-soil convective fluids flow. There isn't, however, a general methodthat consider the pore network structure as a variable in the prediction of thecore scale soil's physical functionalities. There are various possible representations of the microscopic pore network: sample scale averaged structural parameters, extrapolation of theoretic pore network, or use of all the information available by modeling within the observed pore network. Different representations implydifferent analyzing methodologies. To our knowledge, few studies have compared the micro-and macroscopic soil's characteristics for the same soil core sample. The objective of our study is to explore the relationship between macroscopic physical properties and microscopic pore network structure. The saturated hydraulic conductivity, the air permeability, the retention curve, and others classical physical parameters were measured for ten soil samples from an agricultural field. The pore network characteristics were quantified through the analyses of X-ray micro-computed tomographic images(micro-CT system Skyscan-1172) with a voxel size of 22 µm3. Some of the first results confirmed what others studies had reported. Then, the comparison between macroscopic properties and microscopic parameters suggested that the air movements depended mostly on the pore connectivity and tortuosity than on the total porosity volume. We have also found that the fractal dimension calculated from the X-ray images and the fractal dimension calculated from the retention curve were significantly different. Our communication will detailthose results and discuss the methodology: would the results be similar with a different voxel size? What are the calculated and measured parameters uncertainties? Sarah Smet, as a research fellow, acknowledges the support of the National Fund for Scientific Research (Brussels, Belgium).

Estimation of soil organic carbon in forests of the United States

NASA Astrophysics Data System (ADS)

Domke, G. M.; Perry, C. H.; Walters, B. F.; Woodall, C. W.; Nave, L. E.; Swanston, C.

2015-12-01

Soil organic carbon (SOC) is the largest terrestrial carbon (C) sink on earth and management of this pool is a critical component of global efforts to mitigate atmospheric C concentrations. Soil organic carbon is also a key indicator of soil quality as it affects essential biological, chemical, and physical soil functions such as nutrient cycling, water retention, and soil structure maintenance. Much of the SOC on earth is found in forest ecosystems and is thought to be relatively stable. That said, there is growing evidence that SOC may be sensitive to disturbance and global change drivers. In the United States (US), SOC in forests is monitored by the national forest inventory (NFI) conducted by the Forest Inventory and Analysis (FIA) program within the US Department of Agriculture, Forest Service. The FIA program currently uses SOC predictions based on SSURGO/STATSGO data to populate the NFI. Most of estimates of SOC in forests from the SSURGO/STATSGO data are based primarily upon expert opinion and lack systematic field observations. The FIA program has been consistently measuring soil attributes as part of the NFI since 2001 and has amassed an extensive inventory of SOC in forests in the conterminous US and coastal Alaska. Here we present estimates of SOC obtained using data from the NFI and International Soil Carbon Network and describe the modeling framework used to compile estimates for United Nations Framework Convention on Climate Change reporting.

3D soil water nowcasting using electromagnetic conductivity imaging and the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Huang, Jingyi; McBratney, Alex; Minasny, Budiman; Triantafilis, John

2017-04-01

Mapping and immediate forecasting of soil water content (θ) and its movement can be challenging. Although apparent electrical conductivity (ECa) measured by electromagnetic induction has been used, it is difficult to apply it along a transect or across a field. Across a 3.95-ha field with varying soil texture, an ensemble Kalman filter (EnFK) was used to monitor and nowcast θ dynamics in 2-d and 3-d over 16 days. The EnKF combined a physical model fitted with θ measured by soil moisture sensors and an Artificial Neural Network model comprising estimate of true electrical conductivity (σ) generated by inversions of DUALEM-421S ECa data. Results showed that the spatio-temporal variation in θ can be successfully modelled using the EnKF (Lin's concordance = 0.89). Soil water dried fast at the beginning of the irrigation and decreased with time and soil depth, which were consistent with the classical soil drying theory and experiments. It was also found that the soil dried fast in the loamy and duplex soils across the field, which was attributable to deep drainage and preferential flows. It was concluded that the EnKF approach can be used to better the irrigation practice so that variation in irrigation is minimised and irrigation efficiency is improved by applying variable rates of irrigation across the field. In addition, soil water status can be nowcasted using this method with weather forecast information, which will provide guidance to farmers for real-time irrigation management.

The response of soil solution chemistry in European forests to decreasing acid deposition.

PubMed

Johnson, James; Graf Pannatier, Elisabeth; Carnicelli, Stefano; Cecchini, Guia; Clarke, Nicholas; Cools, Nathalie; Hansen, Karin; Meesenburg, Henning; Nieminen, Tiina M; Pihl-Karlsson, Gunilla; Titeux, Hugues; Vanguelova, Elena; Verstraeten, Arne; Vesterdal, Lars; Waldner, Peter; Jonard, Mathieu

2018-03-31

Acid deposition arising from sulphur (S) and nitrogen (N) emissions from fossil fuel combustion and agriculture has contributed to the acidification of terrestrial ecosystems in many regions globally. However, in Europe and North America, S deposition has greatly decreased in recent decades due to emissions controls. In this study, we assessed the response of soil solution chemistry in mineral horizons of European forests to these changes. Trends in pH, acid neutralizing capacity (ANC), major ions, total aluminium (Al tot ) and dissolved organic carbon were determined for the period 1995-2012. Plots with at least 10 years of observations from the ICP Forests monitoring network were used. Trends were assessed for the upper mineral soil (10-20 cm, 104 plots) and subsoil (40-80 cm, 162 plots). There was a large decrease in the concentration of sulphate (SO42-) in soil solution; over a 10-year period (2000-2010), SO42- decreased by 52% at 10-20 cm and 40% at 40-80 cm. Nitrate was unchanged at 10-20 cm but decreased at 40-80 cm. The decrease in acid anions was accompanied by a large and significant decrease in the concentration of the nutrient base cations: calcium, magnesium and potassium (Bc = Ca 2+  + Mg 2+  + K + ) and Al tot over the entire dataset. The response of soil solution acidity was nonuniform. At 10-20 cm, ANC increased in acid-sensitive soils (base saturation ≤10%) indicating a recovery, but ANC decreased in soils with base saturation >10%. At 40-80 cm, ANC remained unchanged in acid-sensitive soils (base saturation ≤20%, pHCaCl2 ≤ 4.5) and decreased in better-buffered soils (base saturation >20%, pHCaCl2 > 4.5). In addition, the molar ratio of Bc to Al tot either did not change or decreased. The results suggest a long-time lag between emission abatement and changes in soil solution acidity and underline the importance of long-term monitoring in evaluating ecosystem response to decreases in deposition. © 2018 John Wiley & Sons Ltd.

[Monitoring of water and salt transport in silt and sandy soil during the leaching process].

PubMed

Fu, Teng-Fei; Jia, Yong-Gang; Guo, Lei; Liu, Xiao-Lei

2012-11-01

Water and salt transport in soil and its mechanism is the key point of the saline soil research. The dynamic rule of water and transport in soil during the leaching process is the theoretical basis of formation, flush, drainage and improvement of saline soil. In this study, a vertical infiltration experiment was conducted to monitor the variation in the resistivity of silt and sandy soil during the leaching process by the self-designed automatic monitoring device. The experimental results showed that the peaks in the resistivity of the two soils went down and faded away in the course of leaching. It took about 30 minutes for sandy soil to reach the water-salt balance, whereas the silt took about 70 minutes. With the increasing leaching times, the desalination depth remained basically the same, being 35 cm for sandy soil and 10 cm for the silt from the top to bottom of soil column. Therefore, 3 and 7 leaching processes were required respectively for the complete desalination of the soil column. The temporal and spatial resolution of this monitoring device can be adjusted according to the practical demand. This device can not only achieve the remote, in situ and dynamic monitoring data of water and salt transport, but also provide an effective method in monitoring, assessment and early warning of salinization.

Tools based on multivariate statistical analysis for classification of soil and groundwater in Apulian agricultural sites.

PubMed

Ielpo, Pierina; Leardi, Riccardo; Pappagallo, Giuseppe; Uricchio, Vito Felice

2017-06-01

In this paper, the results obtained from multivariate statistical techniques such as PCA (Principal component analysis) and LDA (Linear discriminant analysis) applied to a wide soil data set are presented. The results have been compared with those obtained on a groundwater data set, whose samples were collected together with soil ones, within the project "Improvement of the Regional Agro-meteorological Monitoring Network (2004-2007)". LDA, applied to soil data, has allowed to distinguish the geographical origin of the sample from either one of the two macroaeras: Bari and Foggia provinces vs Brindisi, Lecce e Taranto provinces, with a percentage of correct prediction in cross validation of 87%. In the case of the groundwater data set, the best classification was obtained when the samples were grouped into three macroareas: Foggia province, Bari province and Brindisi, Lecce and Taranto provinces, by reaching a percentage of correct predictions in cross validation of 84%. The obtained information can be very useful in supporting soil and water resource management, such as the reduction of water consumption and the reduction of energy and chemical (nutrients and pesticides) inputs in agriculture.

Coincident Above- and Below-ground Autonomous Monitoring to Quantify Co-variability in Permafrost, Soil and Vegetation Properties in Arctic Tundra: Supporting Data

DOE Data Explorer

Baptiste Dafflon; Rusen Oktem; John Peterson; Craig Ulrich; Anh Phuong Tran; Vladimir Romanovsky; Susan Hubbard

2017-05-10

The dataset contains measurements obtained through electrical resistivity tomography (ERT) to monitor soil properties, pole-mounted optical cameras to monitor vegetation dynamics, point probes to measure soil temperature, and periodic manual measurements of thaw layer thickness, snow thickness and soil dielectric permittivity.

The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

NASA Astrophysics Data System (ADS)

Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.

2011-02-01

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status January 2011), the ISMN contains data of 16 networks and more than 500 stations located in the North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

NASA Astrophysics Data System (ADS)

Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Xaver, A.; Gruber, A.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.

2011-05-01

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

Event-based soil loss models for construction sites

NASA Astrophysics Data System (ADS)

Trenouth, William R.; Gharabaghi, Bahram

2015-05-01

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

Hydrologic response across a snow persistence gradient on the west and east slopes of the Rocky Mountains in Colorado

NASA Astrophysics Data System (ADS)

Richard, G. A.; Hammond, J. C.; Kampf, S. K.; Moore, C. D.; Eurich, A.

2017-12-01

Snowpack trend analyses and modeling studies suggest that lower elevation snowpacks in mountain regions are most sensitive to drought and warming temperatures, however, in Colorado, most snow monitoring occurs in the high elevations where snow lasts throughout the winter and most streamflow monitoring occurs at lower elevations. The lack of combined snow and streamflow monitoring in watersheds along the transition from intermittent to persistent snow creates a gap in our understanding of snowmelt and runoff within the intermittent-persistent snow transition. Expanded hydrologic monitoring that spans the gradient of snow conditions in Colorado can help improve streamflow prediction and inform land and water managers. This study established hydrologic monitoring watersheds in intermittent, transitional, and persistent snow zones on the east slope and west slope of the Rocky Mountains in Colorado, and uses this monitoring network to improve understanding of how snow accumulation and melt affect soil moisture and streamflow generation under different snow conditions. We monitored six small watersheds (three west slope, three east slope) (0.8 to 3.9 km2) that drain intermittent, transitional, and persistent snow zones. At each site, we measured: streamflow, snow depth, soil moisture, precipitation, air temperature, and snow water equivalent (SWE). In our first season of monitoring, the west slope persistent and transitional sites had more mid-winter melt and infiltration, shorter snowpack duration, and lower peak SWE than the east slope sites. Snow cover remained at the east slope persistent site into June, whereas much of the snow at the persistent site on the west slope had already melted by early June. The difference in soil water input likely has consequences for streamflow response that we will continue to examine in future years. At the west slope intermittent site, the stream did not flow during the entire first year of monitoring, while at the east slope intermittent site, the streams flowed intermittently during winter and spring, likely a result of different subsurface geology. With our ongoing watershed monitoring across a broad range of snow conditions in Colorado, we continue to learn about the factors that increase or decrease streamflow in the headwater streams that supply the state's major rivers.

Development of an Experimental African Drought Monitoring and Seasonal Forecasting System: A First Step towards a Global Drought Information System

NASA Astrophysics Data System (ADS)

Wood, E. F.; Chaney, N.; Sheffield, J.; Yuan, X.

2012-12-01

Extreme hydrologic events in the form of droughts are a significant source of social and economic damage. Internationally, organizations such as UNESCO, the Group on Earth Observations (GEO), and the World Climate Research Programme (WCRP) have recognized the need for drought monitoring, especially for the developing world where drought has had devastating impacts on local populations through food insecurity and famine. Having the capacity to monitor droughts in real-time, and to provide drought forecasts with sufficient warning will help developing countries and international programs move from the management of drought crises to the management of drought risk. While observation-based assessments, such as those produced by the US Drought Monitor, are effective for monitoring in countries with extensive observation networks (of precipitation in particular), their utility is lessened in areas (e.g., Africa) where observing networks are sparse. For countries with sparse networks and weak reporting systems, remote sensing observations can provide the real-time data for the monitoring of drought. More importantly, these datasets are now available for at least a decade, which allows for the construction of a climatology against which current conditions can be compared. In this presentation we discuss the development of our multi-lingual experimental African Drought Monitor (ADM) (see http://hydrology.princeton.edu/~nchaney/ADM_ML). At the request of UNESCO, the ADM system has been installed at AGRHYMET, a regional climate and agricultural center in Niamey, Niger and at the ICPAC climate center in Nairobi, Kenya. The ADM system leverages off our U.S. drought monitoring and forecasting system (http://hydrology.princeton.edu/forecasting) that uses the NLDAS data to force the VIC land surface model (LSM) at 1/8th degree spatial resolution for the estimation of our soil moisture drought index (Sheffield et al., 2004). For the seasonal forecast of drought, CFSv2 climate forecasts are bias corrected, downscaled and used as inputs to the VIC LSM as well as forecasts based on ESP and CPC official seasonal outlook. For Africa, data from a combination of remote sensing (TMPA-based precipitation, land cover characteristics) and GFS analysis fields (temperature and wind) are used to monitor drought using our soil moisture drought index as well as 1, 3 and and 6-month SPI. River discharge is also estimated at over 900 locations. Seasonal forecasts have been developed using CFSv2 climate forecasts following the approaches used over CONUS. We will discuss the performance of the system to evaluate the depiction of drought over various scales, from regional to the African continent, and over a number of years to capture multiple drought events. Furthermore, the hindcasts from the seasonal drought forecast system are analyzed to assess the ability of seasonal climate models to detect drought on-set and its recovery. Finally, we will discuss whether our ADM provides a pathway to a Global Drought Information System, a goal of the WCRP Drought Task Force.

Monitoring technologies for the evaluation of a Soil-Aquifer-Treatment system in coastal aquifer environments.

NASA Astrophysics Data System (ADS)

Kallioras, Andreas; Tsertou, Athanasia; Foglia, Laura; Bumberger, Jan; Vienken, Thomas; Dietrich, Peter; Schüth, Christoph

2014-05-01

Artificial recharge of groundwater has an important role to play in water reuse. Treated sewage effluent can be infiltrated into the ground for recharge of aquifers. As the effluent water moves through the soil and the aquifer, it undergoes significant quality improvements through physical, chemical, and biological processes in the underground environment. Collectively, these processes and the water quality improvement obtained are called soil-aquifer-treatment (SAT) or geopurification. Recharge systems for SAT can be designed as infiltration-recovery systems, where all effluent water is recovered as such from the aquifer, or after blending with native groundwater. SAT typically removes essentially all suspended solids, biochemical oxygen demand (BOD), and pathogens (viruses, bacteria, protozoa, and helminthic eggs). Concentrations of synthetic organic carbon, phosphorous, and heavy metals are greatly reduced. The pilot site of LTCP will involve the employment of infiltration basins, which will be using waters of impaired quality as a recharge source, and hence acting as a Soil-Aquifer-Treatment, SAT, system. T he LTCP site will be employed as a pilot SAT system complemented by new technological developments, which will be providing continuous monitoring of the quantitative and qualitative characteristics of infiltrating groundwater through all hydrologic zones (i.e. surface, unsaturated and saturated zone). This will be achieved through the development and installation of an integrated system of prototype sensors, installed on-site, and offering a continuous evaluation of the performance of the SAT system. An integrated approach of the performance evaluation of any operating SAT system should aim at parallel monitoring of all hydrologic zones, proving the sustainability of all involved water quality treatment processes within unsaturated and saturated zone. Hence a prototype system of Time Domain Reflectometry (TDR) sensors will be developed, in order to achieve continuous quantitative monitoring of the unsaturated zone through the entire soil column down to significant depths below the SAT basin. The above technique will offer continuous monitoring of infiltration rates and possible mechanical clogging effects. The qualitative monitoring of the unsaturated zone will be achieved through the installation of appropriate pore-water samplers within a multi-level basis, ensuring repeatability of sampling of infiltrating water of impaired quality. This study also involves the qualitative and quantitative assessment of the Lavrion multi-aquifer system through continuous monitoring of the performance of (i) the alluvial aquifer and its potential for additional water treatment as well as (ii) the effects of the SAT system for countermeasuring seawater intrusion in the area of Lavrion. Additionally, setup and calibration of numerical flow and transport models for evaluating and optimizing different operational modes of the SAT system within both saturated and unsaturated zones will be conducted. The monitoring system will be connected to an ad-hoc wireless network for continuous data transfer within the SAT facilities. It is envisaged that the development and combined application of all the above technologies will provide an integrated monitoring platform for the evaluation of SAT system performance.

Estimating surface soil moisture from SMAP observations using a neural network technique

USDA-ARS?s Scientific Manuscript database

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to June 2016 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observ...

Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra

NASA Astrophysics Data System (ADS)

Dafflon, Baptiste; Oktem, Rusen; Peterson, John; Ulrich, Craig; Tran, Anh Phuong; Romanovsky, Vladimir; Hubbard, Susan S.

2017-06-01

Coincident monitoring of the spatiotemporal distribution of and interactions between land, soil, and permafrost properties is important for advancing our understanding of ecosystem dynamics. In this study, a novel monitoring strategy was developed to quantify complex Arctic ecosystem responses to the seasonal freeze-thaw-growing season conditions. The strategy exploited autonomous measurements obtained through electrical resistivity tomography to monitor soil properties, pole-mounted optical cameras to monitor vegetation dynamics, point probes to measure soil temperature, and periodic manual measurements of thaw layer thickness, snow thickness, and soil dielectric permittivity. The spatially and temporally dense monitoring data sets revealed several insights about tundra system behavior at a site located near Barrow, AK. In the active layer, the soil electrical conductivity (a proxy for soil water content) indicated an increasing positive correlation with the green chromatic coordinate (a proxy for vegetation vigor) over the growing season, with the strongest correlation (R = 0.89) near the typical peak of the growing season. Soil conductivity and green chromatic coordinate also showed significant positive correlations with thaw depth, which is influenced by soil and surface properties. In the permafrost, soil electrical conductivity revealed annual variations in solute concentration and unfrozen water content, even at temperatures well below 0°C in saline permafrost. These conditions may contribute to an acceleration of long-term thaw in Coastal permafrost regions. Demonstration of this first aboveground and belowground geophysical monitoring approach within an Arctic ecosystem illustrates its significant potential to remotely "visualize" permafrost, soil, and vegetation ecosystem codynamics in high resolution over field relevant scales.

Mediterranean Agricultural Soil Conservation under global Change: The MASCC project.

NASA Astrophysics Data System (ADS)

Raclot, Damien; Ciampalini, Rossano

2017-04-01

The MASCC project (2016-2019, http://mascc-project.org) aims to address mitigation and adaptation strategies to global change by assessing current and future development of Mediterranean agricultural soil vulnerability to erosion in relation to projected land use, agricultural practices and climate change. It targets to i) assess the similarities/dissimilarities in dominant factors affecting the current Mediterranean agricultural soil vulnerability by exploring a wide range of Mediterranean contexts; ii) improve the ability to evaluate the impact of extreme events on both the current and projected agricultural soil vulnerability and the sediment delivery at catchment outlet; iii) evaluate the vulnerability and resilience of agricultural production to a combination of potential changes in a wide range of Mediterranean contexts, iv) and provide guidelines on sustainable agricultural conservation strategies adapted to each specific agro-ecosystem and taking into consideration both on- and off-site erosion effects and socio-economics issues. To achieve these objectives, the MASCC project consortium gather researchers from six Mediterranean countries (France, Morocco, Tunisia, Italy, Spain and Portugal) which monitor mid- to long-term environmental catchments and benefit from mutual knowledge created from previous projects and network. The major assets for MASCC are: i) the availability of an unrivalled database on catchment soil erosion and innovative agricultural practices comprising a wide range of Mediterranean contexts, ii) the capacity to better evaluate the impact of extreme events on soil erosion, iii) the expert knowledge of the LANDSOIL model, a catchment-scale integrated approach of the soil-landscape system that enables to simulate both the sediment fluxes at the catchment outlet and the intra-catchment soil evolving properties and iv) the multi-disciplinarity of the involved researchers with an international reputation in the fields of soil science, modelling changes in soil properties, erosion and sediment transport, agronomy and socio-economy. Beyond the description of the MASCC project, this presentation will describe the first results on the variability of soil erosion observed in the monitored catchments and on the impact of major events on the current soil erosion delivered at catchment outlet. As a starting project, MASCC will foster the involvement of all additional participants that would like to contribute to the project. Acknowledgements: We thanks the Arimnet2 ERA-Net initiative that funded the MASCC project. Keywords: Soil erosion, Agriculture, Conservation, Global change, Mediterranean area.

Disposal and improvement of contaminated by waste extraction of copper mining in chile

NASA Astrophysics Data System (ADS)

Naranjo Lamilla, Pedro; Blanco Fernández, David; Díaz González, Marcos; Robles Castillo, Marcelo; Decinti Weiss, Alejandra; Tapia Alvarez, Carolina; Pardo Fabregat, Francisco; Vidal, Manuel Miguel Jordan; Bech, Jaume; Roca, Nuria

2016-04-01

This project originated from the need of a mining company, which mines and processes copper ore. High purity copper is produced with an annual production of 1,113,928 tons of concentrate to a law of 32%. This mining company has generated several illegal landfills and has been forced by the government to make a management center Industrial Solid Waste (ISW). The forecast volume of waste generated is 20,000 tons / year. Chemical analysis established that the studied soil has a high copper content, caused by nature or from the spread of contaminants from mining activities. Moreover, in some sectors, soil contamination by mercury, hydrocarbons and oils and fats were detected, likely associated with the accumulation of waste. The waters are also impacted by mining industrial tasks, specifically copper ores, molybdenum, manganese, sulfates and have an acidic pH. The ISW management center dispels the pollution of soil and water and concentrating all activities in a technically suitable place. In this center the necessary guidelines for the treatment and disposal of soil contamination caused by uncontrolled landfills are given, also generating a leachate collection system and a network of fluid monitoring physicochemical water quality and soil environment. Keywords: Industrial solid waste, soil contamination, Mining waste

Development of wireless sensor network for landslide monitoring system

NASA Astrophysics Data System (ADS)

Suryadi; Puranto, Prabowo; Adinanta, Hendra; Tohari, Adrin; Priambodo, Purnomo S.

2017-05-01

A wireless sensor network has been developed to monitor soil movement of some observed areas periodically. The system consists of four nodes and one gateway which installed on a scope area of 0.2 Km2. Each of nodehastwo types of sensor,an inclinometer and an extensometer. An inclinometer sensor is used to measure the tilt of a structure while anextensometer sensor is used to measure the displacement of soil movement. Each of nodeisalso supported by awireless communication device, a solar power supply unit, and a microcontroller unit called sensor module. In this system, there is also gateway module as a main communication system consistinga wireless communication device, power supply unit, and rain gauge to measure the rainfall intensity of the observed area. Each sensor of inclinometer and extensometer isconnected to the sensor module in wiring system but sensor module iscommunicating with gateway in a wireless system. Those four nodes are alsoconnectedeach other in a wireless system collecting the data from inclinometer and extensometer sensors. Module Gateway istransmitting the instruction code to each sensor module one by one and collecting the data from them. Gateway module is an important part to communicate with not only sensor modules but also to the server. This wireless system wasdesigned toreducethe electric consumption powered by 80 WP solar panel and 55Ah battery. This system has been implemented in Pangalengan, Bandung, which has high intensity of rainfall and it can be seen on the website.

Validating visual disturbance types and classes used for forest soil monitoring protocols

Treesearch

D. S. Page-Dumroese; A. M. Abbott; M. P. Curran; M. F. Jurgensen

2012-01-01

We describe several methods for validating visual soil disturbance classes used during forest soil monitoring after specific management operations. Site-specific vegetative, soil, and hydrologic responses to soil disturbance are needed to identify sensitive and resilient soil properties and processes; therefore, validation of ecosystem responses can provide information...

Coupling root architecture and pore network modeling - an attempt towards better understanding root-soil interactions

NASA Astrophysics Data System (ADS)

Leitner, Daniel; Bodner, Gernot; Raoof, Amir

2013-04-01

Understanding root-soil interactions is of high importance for environmental and agricultural management. Root uptake is an essential component in water and solute transport modeling. The amount of groundwater recharge and solute leaching significantly depends on the demand based plant extraction via its root system. Plant uptake however not only responds to the potential demand, but in most situations is limited by supply form the soil. The ability of the plant to access water and solutes in the soil is governed mainly by root distribution. Particularly under conditions of heterogeneous distribution of water and solutes in the soil, it is essential to capture the interaction between soil and roots. Root architecture models allow studying plant uptake from soil by describing growth and branching of root axes in the soil. Currently root architecture models are able to respond dynamically to water and nutrient distribution in the soil by directed growth (tropism), modified branching and enhanced exudation. The porous soil medium as rooting environment in these models is generally described by classical macroscopic water retention and sorption models, average over the pore scale. In our opinion this simplified description of the root growth medium implies several shortcomings for better understanding root-soil interactions: (i) It is well known that roots grow preferentially in preexisting pores, particularly in more rigid/dry soil. Thus the pore network contributes to the architectural form of the root system; (ii) roots themselves can influence the pore network by creating preferential flow paths (biopores) which are an essential element of structural porosity with strong impact on transport processes; (iii) plant uptake depend on both the spatial location of water/solutes in the pore network as well as the spatial distribution of roots. We therefore consider that for advancing our understanding in root-soil interactions, we need not only to extend our root models, but also improve the description of the rooting environment. Until now there have been no attempts to couple root architecture and pore network models. In our work we present a first attempt to join both types of models using the root architecture model of Leitner et al., (2010) and a pore network model presented by Raoof et al. (2010). The two main objectives of coupling both models are: (i) Representing the effect of root induced biopores on flow and transport processes: For this purpose a fixed root architecture created by the root model is superimposed as a secondary root induced pore network to the primary soil network, thus influencing the final pore topology in the network generation. (ii) Representing the influence of pre-existing pores on root branching: Using a given network of (rigid) pores, the root architecture model allocates its root axes into these preexisting pores as preferential growth paths with thereby shape the final root architecture. The main objective of our study is to reveal the potential of using a pore scale description of the plant growth medium for an improved representation of interaction processes at the interface of root and soil. References Raoof, A., Hassanizadeh, S.M. 2010. A New Method for Generating Pore-Network Models. Transp. Porous Med. 81, 391-407. Leitner, D, Klepsch, S., Bodner, G., Schnepf, S. 2010. A dynamic root system growth model based on L-Systems. Tropisms and coupling to nutrient uptake from soil. Plant Soil 332, 177-192.

Collaborative Catchment-Scale Water Quality Management using Integrated Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Zia, Huma; Harris, Nick; Merrett, Geoff

2013-04-01

Electronics and Computer Science, University of Southampton, United Kingdom Summary The challenge of improving water quality (WQ) is a growing global concern [1]. Poor WQ is mainly attributed to poor water management and outdated agricultural activities. We propose that collaborative sensor networks spread across an entire catchment can allow cooperation among individual activities for integrated WQ monitoring and management. We show that sharing information on critical parameters among networks of water bodies and farms can enable identification and quantification of the contaminant sources, enabling better decision making for agricultural practices and thereby reducing contaminants fluxes. Motivation and results Nutrient losses from land to water have accelerated due to agricultural and urban pursuits [2]. In many cases, the application of fertiliser can be reduced by 30-50% without any loss of yield [3]. Thus information about nutrient levels and trends around the farm can improve agricultural practices and thereby reduce water contamination. The use of sensor networks for monitoring WQ in a catchment is in its infancy, but more applications are being tested [4]. However, these are focussed on local requirements and are mostly limited to water bodies. They have yet to explore the use of this technology for catchment-scale monitoring and management decisions, in an autonomous and dynamic manner. For effective and integrated WQ management, we propose a system that utilises local monitoring networks across a catchment, with provision for collaborative information sharing. This system of networks shares information about critical events, such as rain or flooding. Higher-level applications make use of this information to inform decisions about nutrient management, improving the quality of monitoring through the provision of richer datasets of catchment information to local networks. In the full paper, we present example scenarios and analyse how the benefits of collaborative information sharing can have a direct influence on agricultural practice. We apply a nutrient management scheme to a model of an example catchment with several individual networks. The networks are able to correlate catchment events to events within their zone of influence, allowing them to adapt their monitoring and control strategy in light of wider changes across the catchment. Results indicate that this can lead to significant reductions in nutrient losses (up to 50%) and better reutilization of nutrients amongst farms, having a positive impact on catchment scale water quality and fertilizer costs. 1. EC, E.C., Directive 2000/60/EC establishing a framework for Community action in the field of water policy, 2000. 2. Rivers, M., K. Smettem, and P. Davies. Estimating future scenarios for farm-watershed nutrient fluxes using dynamic simulation modelling-Can on-farm BMPs really do the job at the watershed scale? in Proc.29th Int.Conf System Dynamics Society, 2011. 2010. Washington 3. Liu, C., et al., On-farm evaluation of winter wheat yield response to residual soil nitrate-N in North China Plain. Agronomy Journal, 2008. 100(6): p. 1527-1534. 4. Kotamäki, N., et al., Wireless in-situ sensor network for agriculture and water monitoring on a river basin scale in Southern Finland: Evaluation from a data user's perspective. Sensors, 2009. 9(4): p. 2862-2883.

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

USDA-ARS?s Scientific Manuscript database

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

Modeling Energy and Mass Fluxes Over a Vineyard Using the Acasa Model

NASA Astrophysics Data System (ADS)

Marras, S.; Bellucco, V.; Pyles, D.; Falk, M.; Sirca, C.; Duce, P.; Snyder, R. L.; Paw U, K.; Spano, D.

2012-12-01

Energy and mass fluxes are widely monitored over natural ecosystems by the Eddy Covariance (EC) towers within the FLUXNET monitoring network. Only a few studies focused on EC measurements over tree crops and vines, and there is a lack of information useful to parameterize crop and flux models over such systems. The aim of this study was to improve our knowledge about the performance of the land surface model ACASA (Advanced Canopy-Atmosphere-Soil Algorithm) in estimating energy, water, and carbon fluxes over a typical Mediterranean vineyard located in Southern Sardinia (Italy). ACASA estimates turbulent fluxes per 20 canopy layers (10 layers within and 10 above the canopy) and 15 soil layers, using third-order closure equations. CO2 fluxes are estimated using a combination of Ball-Berry and Farquhar equations. The model parameters derived from literature, from a previous work conducted in Tuscany (Italy) and from direct measurements collected in the experimental site of this study. An Eddy Covariance measurement tower was installed to continuously monitor sensible and latent heat, and CO2 fluxes, in conjunction with a net radiometer, and soil heat flux plates from June 2009. A meteorological station was also set up for ancillary measurements. Model performance was evaluated by RMSE and linear regression statistics. Results for the energy balance components and CO2 exchanges will be presented. Detailed analysis was devoted to evaluate the model ability in estimating the vineyard evapotranspiration. This term of the energy balance is, in fact, important for farmers since they are mainly interested in quantify crop water requirements for a better irrigation management.

An experimental investigation to characterise soil macroporosity under different land use and land covers of northeast India

NASA Astrophysics Data System (ADS)

Shougrakpam, Sangeeta; Sarkar, Rupak; Dutta, Subashisa

2010-10-01

Saturated macropore flow is the dominant hydrological process in tropical and subtropical hilly watersheds of northeast India. The process of infiltration into saturated macroporous soils is primarily controlled by size, network, density, connectivity, saturation of surrounding soil matrix, and depthwise distribution of macropores. To understand the effects of local land use, land cover and management practices on soil macroporosity, colour dye infiltration experiments were conducted with ten soil columns (25 × 25 × 50 cm) collected from different watersheds of the region under similar soil and agro-climatic zones. The sampling sites included two undisturbed forested hillslopes, two conventionally cultivated paddy fields, two forest lands abandoned after Jhum cultivation, and two paddy fields, one pineapple plot and one banana plot presently under active cultivation stage of the Jhum cycle. Digital image analyses of the obtained dye patterns showed that the infiltration patterns differed significantly for different sites with varying land use, land cover, and cultivation practices. Undisturbed forest soils showed high degree of soil macroporosity throughout the soil profile, paddy fields revealed sealing of macropores at the topsoil due to hard pan formation, and Jhum cultivated plots showed disconnected subsoil macropores. The important parameters related to soil macropores such as maximum and average size of macropores, number of active macropores, and depthwise distribution of macropores were estimated to characterise the soil macroporosity for the sites. These experimentally derived quantitative data of soil macroporosity can have wide range of applications in the region such as water quality monitoring and groundwater pollution assessment due to preferential leaching of solutes and pesticides, study of soil structural properties and infiltration behaviour of soils, investigation of flash floods in rivers, and hydrological modelling of the watersheds.

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

NASA Astrophysics Data System (ADS)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

3D soil water nowcasting using electromagnetic conductivity imaging and the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Huang, Jingyi; McBratney, Alex B.; Minasny, Budiman; Triantafilis, John

2017-06-01

Mapping and immediate forecasting of soil water content (θ) and its movement can be challenging. Although inversion of apparent electrical conductivity (ECa) measured by electromagnetic induction to calculate depth-specific electrical conductivity (σ) has been used, it is difficult to apply it across a field. In this paper we use a calibration established along a transect, across a 3.94-ha field with varying soil texture, using an ensemble Kalman filter (EnKF) to monitor and nowcast the 3-dimensional θ dynamics on 16 separate days over a period of 38 days. The EnKF combined a physical model fitted with θ measured by soil moisture sensors and an Artificial Neural Network model comprising σ generated by quasi-3d inversions of DUALEM-421S ECa data. Results showed that the distribution of θ was controlled by soil texture, topography, and vegetation. Soil water dried fastest at the beginning after the initial irrigation event and decreased with time and soil depth, which was consistent with classical soil drying theory and experiments. It was also found that the soil dried fastest in the loamy and duplex soils present in the field, which was attributable to deep drainage and preferential flow. It was concluded that the EnKF approach can be used to improve the irrigation efficiency by applying variable irrigation rates across the field. In addition, soil water status can be nowcasted across large spatial extents using this method with weather forecast information, which will provide guidance to farmers for real-time irrigation management.

Potential for the Use of Wireless Sensor Networks for Monitoring of CO2 Leakage Risks

NASA Astrophysics Data System (ADS)

Pawar, R.; Illangasekare, T. H.; Han, Q.; Jayasumana, A.

2015-12-01

Storage of supercritical CO2 in deep saline geologic formation is under study as a means to mitigate potential global climate change from green house gas loading to the atmosphere. Leakage of CO2 from these formations poses risk to the storage permanence goal of 99% of injected CO2 remaining sequestered from the atmosphere,. Leaked CO2 that migrates into overlying groundwater aquifers may cause changes in groundwater quality that pose risks to environmental and human health. For these reasons, technologies for monitoring, measuring and accounting of injected CO2 are necessary for permitting of CO2 sequestration projects under EPA's class VI CO2 injection well regulations. While the probability of leakage related to CO2 injection is thought to be small at characterized and permitted sites, it is still very important to protect the groundwater resources and develop methods that can efficiently and accurately detect CO2 leakage. Methods that have been proposed for leakage detection include remote sensing, soil gas monitoring, geophysical techniques, pressure monitoring, vegetation stress and eddy covariance measurements. We have demonstrated the use of wireless sensor networks (WSN) for monitoring of subsurface contaminant plumes. The adaptability of this technology for leakage monitoring of CO2 through geochemical changes in the shallow subsurface is explored. For this technology to be viable, it is necessary to identify geochemical indicators such as pH or electrical conductivity that have high potential for significant change in groundwater in the event of CO2 leakage. This talk presents a conceptual approach to use WSNs for CO2 leakage monitoring. Based on our past work on the use of WSN for subsurface monitoring, some of the challenges that need to be over come for this technology to be viable for leakage detection will be discussed.

Form and function in hillslope hydrology: in situ imaging and characterization of flow-relevant structures

NASA Astrophysics Data System (ADS)

Jackisch, Conrad; Angermann, Lisa; Allroggen, Niklas; Sprenger, Matthias; Blume, Theresa; Tronicke, Jens; Zehe, Erwin

2017-07-01

The study deals with the identification and characterization of rapid subsurface flow structures through pedo- and geo-physical measurements and irrigation experiments at the point, plot and hillslope scale. Our investigation of flow-relevant structures and hydrological responses refers to the general interplay of form and function, respectively. To obtain a holistic picture of the subsurface, a large set of different laboratory, exploratory and experimental methods was used at the different scales. For exploration these methods included drilled soil core profiles, in situ measurements of infiltration capacity and saturated hydraulic conductivity, and laboratory analyses of soil water retention and saturated hydraulic conductivity. The irrigation experiments at the plot scale were monitored through a combination of dye tracer, salt tracer, soil moisture dynamics, and 3-D time-lapse ground penetrating radar (GPR) methods. At the hillslope scale the subsurface was explored by a 3-D GPR survey. A natural storm event and an irrigation experiment were monitored by a dense network of soil moisture observations and a cascade of 2-D time-lapse GPR trenches. We show that the shift between activated and non-activated state of the flow paths is needed to distinguish structures from overall heterogeneity. Pedo-physical analyses of point-scale samples are the basis for sub-scale structure inference. At the plot and hillslope scale 3-D and 2-D time-lapse GPR applications are successfully employed as non-invasive means to image subsurface response patterns and to identify flow-relevant paths. Tracer recovery and soil water responses from irrigation experiments deliver a consistent estimate of response velocities. The combined observation of form and function under active conditions provides the means to localize and characterize the structures (this study) and the hydrological processes (companion study Angermann et al., 2017, this issue).

Satellite Mapping of Rain-Induced Nitric Oxide Emissions from Soils

NASA Technical Reports Server (NTRS)

Jaegle, L.; Martin, R. V.; Chance, K.; Steinberger, L.; Kurosu, T. P.; Jacob, D. J.; Modi, A. I.; Yoboue, V.; Sigha-Nkamdjou, L.; Galy-Lacaux, C.

2004-01-01

We use space-based observations of NO2 columns from the Global Ozone Monitoring Experiment (GOME) to map the spatial and seasonal variations of NOx emissions over Africa during 2000. The GOME observations show not only enhanced tropospheric NO2 columns from biomass burning during the dry season but also comparable enhancements from soil emissions during the rainy season over the Sahel. These soil emissions occur in strong pulses lasting 1-3 weeks following the onset of rain, and affect 3 million sq km of semiarid sub-Saharan savanna. Surface observations of NO2 from the International Global Atmospheric Chemistry (IGAC)/Deposition of Biochemically Important Trace Species (DEBITS)/Africa (IDAF) network over West Africa provide further evidence for a strong role for microbial soil sources. By combining inverse modeling of GOME NO2 columns with space-based observations of fires, we estimate that soils contribute 3.3+/-1.8 TgN/year, similar to the biomass burning source (3.8+/-2.1 TgN/year), and thus account for 40% of surface NO(x) emissions over Africa. Extrapolating to all the tropics, we estimate a 7.3 TgN/year biogenic soil source, which is a factor of 2 larger compared to model-based inventories but agrees with observation-based inventories. These large soil NO(x) emissions are likely to significantly contribute to the ozone enhancement originating from tropical Africa.

Characterizing dust aerosols in the atmospheric boundary layer over the deserts in Northwest China: monitoring network and field observation

NASA Astrophysics Data System (ADS)

He, Q.; Matimin, A.; Yang, X.

2016-12-01

TheTaklimakan, Gurbantunggut and BadainJaran Deserts with the total area of 43.8×104 km2 in Northwest China are the major dust emission sources in Central Asia. Understanding Central Asian dust emissions and the interaction with the atmospheric boundary layer has an important implication for regional and global climate and environment changes. In order to explore these scientific issues, a monitoring network of 63 sites was established over the vast deserts (Taklimakan Desert, Gurbantunggut Desert and Badain Jaran Desert) in Northwest China for the comprehensive measurements of dust aerosol emission, transport and deposition as well as the atmospheric boundary layer including the meteorological parameters of boundary layer, surface radiation, surface heat fluxes, soil parameters, dust aerosol properties, water vapor profiles, and dust emission. Based on the monitoring network, the field experiments have been conducted to characterize dust aerosols and the atmospheric boundary layer over the deserts. The experiment observation indicated that depth of the convective boundary layer can reach 5000m on summer afternoons. In desert regions, the diurnal mean net radiation was effected significantly by dust weather, and sensible heat was much greater than latent heat accounting about 40-50% in the heat balance of desert. The surface soil and dust size distributions of Northwest China Deserts were obtained through widely collecting samples, results showed that the dominant dust particle size was PM100within 80m height, on average accounting for 60-80% of the samples, with 0.9-2.5% for PM0-2.5, 3.5-7.0% for PM0-10 and 5.0-14.0% for PM0-20. The time dust emission of Taklimakan Desert, Gurbantunggut Desert and Badain Jaran Desert accounted for 0.48%, 7.3%×10-5and 1.9% of the total time within a year, and the threshold friction velocity for dust emission were 0.22-1.06m/s, 0.29-1.5m/s and 0.21-0.59m/s, respectively.

Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Yang, Zhengwei; Sherstha, Ranjay; Crow, Wade; Bolten, John; Mladenova, Iva; Yu, Genong; Di, Liping

2016-01-01

Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.

Soil networks become more connected and take up more carbon as nature restoration progresses.

PubMed

Morriën, Elly; Hannula, S Emilia; Snoek, L Basten; Helmsing, Nico R; Zweers, Hans; de Hollander, Mattias; Soto, Raquel Luján; Bouffaud, Marie-Lara; Buée, Marc; Dimmers, Wim; Duyts, Henk; Geisen, Stefan; Girlanda, Mariangela; Griffiths, Rob I; Jørgensen, Helene-Bracht; Jensen, John; Plassart, Pierre; Redecker, Dirk; Schmelz, Rűdiger M; Schmidt, Olaf; Thomson, Bruce C; Tisserant, Emilie; Uroz, Stephane; Winding, Anne; Bailey, Mark J; Bonkowski, Michael; Faber, Jack H; Martin, Francis; Lemanceau, Philippe; de Boer, Wietse; van Veen, Johannes A; van der Putten, Wim H

2017-02-08

Soil organisms have an important role in aboveground community dynamics and ecosystem functioning in terrestrial ecosystems. However, most studies have considered soil biota as a black box or focussed on specific groups, whereas little is known about entire soil networks. Here we show that during the course of nature restoration on abandoned arable land a compositional shift in soil biota, preceded by tightening of the belowground networks, corresponds with enhanced efficiency of carbon uptake. In mid- and long-term abandoned field soil, carbon uptake by fungi increases without an increase in fungal biomass or shift in bacterial-to-fungal ratio. The implication of our findings is that during nature restoration the efficiency of nutrient cycling and carbon uptake can increase by a shift in fungal composition and/or fungal activity. Therefore, we propose that relationships between soil food web structure and carbon cycling in soils need to be reconsidered.

Soil quality monitoring: Examples of existing protocols

Treesearch

Daniel G. Neary; Carl C. Trettin; Deborah Page-Dumroese

2010-01-01

Many forestry and agricultural agencies and organizations worldwide have developed soil monitoring and quality standards and guidelines to ensure future sustainability of land management. These soil monitoring standards are typically developed in response to international initiatives such as the Montreal Process, the Helsinki Ministerial Conference,or in support of...

Soil quality monitoring: examples of existing protocols

Treesearch

Daniel G. Neary; Carl C. Trettin; Deborah Page-Dumroese

2010-01-01

Many forestry and agricultural agencies and organizations worldwide have developed soil monitoring and quality standards and guidelines to ensure future sustainability of land management. These soil monitoring standards are typically developed in response to international initiatives such as the Montreal Process, the Helsinki Ministerial Conference, or in support of...

Proceedings of the Alaska forest soil productivity workshop.

Treesearch

C.W. Slaughter; T. Gasbarro

1988-01-01

The Alaska Forest Soil Productivity Workshop addressed (1) the role of soil information for forest management in Alaska; (2) assessment, monitoring, and enhancement of soil productivity; and (3) Alaska research projects involved in studies of productivity of forests and soils. This proceedings includes 27 papers in five categories: agency objectives in monitoring and...

EPMOSt: An Energy-Efficient Passive Monitoring System for Wireless Sensor Networks

PubMed Central

Garcia, Fernando P.; Andrade, Rossana M. C.; Oliveira, Carina T.; de Souza, José Neuman

2014-01-01

Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN). In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network. An energy-efficient passive monitoring system is necessary when we need to monitor a WSN in a real scenario because the lifetime of the monitoring network is extended and, consequently, the target network benefits from the monitoring for a longer time. In this work, we have identified, analyzed and compared the main passive monitoring systems proposed for WSN. During our research, we did not identify any passive monitoring system for WSN that aims to reduce the energy consumption of the monitoring network. Therefore, we propose an Energy-efficient Passive MOnitoring SysTem for WSN named EPMOSt that provides monitoring information using a Simple Network Management Protocol (SNMP) agent. Thus, any management tool that supports the SNMP protocol can be integrated with this monitoring system. Experiments with real sensors were performed in several scenarios. The results obtained show the energy efficiency of the proposed monitoring system and the viability of using it to monitor WSN in real scenarios. PMID:24949639

Cosmic Ray Neutron Sensing in Complex Systems

NASA Astrophysics Data System (ADS)

Piussi, L. M.; Tomelleri, E.; Tonon, G.; Bertoldi, G.; Mejia Aguilar, A.; Monsorno, R.; Zebisch, M.

2017-12-01

Soil moisture is a key variable in environmental monitoring and modelling: being located at the soil-atmosphere boundary, it is a driving force for water, energy and carbon fluxes. Nevertheless its importance, soil moisture observations lack of long time-series at high acquisition frequency in spatial meso-scale resolutions: traditional measurements deliver either long time series with high measurement frequency at spatial point scale or large scale and low frequency acquisitions. The Cosmic Ray Neutron Sensing (CRNS) technique fills this gap because it supplies information from a footprint of 240m of diameter and 15 to 83 cm of depth at a temporal resolution varying between 15 minutes and 24 hours. In addition, being a passive sensing technique, it is non-invasive. For these reasons, CRNS is gaining more and more attention from the scientific community. Nevertheless, the application of this technique in complex systems is still an open issue: where different Hydrogen pools are present and where their distributions vary appreciably with space and time, the traditional calibration method shows some limits. In order to obtain a better understanding of the data and to compare them with remote sensing products and spatially distributed traditional measurements (i.e. Wireless Sensors Network), the complexity of the surrounding environment has to be taken into account. In the current work we assessed the effects of spatial-temporal variability of soil moisture within the footprint, in a steep, heterogeneous mountain grassland area. Measurement were performed with a Cosmic Ray Neutron Probe (CRNP) and a mobile Wireless Sensors Network. We performed an in-deep sensitivity analysis of the effects of varying distributions of soil moisture on the calibration of the CRNP and our preliminary results show how the footprint shape varies depending on these dynamics. The results are then compared with remote sensing data (Sentinel 1 and 2). The current work is an assessment of different calibration procedures and their effect on the measurement outcome. We found that the response of the CRNP follows quite well the punctual measurement performed by a TDR installed on the site, but discrepancies could be explained by using the Wireless Sensors Network to perform a spatially weighted calibration and to introduce temporal dynamics.

Impacts of soil sealing on potential agriculture in Egypt using remote sensing and GIS techniques

NASA Astrophysics Data System (ADS)

Mohamed, Elsayed Said; Belal, Abdelaziz; Shalaby, Adel

2015-10-01

This paper highlights the impacts of soil sealing on the agricultural soils in Nile Delta using remote sensing and GIS. The current work focuses on two aims. The first aim is to evaluate soil productivity lost to urban sprawl, which is a significant cause of soil sealing in Nile Delta. The second aim is to evaluate the Land Use and Land Cover Changes (LU LC) from 2001 to 2013 in El-Gharbia governorate as a case study. Three temporal data sets of images from two different sensors: Landsat 7 Enhanced Thematic Mapper (ETM+) with 30 m resolution acquired in 2001 and Landsat 8 acquired in 2013 with 30 m resolution, and Egypt sat acquired in 2010 with 7.8 m resolution, consequently were used. Four different supervised classification techniques (Maximum Likelihood (ML), Minimum Distance, Neural Networks (NN); and Support Vector Machine (SVM) were applied to monitor the changes of LULC in the investigated area. The results showed that the agricultural soils of the investigated area are characterized by high soil productivity depending on its chemical and physical properties. During 2010-2013, soil sealing took place on 1397 ha from the study area which characterized by soil productivity classes ranging between I and II. It is expected that the urban sprawl will be increased to 12.4% by 2020 from the study area, which means that additional 3400 ha of productive soils will be lost from agriculture. However, population growth is the most significant factor effecting urban sprawl in Nile Delta.

Soil ionomic and enzymatic responses and correlations to fertilizations amended with and without organic fertilizer in long-term experiments.

PubMed

Feng, Xumeng; Ling, Ning; Chen, Huan; Zhu, Chen; Duan, Yinghua; Peng, Chang; Yu, Guanghui; Ran, Wei; Shen, Qirong; Guo, Shiwei

2016-04-15

To investigate potential interactions between the soil ionome and enzyme activities affected by fertilization with or without organic fertilizer, soil samples were collected from four long-term experiments over China. Irrespective of variable interactions, fertilization type was the major factor impacting soil ionomic behavior and accounted for 15.14% of the overall impact. Sampling site was the major factor affecting soil enzymatic profile and accounted for 34.25% of the overall impact. The availabilities of Pb, La, Ni, Co, Fe and Al were significantly higher in soil with only chemical fertilizer than the soil with organic amendment. Most of the soil enzyme activities, including α-glucosidase activity, were significantly activated by organic amendment. Network analysis between the soil ionome and the soil enzyme activities was more complex in the organic-amended soils than in the chemical fertilized soils, whereas the network analysis among the soil ions was less complex with organic amendment. Moreover, α-glucosidase was revealed to generally harbor more corrections with the soil ionic availabilities in network. We concluded that some of the soil enzymes activated by organic input can make the soil more vigorous and stable and that the α-glucosidase revealed by this analysis might help stabilize the soil ion availability.

Soil ionomic and enzymatic responses and correlations to fertilizations amended with and without organic fertilizer in long-term experiments

PubMed Central

Feng, Xumeng; Ling, Ning; Chen, Huan; Zhu, Chen; Duan, Yinghua; Peng, Chang; Yu, Guanghui; Ran, Wei; Shen, Qirong; Guo, Shiwei

2016-01-01

To investigate potential interactions between the soil ionome and enzyme activities affected by fertilization with or without organic fertilizer, soil samples were collected from four long-term experiments over China. Irrespective of variable interactions, fertilization type was the major factor impacting soil ionomic behavior and accounted for 15.14% of the overall impact. Sampling site was the major factor affecting soil enzymatic profile and accounted for 34.25% of the overall impact. The availabilities of Pb, La, Ni, Co, Fe and Al were significantly higher in soil with only chemical fertilizer than the soil with organic amendment. Most of the soil enzyme activities, including α-glucosidase activity, were significantly activated by organic amendment. Network analysis between the soil ionome and the soil enzyme activities was more complex in the organic-amended soils than in the chemical fertilized soils, whereas the network analysis among the soil ions was less complex with organic amendment. Moreover, α-glucosidase was revealed to generally harbor more corrections with the soil ionic availabilities in network. We concluded that some of the soil enzymes activated by organic input can make the soil more vigorous and stable and that the α-glucosidase revealed by this analysis might help stabilize the soil ion availability. PMID:27079657

Soil biogeochemical and fungal patterns across a precipitation gradient in the lowland tropical rainforests of French Guiana

NASA Astrophysics Data System (ADS)

Soong, J.; Verbruggen, E.; Janssens, I.

2016-12-01

The Guyafor network contains over 12 pristine tropical rainforest long-term research sites throughout French Guiana, with a focus on vegetation and environmental monitoring at regular intervals. However, biogeochemical and belowground insights are needed to complete the picture of ecosystem functioning in these lowland tropical rainforests, which are critical to Earth's water and energy balance. Improving our biogeochemical understanding of these ecosystems is needed to improve Earth System Models, which poorly represent tropical systems. In July 2015 we sampled soils and litter from 12 of the Guyafor permanent plots in French Guiana spanning a mean annual precipitation gradient of over 2000 mm per year. We measured soil texture, pH, C, N and available P stocks in the top 30 cm, and fungal biodiversity using ITS DNA sequencing and characterized soil organic matter (SOM) C, N and P distribution among physically defined SOM fractions. We also measured litter layer standing stocks and CNP stoichiometry. We found significant stocks of SOM in the top 30 cm of the soil varying by a factor of 4 in the top 30 cm of soil with a negative correlation of arbuscular mycorrhizal fungi and soil C and N with available P. Available P was also a strong predictor of fungal community composition. Furthermore there is evidence for precipitation and mineralogical influences on leaf litter and SOM dynamics highlighting the importance of heterogeneity in tropical soil substrates and sub-climates in better understanding the biogeochemistry of tropical ecosystems.

Biotic and Abiotic Soil Properties Influence Survival of Listeria monocytogenes in Soil

PubMed Central

Locatelli, Aude; Spor, Aymé; Jolivet, Claudy; Piveteau, Pascal; Hartmann, Alain

2013-01-01

Listeria monocytogenes is a food-borne pathogen responsible for the potentially fatal disease listeriosis and terrestrial ecosystems have been hypothesized to be its natural reservoir. Therefore, identifying the key edaphic factors that influence its survival in soil is critical. We measured the survival of L. monocytogenes in a set of 100 soil samples belonging to the French Soil Quality Monitoring Network. This soil collection is meant to be representative of the pedology and land use of the whole French territory. The population of L. monocytogenes in inoculated microcosms was enumerated by plate count after 7, 14 and 84 days of incubation. Analysis of survival profiles showed that L. monocytogenes was able to survive up to 84 days in 71% of the soils tested, in the other soils (29%) only a short-term survival (up to 7 to 14 days) was observed. Using variance partitioning techniques, we showed that about 65% of the short-term survival ratio of L. monocytogenes in soils was explained by the soil chemical properties, amongst which the basic cation saturation ratio seems to be the main driver. On the other hand, while explaining a lower amount of survival ratio variance (11%), soil texture and especially clay content was the main driver of long-term survival of L. monocytogenes in soils. In order to assess the effect of the endogenous soils microbiota on L. monocytogenes survival, sterilized versus non-sterilized soils microcosms were compared in a subset of 9 soils. We found that the endogenous soil microbiota could limit L. monocytogenes survival especially when soil pH was greater than 7, whereas in acidic soils, survival ratios in sterilized and unsterilized microcosms were not statistically different. These results point out the critical role played by both the endogenous microbiota and the soil physic-chemical properties in determining the survival of L. monocytogenes in soils. PMID:24116083

Potentials and Limitations of Wireless Sensor Networks for Environmental

NASA Astrophysics Data System (ADS)

Bumberger, J.; Remmler, P.; Hutschenreuther, T.; Toepfer, H.; Dietrich, P.

2013-12-01

Understanding and dealing with environmental challenges worldwide requires suitable interdisciplinary methods and a level of expertise to be able to implement these solutions, so that the lifestyles of future generations can be secured in the years to come. To characterize environmental systems it is necessary to identify and describe processes with suitable methods. Environmental systems are often characterized by their high heterogeneity, so individual measurements for their complete representation are often not sufficient. The application of wireless sensor networks in terrestrial and aquatic ecosystems offer significant benefits as a better consideration of the local test conditions becomes possible. This can be essential for the monitoring of heterogeneous environmental systems. Significant advantages in the application of wireless sensor networks are their self-organizing behaviour, resulting in a major reduction in installation and operation costs and time. In addition, a point measurement with a sensor is significantly improved by measuring at several points. It is also possible to perform analog and digital signal processing and computation on the basis of the measured data close to the sensor. Hence, a significant reduction of the data to be transmitted can be achieved which leads to a better energy management of sensor nodes. Furthermore, their localization via satellite, the miniaturization of the nodes and long-term energy self-sufficiency are current topics under investigation. In this presentation, the possibilities and limitations of the applicability of wireless sensor networks for long-term environmental monitoring are presented. To underline the importance of this future technology, example concepts are given in the field of near-surface geothermics, groundwater observation, measurement of spatial radiation intensity and air humidity on soils, measurement of matter fluxes, greenhouse gas measurement, and landslide monitoring.

Decision Support system- DSS- for irrigation management in greenhouses: a case study in Campania Region

NASA Astrophysics Data System (ADS)

Monaco, Eugenia; De Mascellis, Roberto; Riccardi, Maria; Basile, Angelo; D'Urso, Guido; Magliulo, Vincenzo; Tedeschi, Anna

2016-04-01

In Mediterranean Countries the proper management of water resources is important for the preservation of actual production systems. The possibility to manage water resources is possible especially in the greenhouses systems. The challenge to manage the soil in greenhouse farm can be a strategy to maintain both current production systems both soil conservation. In Campania region protected crops (greenhouses and tunnels) have a considerable economic importance both for their extension in terms of surface harvested and also for their production in terms of yields. Agricultural production in greenhouse is closely related to the micro-climatic condition but also to the physical and agronomic characteristics of the soil-crop system. The protected crops have an high level of technology compare to the other production systems, but the irrigation management is still carried out according to empirical criteria. The rational management of the production process requires an appropriate control of climatic parameters (temperature, humidity, wind) and agronomical inputs (irrigation, fertilization,). All these factors need to be monitored as well is possible, in order to identify the optimal irrigation schedule. The aim of this work is to implement a Decision Support system -DSS- for irrigation management in greenhouses focused on a smart irrigation control based on observation of the agro-climatic parameters monitored with an advanced wireless sensors network. The study is conducted in a greenhouse farm of 6 ha located in the district of Salerno were seven plots were cropped with rocket. Preliminary a study of soils proprieties was conducted in order to identify spatial variability of the soil in the farm. So undisturbed soil samples were collected to define chemical and physical proprieties; moreover soil hydraulic properties were determined for two soils profiles deemed representation of the farm. Then the wireless sensors, installed at different depth in the soils, determined volumetric water content (VWC) by measuring the dielectric constant of the soil using frequency domain technology (FDR). The data acquired real time were used to determine water balance with a physically based model Hydrus 1D. The results show how the model is able to identify the optimal irrigation schedule as function of soil proprieties and crop needs. Keywords: irrigation, DSS, rocket, water content

Deploying temporary networks for upscaling of sparse network stations

USDA-ARS?s Scientific Manuscript database

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

[Monitoring and SWOT analysis of Ascaris eggs pollution in soil of rural China].

PubMed

Zhu, Hui-hui; Zhou, Chang-hai; Zang, Wei; Zhang, Xue-qiang; Chen, Ying-dan

2014-06-01

To understand the status of Ascaris eggs pollution in soil at national monitoring spots of soil-transmitted nematodiasis, so as to provide the evidence for making countermeasures and evaluating the control effect. Ten households were selected from each of the 22 national monitoring spots annually according to the National Surveillance Program of Soil-Transmitted Nematodiasis (Trial), and the soil samples from vegetable gardens, toilet periphery, courtyards and kitchens were collected and examined by using the modified floatation test with saturated sodium nitrate. Fertilized or unfertilized eggs as well as live or dead fertilized eggs were discriminated and identified. In addition, a SWOT analysis of monitoring of Ascaris eggs pollution in the soil of rural China was carried out. A total of 1 090 households were monitored in 22 monitoring spots from 2006 to 2010. The total detection rate of Ascaris eggs in the soil was 30.73%, and the detection rates of fertilized, unfertilized and live fertilized eggs were 13.21%, 26.42% and 20.28%, respectively. The total detection rates of Ascaris eggs in the vegetable garden, toilet periphery, courtyard and kitchen were 16.51%, 13.49%, 14.22% and 10.73% respectively. The SWOT analysis demonstrated that the monitoring work had both advantages and disadvantages, and was faced with opportunities as well as threats. The pollution status of Ascaris eggs in the soil is still quite severe at some national monitoring spots, and the counter-measures such as implementing hazard-free treatment of stool, improving water supply and sanitation and reforming environment should be taken to protect people from being infected.

Application of neural network to remote sensing of soil moisture using theoretical polarimetric backscattering coefficients

NASA Technical Reports Server (NTRS)

Wang, L.; Shin, R. T.; Kong, J. A.; Yueh, S. H.

1993-01-01

This paper investigates the potential application of neural network to inversion of soil moisture using polarimetric remote sensing data. The neural network used for the inversion of soil parameters is multi-layer perceptron trained with the back-propagation algorithm. The training data include the polarimetric backscattering coefficients obtained from theoretical surface scattering models together with an assumed nominal range of soil parameters which are comprised of the soil permittivity and surface roughness parameters. Soil permittivity is calculated from the soil moisture and the assumed soil texture based on an empirical formula at C-, L-, and P-bands. The rough surface parameters for the soil surface, which is described by the Gaussian random process, are the root-mean-square (rms) height and correlation length. For the rough surface scattering, small perturbation method is used for the L-band frequency, and Kirchhoff approximation is used for the C-band frequency to obtain the corresponding backscattering coefficients. During the training, the backscattering coefficients are the inputs to the neural net and the output from the net are compared with the desired soil parameters to adjust the interconnecting weights. The process is repeated for each input-output data entry and then for the entire training data until convergence is reached. After training, the backscattering coefficients are applied to the trained neural net to retrieve the soil parameters which are compared with the desired soil parameters to verify the effectiveness of this technique. Several cases are examined. First, for simplicity, the correlation length and rms height of the soil surface are fixed while soil moisture is varied. Soil moisture obtained using the neural networks with either L-band or C-band backscattering coefficients for the HH and VV polarizations as inputs is in good agreement with the desired soil moisture. The neural net output matches the desired output for the soil moisture range of 16 to 60 percent for the C-band case. The next case investigated is to vary both soil moisture and rms height while keeping the correlation length fixed. For this case, C-band backscattering coefficients are not sufficient for retrieving two parameters because the Kirchhoff approximation gives the same HH and VV backscattering coefficients. Therefore, the backscattering coefficients at two different frequency bands are necessary to find both the soil moisture and rms height. Finally, the neural nets are also applied to simultaneously invert soil moisture, rms height, and correlation length. Overall, the soil moisture retrieved from the neural network agrees very well with the desired soil moisture. This suggests that the neural network shows potential for retrieval of soil parameters from remote sensing data.

ERT to aid in WSN based early warning system for landslides

NASA Astrophysics Data System (ADS)

T, H.

2017-12-01

Amrita University's landslide monitoring and early warning system using Wireless Sensor Networks (WSN) consists of heterogeneous sensors like rain gauge, moisture sensor, piezometer, geophone, inclinometer, tilt meter etc. The information from the sensors are accurate and limited to that point. In order to monitor a large area, ERT can be used in conjunction with WSN technology. To accomplish the feasibility of ERT in landslide early warning along with WSN technology, we have conducted experiments in Amrita's landslide laboratory setup. The experiment was aimed to simulate landslide, and monitor the changes happening in the soil using moisture sensor and ERT. Simulating moisture values from resistivity measurements to a greater accuracy can help in landslide monitoring for large areas. For accomplishing the same we have adapted two mathematical approaches, 1) Regression analysis between resistivity measurements and actual moisture values from moisture sensor, and 2) Using Waxman Smith model to simulate moisture values from resistivity measurements. The simulated moisture values from Waxman Smith model is compared with the actual moisture values and the Mean Square Error (MSE) is found to be 46.33. Regression curve is drawn for the resistivity vs simulated moisture values from Waxman model, and it is compared with the regression curve of actual model, which is shown in figure-1. From figure-1, it is clear that there the regression curve from actual moisture values and the regression curve from simulated moisture values, follow the similar pattern and there is a small difference between them. Moisture values can be simulated to a greater accuracy using actual regression equation, but the limitation is that, regression curves will differ for different sites and different soils. Regression equation from actual moisture values can be used, if we have conducted experiment in the laboratory for a particular soil sample, otherwise with the knowledge of soil properties, Waxman model can be used to simulate moisture values. The promising results assure that, ERT measurements when used in conjunction with WSN technique, vital paramters triggering landslides like moisture can be simulated for a large area, which will help in providing early warning for large areas.

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.

A soil sampling intercomparison exercise for the ALMERA network.

PubMed

Belli, Maria; de Zorzi, Paolo; Sansone, Umberto; Shakhashiro, Abduhlghani; Gondin da Fonseca, Adelaide; Trinkl, Alexander; Benesch, Thomas

2009-11-01

Soil sampling and analysis for radionuclides after an accidental or routine release is a key factor for the dose calculation to members of the public, and for the establishment of possible countermeasures. The IAEA organized for selected laboratories of the ALMERA (Analytical Laboratories for the Measurement of Environmental Radioactivity) network a Soil Sampling Intercomparison Exercise (IAEA/SIE/01) with the objective of comparing soil sampling procedures used by different laboratories. The ALMERA network is a world-wide network of analytical laboratories located in IAEA member states capable of providing reliable and timely analysis of environmental samples in the event of an accidental or intentional release of radioactivity. Ten ALMERA laboratories were selected to participate in the sampling exercise. The soil sampling intercomparison exercise took place in November 2005 in an agricultural area qualified as a "reference site", aimed at assessing the uncertainties associated with soil sampling in agricultural, semi-natural, urban and contaminated environments and suitable for performing sampling intercomparison. In this paper, the laboratories sampling performance were evaluated.

Soil compaction monitoring of the Pool Timber Sale, Rio Grande National Forest, Colorado, 16 years after logging

Treesearch

John J. Rawinski; Deborah S. Page-Dumroese

2008-01-01

We conducted a soil monitoring project in 1992 after a shelterwood harvest. One year after harvesting, we determined that 21.32 percent of the area in Unit 5 of the Pool Timber Sale was considered to have detrimental soil compaction. In 2007, we conducted another monitoring project on the same stand by the same person to determine the degree of soil compaction recovery...

A multidisciplinary monitoring network at Mayon volcano, Philippines: A collaborative effort between PHIVOLCS and EOS

NASA Astrophysics Data System (ADS)

Schwandner, F. M.; Hidayat, D.; Laguerta, E. P.; Baloloy, A. V.; Valerio, R.; Vaquilar, R.; Arpa, M. C.; Marcial, S. S.; Novianti, M. L.

2012-04-01

Mount Mayon in Albay province (Philippines) is an openly-degassing basaltic-andesitic stratovolcano, located on the northern edge of the northwest-trending OAS graben. Its latest eruptions were in Aug-Sept 2006 and Dec 2009. Mayon's current status is PHIVOLCS' level 1 with low seismicity dominated mostly local and regional tectonic earthquakes and continuous emission of SO2 from its summit crater. A research collaboration between the Earth Observatory of Singapore-NTU and the Philippine Institute of Volcanology and Seismology (PHIVOLCS) was initiated in 2009, aimed at developing a multi-disciplinary monitoring network around Mayon. The network design comprises a network of co-located geophysical, geochemical, hydrological and meteorological sensors, in both radial and circular arrangements. Radially arranged stations are intended to capture and distinguish vertical conduit processes, while the circular station design (including existing PHIVOLCS stations in cooperation with JICA, Japan) is meant to distinguish locations and sector activity of subsurface events. Geophysical instrumentation from EOS currently includes 4 broadband seismographs (in addition to 3 existing broadbands and 3 short period instruments from PHIVOLCS & JICA), and 5 tiltmeters. Four continuous cGPS stations will be installed in 2012, complementing 5 existing PHIVOLCS stations. Stations are also designed to house a multi-sensor package of static subsurface soil CO2 monitoring stations, the first of which was installed in early 2012, and which include subsoil sensors for heat flux, temperature, and moisture, as well as meteorological stations (with sonic anemometers and contact rain gages). These latter sensors are all controlled from one control box per station. Meteorological stations will help us to validate tilt, gas permeability, and also know lahar initiation potential. Since early 2011, separate stations downwind of the two prevailing wind directions from the summit continuously monitor the SO2 plume during daylight (the first Asian NOVAC dual-channel mini-DOAS). One unused agricultural well and one boxed spring were equipped with multi-sensor probes, installed in spring and summer 2011, to detect bulk volumetric strain and changes in chemical composition in high-gain and low-gain mode. All stations are autonomous in terms of their power source (solar), and are designed to withstand typhoons, break-in attempts and direct/indirect lightning strikes. To telemeter the data from these instruments to the local PHIVOLCS observatory at Lignon Hill (Legazpi), we use spread-spectrum radios with our own repeater stations, GSM/GPRS radio modems, and 3G broadband Internet. High rate data including seismic and NOVAC SO2 data are transmitted via spread-spectrum radio, whereas tilt, ground CO2, meteorology, hydrology and soil parameters are transmitted via 3G and SMS. We designed a low-cost datalogger system, which has been operating since Jan 2011, performing continuous data acquisition with sampling rate of 20 minute/sample and transmitted through GSM network, for tilt data. The receiving station is the PHIVOLCS Lignon Hill Observatory (LHO), where an off-grid power system has been installed to ensure continuous operation of the monitoring computers and radios. Local pre-processing by observatory staff and local archiving ensures close to immediate availability of data products in times of crisis. The data are also forwarded via TCP/IP to servers at PHIVOLCS headquarters and at EOS. Network infrastructure and data flows will be completed in 2012.

Forest Soil Disturbance Monitoring Protocol: Volume II: Supplementary methods, statistics, and data collection

Treesearch

Deborah S. Page-Dumroese; Ann M. Abbott; Thomas M. Rice

2009-01-01

Volume I and volume II of the Forest Soil Disturbance Monitoring Protocol (FSDMP) provide information for a wide range of users, including technicians, field crew leaders, private landowners, land managers, forest professionals, and researchers. Volume I: Rapid Assessment includes the basic methods for establishing forest soil monitoring transects and consistently...

Coupling of phenological information and simulated vegetation index time series: Limitations and potentials for the assessment and monitoring of soil erosion risk

USDA-ARS?s Scientific Manuscript database

Monitoring of agricultural used soils at frequent intervals is needed to get a sufficient understanding of soil erosion processes. This is crucial to support decision making and refining soil policies especially in the context of climate change. Along with rainfall erosivity, soil coverage by vegeta...

Baseline map of organic carbon in Australian soil to support national carbon accounting and monitoring under climate change

PubMed Central

Viscarra Rossel, Raphael A; Webster, Richard; Bui, Elisabeth N; Baldock, Jeff A

2014-01-01

We can effectively monitor soil condition—and develop sound policies to offset the emissions of greenhouse gases—only with accurate data from which to define baselines. Currently, estimates of soil organic C for countries or continents are either unavailable or largely uncertain because they are derived from sparse data, with large gaps over many areas of the Earth. Here, we derive spatially explicit estimates, and their uncertainty, of the distribution and stock of organic C in the soil of Australia. We assembled and harmonized data from several sources to produce the most comprehensive set of data on the current stock of organic C in soil of the continent. Using them, we have produced a fine spatial resolution baseline map of organic C at the continental scale. We describe how we made it by combining the bootstrap, a decision tree with piecewise regression on environmental variables and geostatistical modelling of residuals. Values of stock were predicted at the nodes of a 3-arc-sec (approximately 90 m) grid and mapped together with their uncertainties. We then calculated baselines of soil organic C storage over the whole of Australia, its states and territories, and regions that define bioclimatic zones, vegetation classes and land use. The average amount of organic C in Australian topsoil is estimated to be 29.7 t ha−1 with 95% confidence limits of 22.6 and 37.9 t ha−1. The total stock of organic C in the 0–30 cm layer of soil for the continent is 24.97 Gt with 95% confidence limits of 19.04 and 31.83 Gt. This represents approximately 3.5% of the total stock in the upper 30 cm of soil worldwide. Australia occupies 5.2% of the global land area, so the total organic C stock of Australian soil makes an important contribution to the global carbon cycle, and it provides a significant potential for sequestration. As the most reliable approximation of the stock of organic C in Australian soil in 2010, our estimates have important applications. They could support Australia's National Carbon Accounting System, help guide the formulation of policy around carbon offset schemes, improve Australia's carbon balances, serve to direct future sampling for inventory, guide the design of monitoring networks and provide a benchmark against which to assess the impact of changes in land cover, land management and climate on the stock of C in Australia. In this way, these estimates would help us to develop strategies to adapt and mitigate the effects of climate change. PMID:24599716

Baseline map of organic carbon in Australian soil to support national carbon accounting and monitoring under climate change.

PubMed

Viscarra Rossel, Raphael A; Webster, Richard; Bui, Elisabeth N; Baldock, Jeff A

2014-09-01

We can effectively monitor soil condition-and develop sound policies to offset the emissions of greenhouse gases-only with accurate data from which to define baselines. Currently, estimates of soil organic C for countries or continents are either unavailable or largely uncertain because they are derived from sparse data, with large gaps over many areas of the Earth. Here, we derive spatially explicit estimates, and their uncertainty, of the distribution and stock of organic C in the soil of Australia. We assembled and harmonized data from several sources to produce the most comprehensive set of data on the current stock of organic C in soil of the continent. Using them, we have produced a fine spatial resolution baseline map of organic C at the continental scale. We describe how we made it by combining the bootstrap, a decision tree with piecewise regression on environmental variables and geostatistical modelling of residuals. Values of stock were predicted at the nodes of a 3-arc-sec (approximately 90 m) grid and mapped together with their uncertainties. We then calculated baselines of soil organic C storage over the whole of Australia, its states and territories, and regions that define bioclimatic zones, vegetation classes and land use. The average amount of organic C in Australian topsoil is estimated to be 29.7 t ha(-1) with 95% confidence limits of 22.6 and 37.9 t ha(-1) . The total stock of organic C in the 0-30 cm layer of soil for the continent is 24.97 Gt with 95% confidence limits of 19.04 and 31.83 Gt. This represents approximately 3.5% of the total stock in the upper 30 cm of soil worldwide. Australia occupies 5.2% of the global land area, so the total organic C stock of Australian soil makes an important contribution to the global carbon cycle, and it provides a significant potential for sequestration. As the most reliable approximation of the stock of organic C in Australian soil in 2010, our estimates have important applications. They could support Australia's National Carbon Accounting System, help guide the formulation of policy around carbon offset schemes, improve Australia's carbon balances, serve to direct future sampling for inventory, guide the design of monitoring networks and provide a benchmark against which to assess the impact of changes in land cover, land management and climate on the stock of C in Australia. In this way, these estimates would help us to develop strategies to adapt and mitigate the effects of climate change. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Methods of Soil Resampling to Monitor Changes in the Chemical Concentrations of Forest Soils.

PubMed

Lawrence, Gregory B; Fernandez, Ivan J; Hazlett, Paul W; Bailey, Scott W; Ross, Donald S; Villars, Thomas R; Quintana, Angelica; Ouimet, Rock; McHale, Michael R; Johnson, Chris E; Briggs, Russell D; Colter, Robert A; Siemion, Jason; Bartlett, Olivia L; Vargas, Olga; Antidormi, Michael R; Koppers, Mary M

2016-11-25

Recent soils research has shown that important chemical soil characteristics can change in less than a decade, often the result of broad environmental changes. Repeated sampling to monitor these changes in forest soils is a relatively new practice that is not well documented in the literature and has only recently been broadly embraced by the scientific community. The objective of this protocol is therefore to synthesize the latest information on methods of soil resampling in a format that can be used to design and implement a soil monitoring program. Successful monitoring of forest soils requires that a study unit be defined within an area of forested land that can be characterized with replicate sampling locations. A resampling interval of 5 years is recommended, but if monitoring is done to evaluate a specific environmental driver, the rate of change expected in that driver should be taken into consideration. Here, we show that the sampling of the profile can be done by horizon where boundaries can be clearly identified and horizons are sufficiently thick to remove soil without contamination from horizons above or below. Otherwise, sampling can be done by depth interval. Archiving of sample for future reanalysis is a key step in avoiding analytical bias and providing the opportunity for additional analyses as new questions arise.

Methods of Soil Resampling to Monitor Changes in the Chemical Concentrations of Forest Soils

PubMed Central

Lawrence, Gregory B.; Fernandez, Ivan J.; Hazlett, Paul W.; Bailey, Scott W.; Ross, Donald S.; Villars, Thomas R.; Quintana, Angelica; Ouimet, Rock; McHale, Michael R.; Johnson, Chris E.; Briggs, Russell D.; Colter, Robert A.; Siemion, Jason; Bartlett, Olivia L.; Vargas, Olga; Antidormi, Michael R.; Koppers, Mary M.

2016-01-01

Recent soils research has shown that important chemical soil characteristics can change in less than a decade, often the result of broad environmental changes. Repeated sampling to monitor these changes in forest soils is a relatively new practice that is not well documented in the literature and has only recently been broadly embraced by the scientific community. The objective of this protocol is therefore to synthesize the latest information on methods of soil resampling in a format that can be used to design and implement a soil monitoring program. Successful monitoring of forest soils requires that a study unit be defined within an area of forested land that can be characterized with replicate sampling locations. A resampling interval of 5 years is recommended, but if monitoring is done to evaluate a specific environmental driver, the rate of change expected in that driver should be taken into consideration. Here, we show that the sampling of the profile can be done by horizon where boundaries can be clearly identified and horizons are sufficiently thick to remove soil without contamination from horizons above or below. Otherwise, sampling can be done by depth interval. Archiving of sample for future reanalysis is a key step in avoiding analytical bias and providing the opportunity for additional analyses as new questions arise. PMID:27911419

Methods of soil resampling to monitor changes in the chemical concentrations of forest soils

USGS Publications Warehouse

Lawrence, Gregory B.; Fernandez, Ivan J.; Hazlett, Paul W.; Bailey, Scott W.; Ross, Donald S.; Villars, Thomas R.; Quintana, Angelica; Ouimet, Rock; McHale, Michael; Johnson, Chris E.; Briggs, Russell D.; Colter, Robert A.; Siemion, Jason; Bartlett, Olivia L.; Vargas, Olga; Antidormi, Michael; Koppers, Mary Margaret

2016-01-01

Recent soils research has shown that important chemical soil characteristics can change in less than a decade, often the result of broad environmental changes. Repeated sampling to monitor these changes in forest soils is a relatively new practice that is not well documented in the literature and has only recently been broadly embraced by the scientific community. The objective of this protocol is therefore to synthesize the latest information on methods of soil resampling in a format that can be used to design and implement a soil monitoring program. Successful monitoring of forest soils requires that a study unit be defined within an area of forested land that can be characterized with replicate sampling locations. A resampling interval of 5 years is recommended, but if monitoring is done to evaluate a specific environmental driver, the rate of change expected in that driver should be taken into consideration. Here, we show that the sampling of the profile can be done by horizon where boundaries can be clearly identified and horizons are sufficiently thick to remove soil without contamination from horizons above or below. Otherwise, sampling can be done by depth interval. Archiving of sample for future reanalysis is a key step in avoiding analytical bias and providing the opportunity for additional analyses as new questions arise.

Research-informed design, management and maintenance of infrastructure slopes: development of a multi-scalar approach

NASA Astrophysics Data System (ADS)

Glendinning, S.; Helm, P. R.; Rouainia, M.; Stirling, R. A.; Asquith, J. D.; Hughes, P. N.; Toll, D. G.; Clarke, D.; Powrie, W.; Smethurst, J.; Hughes, D.; Harley, R.; Karim, R.; Dixon, N.; Crosby, C.; Chambers, J.; Dijkstra, T.; Gunn, D.; Briggs, K.; Muddle, D.

2015-09-01

The UK's transport infrastructure is one of the most heavily used in the world. The performance of these networks is critically dependent on the performance of cutting and embankment slopes which make up £20B of the £60B asset value of major highway infrastructure alone. The rail network in particular is also one of the oldest in the world: many of these slopes are suffering high incidents of instability (increasing with time). This paper describes the development of a fundamental understanding of earthwork material and system behaviour, through the systematic integration of research across a range of spatial and temporal scales. Spatially these range from microscopic studies of soil fabric, through elemental materials behaviour to whole slope modelling and monitoring and scaling up to transport networks. Temporally, historical and current weather event sequences are being used to understand and model soil deterioration processes, and climate change scenarios to examine their potential effects on slope performance in futures up to and including the 2080s. The outputs of this research are being mapped onto the different spatial and temporal scales of infrastructure slope asset management to inform the design of new slopes through to changing the way in which investment is made into aging assets. The aim ultimately is to help create a more reliable, cost effective, safer and more resilient transport system.

The U.S. Geological Survey and City of Atlanta water-quality and water-quantity monitoring network

USGS Publications Warehouse

Horowitz, Arthur J.; Hughes, W. Brian

2006-01-01

Population growth and urbanization affect the landscape, and the quality and quantity of water in nearby rivers and streams, as well as downstream receiving waters (Ellis, 1999). Typical impacts include: (1) disruption of the hydrologic cycle through increases in the extent of impervious surfaces (e.g., roads, roofs, sidewalks) that increase the velocity and volume of surface-water runoff; (2) increased chemical loads to local and downstream receiving waters from industrial sources, nonpoint-source runoff, leaking sewer systems, and sewer overflows; (3) direct or indirect soil contamination from industrial sources, power-generating facilities, and landfills; and (4) reduction in the quantity and quality of aquatic habitats. The City of Atlanta's monitoring network consists of 21 long-term sites. Eleven of these are 'fully instrumented' to provide real-time data on water temperature, pH, specific conductance, dissolved oxygen, turbidity (intended as a surrogate for suspended sediment concentration), water level (gage height, intended as a surrogate for discharge), and precipitation. Data are transmitted hourly and are available on a public Web site (http://ga.water.usgs.gov/). Two sites only measure water level and rainfall as an aid to stormwater monitoring. The eight remaining sites are used to assess water quality.

Simplifying field-scale assessment of spatiotemporal changes of soil salinity

USDA-ARS?s Scientific Manuscript database

Monitoring soil salinity (ECe) is important to properly plan agronomic and irrigation practices. Salinity can be readily measured through soil sampling directed by geospatial measurements of apparent soil electrical conductivity (ECa). Using data from a long-term (1999-2012) monitoring study at a 32...

Spatial analysis of subsoil compaction on cultivated land by means of penetrometry, electrical resistence tomography and X-ray computed tomography

NASA Astrophysics Data System (ADS)

Zumr, David; Vláčilová, Markéta; Dostál, Tomáš; Jeřábek, Jakub; Sobotková, Martina; Sněhota, Michal

2015-04-01

Soil compaction is a well recognized phenomena in the agricultural land. Various effects can alter the degree of the compaction in the field. The topsoil is regularly loosened due to agrotechnical operations, but the subsoil remains usually compacted. Various studies show increasing bulk density and decreasing saturated hydraulic conductivity in the plough pan, even though some authors argue that it does not have to be always the case due to presence of bio-macropores. Hence the structural properties of the subsoil and the spatial distribution of the compacted layer depth within the cultivated fields are important factors influencing soil water regime, nutrients regime and runoff generation. The aim of the contribution is to present the results of the monitoring of the plough pan depth spatial distribution at the experimental catchment Nucice (Central Bohemia, Czech Republic). The soils are classified as Luvisols and Cambisols with a loamy Ap horizon (0.1 - 0.2 m deep) underlined by a silty and silty-clay B horizon. The content of clay particles in the topsoil is around 8%. The soil has low inner aggregate (soil matrix) hydraulic conductivity, with measured values of approximately 0.1 - 2 cm d-1. The bulk topsoil saturated hydraulic conductivity (Ks) is significantly higher and varies depending on the season. To observe the divide between topsoil and subsoil layers in detail and to be able to compare the soil structure and pore networks of both layers we inspected undisturbed soil samples with X-ray computed tomography. The divide between the conservatively tilled topsoil and the subsoil is clearly observable also on terrain. To identify its exact position we implemented a combination of penetrometry, soil sampling and electrical resistance tomography (ERT). The penetration tests accompanied by soil probing were done in an irregular network across the whole catchment based on the slopes and distance to the stream. Several 2D ERT measurements were done locally on a plot of approximately 10 x 50 m. Dipole-dipole scheme with electrode span of 10 cm was used. The results obtained by different techniques are in a good agreement with observed plough pan position. The contribution was prepared within the project of Czech Science Foundation No. 13-20388P. We thank Johannes Koestel from SLU Uppsala for his great help during CT imaging of the soil samples.

Depletion of Stem Water of Sclerocarya birrea Agroforestry Tree Precedes Start of Rainy Season in West African Sudanian Zone

NASA Astrophysics Data System (ADS)

Ceperley, Natalie; Mande, Theophile; Parlange, Marc B.

2013-04-01

Understanding water use by agroforestry trees in dry-land ecosystems is essential for improving water management. Agroforestry trees are valued and promoted for many of their ecologic and economic benefits but are often criticized as competing for valuable water resources. In order to understand the seasonal patterns of source water used by agroforestry trees, samples from rain, ground, and surface water were collected weekly in the subcatchment of the Singou watershed that is part of the Volta Basin. Soil and vegetation samples were collected from and under a Sclerocarya birrea agroforstry trees located in this catchment in sealed vials, extracted, and analyzed with a Picarro L2130-i CRDS to obtain both δO18 and δDH fractions. Meteorological measurements were taken with a network of wireless, autonomous stations that communicate through the GSM network (Sensorscope) and two complete eddy-covariance energy balance stations, in addition to intense monitoring of sub-canopy solar radiation, throughfall, stemflow, and soil moisture. Examination of the time series of δO18 concentrations confirm that values in soil and xylem water are coupled, both becoming enriched during the dry season and depleted during the rainy season. Xylem water δO18 levels drops to groundwater δO18 levels in early March when trees access groundwater for leafing out, however soil water does not reach this level until soil moisture increases in mid-June. The relationship between the δDH and δO18 concentrations of water extracted from soil and tree samples do not fall along the global meteoric water line. In order to explore whether this was a seasonally driven, we grouped samples into an "evaporated" group or a "meteoric" group based on the smaller residual to the respective lines. Although more soil samples were found along the m-line during the rainy season than tree samples or dry season soil samples, there was no significant difference in days since rain for any group This suggests that xylem water is always under stress from evapotranspiration and soil water underwent evaporation soon after a rain event. Visual observation of tree confirms conclusion that trees access deep ground water in March and April, before rain begins and before soil is connected to groundwater. Results from the research are being integrated into a local outreach project to improve use of agroforestry.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Mofettes - Investigation of Natural CO2 Springs - Insights and Methods applied

NASA Astrophysics Data System (ADS)

Lübben, A.; Leven, C.

2014-12-01

The quantification of carbon dioxide concentrations and fluxes leaking from the subsurface into the atmosphere is highly relevant in several research fields such as climate change, CCS, volcanic activity, or earthquake monitoring. Many of the areas with elevated carbon dioxide degassing pose the problem that under the given situation a systematic investigation of the relevant processes is only possible to a limited extent (e.g. in terms of spatial extent, accessibility, hazardous conditions). The upper Neckar valley in Southwest Germany is a region of enhanced natural subsurface CO2 concentrations and mass fluxes of Tertiary volcanic origin. At the beginning of the twentieth century several companies started industrial mining of CO2. The decreasing productivity of the CO2 springs led to the complete shutdown of the industry in 1995 and the existing boreholes were sealed. However, there are evidences that the reservoir, located in the deposits of the Lower Triassic, started to refill during the last 20 years. The CO2 springs replenished and a variety of different phenomena (e.g. mofettes and perished flora and fauna) indicate the active process of large scale CO2 exhalation. This easy-to-access site serves as a perfect example for a natural analog to a leaky CCS site, including abandoned boreholes and a suitable porous rock reservoir in the subsurface. During extensive field campaigns we applied several monitoring techniques like measurements of soil gas concentrations, mass fluxes, electrical resistivity, as well as soil and atmospheric parameters. The aim was to investigate and quantify mass fluxes and the effect of variations in e.g. temperature, soil moisture on the mass flux intensity. Furthermore, we investigated the effect of the vicinity to a mofette on soil parameters like electrical conductivity and soil CO2 concentrations. In times of a changing climate due to greenhouse gases, regions featuring natural CO2 springs demand to be intensively investigated. Our results serve as a contribution to the development of site-specific monitoring networks at CCS sites, as well as a step forward to unravel the share of natural CO2 springs in the global carbon cycle.

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

PubMed

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

2017-11-01

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

Effect of Piriformospora indica inoculation on root development and distribution of maize (Zea mays L.) in the presence of petroleum contaminated soil

NASA Astrophysics Data System (ADS)

Zamani, Javad; Hajabbasi, Mohammad Ali; Alaie, Ebrahim

2014-05-01

The root systems of most terrestrial plants are confronted to various abiotic and biotic stresses. One of these abiotic stresses is contamination of soil with petroleum hydrocarbon, which the efficiency of phytoremediation of petroleum hydrocarbons in soils is dependent on the ability of plant roots to development into the contaminated soils. Piriformospora indica represents a recently discovered fungus that transfers considerable beneficial impact to its host plants. A rhizotron experiment was conducted to study the effects of P. Indica inoculation on root distribution and root and shoot development of maize (Zea mays L.) in the presence of three patterns of petroleum contamination in the soil (subsurface contamination, continuous contamination and without contamination (control)). Root distribution and root and shoot development were monitored over time. The final root and shoot biomass and the final TPH concentration in the rhizosphere were determined. Analysis of digitized images which were prepared of the tracing of the appeared roots along the front rhizotrons showed the depth and total length of root network in the contamination treatments were significantly decreased. Although the degradation of TPH in the rhizosphere of maize was significant, but there were no significant differences between degradation of TPH in the rhizosphere of +P. indica plants in comparison to -P. indica plants.

Characterizing near-surface CO2 conditions before injection - Perspectives from a CCS project in the Illinois Basin, USA

USGS Publications Warehouse

Locke, R.A.; Krapac, I.G.; Lewicki, J.L.; Curtis-Robinson, E.

2011-01-01

The Midwest Geological Sequestration Consortium is conducting a large-scale carbon capture and storage (CCS) project in Decatur, Illinois, USA to demonstrate the ability of a deep saline formation to store one million tonnes of carbon dioxide (CO2) from an ethanol facility. Beginning in early 2011, CO2 will be injected at a rate of 1,000 tonnes/day for three years into the Mount Simon Sandstone at a depth of approximately 2,100 meters. An extensive Monitoring, Verification, and Accounting (MVA) program has been undertaken for the Illinois Basin Decatur Project (IBDP) and is focused on the 0.65 km2 project site. Goals include establishing baseline conditions to evaluate potential impacts from CO2 injection, demonstrating that project activities are protective of human health and the environment, and providing an accurate accounting of stored CO2. MVA efforts are being conducted pre-, during, and post- CO2 injection. Soil and net CO2 flux monitoring has been conducted for more than one year to characterize near-surface CO2 conditions. More than 2,200 soil CO2 flux measurements have been manually collected from a network of 118 soil rings since June 2009. Three ring types have been evaluated to determine which type may be the most effective in detecting potential CO 2 leakage. Bare soil, shallow-depth rings were driven 8 cm into the ground and were prepared to minimize surface vegetation in and near the rings. Bare soil, deep-depth rings were prepared similarly, but were driven 46 cm. Natural-vegetation, shallow-depth rings were driven 8 cm and are most representative of typical vegetation conditions. Bare-soil, shallow-depth rings had the smallest observed mean flux (1.78 ??mol m-2 s-1) versus natural-vegetation, shallow-depth rings (3.38 ??mol m-2 s-1). Current data suggest bare ring types would be more sensitive to small CO2 leak signatures than natural ring types because of higher signal to noise ratios. An eddy covariance (EC) system has been in use since June 2009. Baseline data from EC monitoring is being used to characterize pre-injection conditions, and may then be used to detect changes in net exchange CO2 fluxes (Fc) that could be the result of CO2 leakage into the near-surface environment during or following injection. When injection at IBDP begins, soil and net CO2 monitoring efforts will have established a baseline of near-surface conditions that will be important to help demonstrate the effectiveness of storage activities. ?? 2011 Published by Elsevier Ltd.

Sentinel-1 backscatter sensitivity to vegetation dynamics at the field scale.

NASA Astrophysics Data System (ADS)

Vreugdenhil, Mariette; Eder, Alexander; Bauer-Marschallinger, Bernhard; Cao, Senmao; Naeimi, Vahid; Oismueller, Markus; Strauss, Peter; Wagner, Wolfgang

2017-04-01

Vegetation monitoring is pivotal to improve our understanding of the role vegetation dynamics play in the global carbon-, energy- and hydrological cycle. And with the increasing stress on food supply due to the growing world populating and changing climate, vegetation monitoring is of great importance in agricultural areas. By closely tracking crop conditions, droughts and subsequent crop losses could be mitigated. Sensors operating in the microwave domain are sensitive to several surface characteristics, including soil moisture and vegetation. Hence, spaceborne microwave remote sensing provides the means to monitor vegetation and soil conditions on different scales, ranging from field scale to global scale. However, it also presents a challenge since multiple combinations of soil and vegetation characteristics can lead to a similar measurement. Copernicus Sentinel-1 (S-1) is a series of two satellites, developed by the European Space Agency (ESA) , which carry C-band Synthetic Aperture Radars. The C-SAR sensors provide VV, HH, VH and HV backscatter at a 5 m by 20 m spatial resolution. The temporal revisit time of the two satellites is 3-6 days. With their unique capacity for temporally dense and spatially detailed data, the S-1 satellite series provides for the first time the chance to investigate vegetation dynamics at high temporal and spatial resolution. The aim of this study is to assess the sensitivity of Sentinel-1 backscatter to vegetation dynamics. The study is performed in the Hydrological Open Air Laboratory (HOAL), which is a 66 hectare large catchment located in Petzenkirchen, Austria. In the HOAL several vegetation parameters were measured during the course of the growing season (2016) at the overpass time of S-1a. Vegetation height was obtained ten times for the whole catchment, using georeferenced photos made by a motorized paraglider and a Land Surface Model. In addition, vegetation water content, Leaf Area Index and soil moisture were measured in four different cropfields. An in situ soil moisture network provides continuous soil moisture measurements at 31 locations within the catchment. Different polarizations and ratios thereof were calculated and compared, both spatially and temporally, to the in situ measurements of vegetation height, LAI, vegetation water content and soil moisture. Preliminary results show a clear spatial pattern in cross-polarized backscatter, which is related to different crop types. Time series analysis suggests that a ratio between cross- and co-polarized backscatter is affected by both vegetation water content and vegetation structure. This presentation will provide a comprehensive assessment of Sentinel-1's capability for monitoring of vegetation over croplands, using in situ reference data obtained over a full growing season.

Laboratory evaluation of dual-frequency multisensor capacitance probes to monitor soil water and salinity

USDA-ARS?s Scientific Manuscript database

Real-time information on salinity levels and transport of fertilizers are generally missing from soil profile knowledge bases. A dual-frequency multisensor capacitance probe (MCP) is now commercially available for sandy soils that simultaneously monitor volumetric soil water content (VWC, ') and sa...

Challenges in Bulk Soil Sampling and Analysis for Vapor Intrusion Screening of Soil

EPA Science Inventory

This draft Engineering Issue Paper discusses technical issues with monitoring soil excavations for VOCs and describes options for such monitoring as part of a VI pathway assessment at sites where soil excavation is being considered or used as part of the remedy for VOC-contaminat...

Preferential flows and soil moistures on a Benggang slope: Determined by the water and temperature co-monitoring

NASA Astrophysics Data System (ADS)

Tao, Yu; He, Yangbo; Duan, Xiaoqian; Zou, Ziqiang; Lin, Lirong; Chen, Jiazhou

2017-10-01

Soil preferential flow (PF) has important effects on rainfall infiltration, moisture distribution, and hydrological and ecological process; but it is very difficult to monitor and characterize on a slope. In this paper, soil water and soil temperature at 20, 40, 60, 80 cm depths in six positions were simultaneously monitored at high frequency to confirm the occurrence of PF at a typical Benggang slope underlain granite residual deposits, and to determine the interaction of soil moisture distribution and Benggang erosion. In the presence of PF, the soil temperature was first (half to one hour) governed by the rainwater temperature, then (more than one hour) governed by the upper soil temperature; in the absence of PF (only matrix flow, MF), the soil temperature was initially governed by the upper soil temperature, then by the rainwater temperature. The results confirmed the water replacement phenomenon in MF, thus it can be distinguished from PF by additional temperature monitoring. It indicates that high frequency moisture and temperature monitoring can determine the occurrence of PF and reveal the soil water movement. The distribution of soil water content and PF on the different positions of the slope showed that a higher frequency of PF resulted in a higher variation of average of water content. The frequency of PF at the lower position can be three times as that of the upper position, therefore, the variation coefficient of soil water content increased from 4.67% to 12.68% at the upper position to 8.18%-33.12% at the lower position, where the Benggang erosion (soil collapse) was more possible. The results suggest strong relationships between PF, soil water variation, and collapse activation near the Benggang wall.

Physical soil quality indicators for monitoring British soils

NASA Astrophysics Data System (ADS)

Corstanje, Ron; Mercer, Theresa G.; Rickson, Jane R.; Deeks, Lynda K.; Newell-Price, Paul; Holman, Ian; Kechavarsi, Cedric; Waine, Toby W.

2017-09-01

Soil condition or quality determines its ability to deliver a range of functions that support ecosystem services, human health and wellbeing. The increasing policy imperative to implement successful soil monitoring programmes has resulted in the demand for reliable soil quality indicators (SQIs) for physical, biological and chemical soil properties. The selection of these indicators needs to ensure that they are sensitive and responsive to pressure and change, e.g. they change across space and time in relation to natural perturbations and land management practices. Using a logical sieve approach based on key policy-related soil functions, this research assessed whether physical soil properties can be used to indicate the quality of British soils in terms of their capacity to deliver ecosystem goods and services. The resultant prioritised list of physical SQIs was tested for robustness, spatial and temporal variability, and expected rate of change using statistical analysis and modelling. Seven SQIs were prioritised: soil packing density, soil water retention characteristics, aggregate stability, rate of soil erosion, depth of soil, soil structure (assessed by visual soil evaluation) and soil sealing. These all have direct relevance to current and likely future soil and environmental policy and are appropriate for implementation in soil monitoring programmes.

Use of Cometabolic Air Sparging to Remediate Chloroethene-Contaminated Groundwater Aquifers

DTIC Science & Technology

2001-07-31

sampling event, the temperature, dew point , and relative humidity of the soil gas were analyzed using a Control Company Digital Hygrometer/Thermometer...4.2.1.3 Groundwater and Soil- Gas Multi-Level Monitoring Points .................... 20 4.2.1.4 Groundwater Monitoring Wells...C-1 APPENDIX D: SOIL- GAS MONITORING POINT DATA........................................................D-1 APPENDIX E: HISTORICAL

Evidence supporting the need for a common soil monitoring protocol

Treesearch

Derrick A. Reeves; Mark D. Coleman; Deborah S. Page-Dumroese

2013-01-01

Many public land management agencies monitor forest soils for levels of disturbance related to management activities. Although several soil disturbance monitoring protocols based on visual observation have been developed to assess the amount and types of disturbance caused by forest management, no common method is currently used on National Forest lands in the United...

Determination of the Thermal Properties of Sands as Affected by Water Content, Drainage/Wetting, and Porosity Conditions for Sands With Different Grain Sizes

NASA Astrophysics Data System (ADS)

Smits, K. M.; Sakaki, T.; Limsuwat, A.; Illangasekare, T. H.

2009-05-01

It is widely recognized that liquid water, water vapor and temperature movement in the subsurface near the land/atmosphere interface are strongly coupled, influencing many agricultural, biological and engineering applications such as irrigation practices, the assessment of contaminant transport and the detection of buried landmines. In these systems, a clear understanding of how variations in water content, soil drainage/wetting history, porosity conditions and grain size affect the soil's thermal behavior is needed, however, the consideration of all factors is rare as very few experimental data showing the effects of these variations are available. In this study, the effect of soil moisture, drainage/wetting history, and porosity on the thermal conductivity of sandy soils with different grain sizes was investigated. For this experimental investigation, several recent sensor based technologies were compiled into a Tempe cell modified to have a network of sampling ports, continuously monitoring water saturation, capillary pressure, temperature, and soil thermal properties. The water table was established at mid elevation of the cell and then lowered slowly. The initially saturated soil sample was subjected to slow drainage, wetting, and secondary drainage cycles. After liquid water drainage ceased, evaporation was induced at the surface to remove soil moisture from the sample to obtain thermal conductivity data below the residual saturation. For the test soils studied, thermal conductivity increased with increasing moisture content, soil density and grain size while thermal conductivity values were similar for soil drying/wetting behavior. Thermal properties measured in this study were then compared with independent estimates made using empirical models from literature. These soils will be used in a proposed set of experiments in intermediate scale test tanks to obtain data to validate methods and modeling tools used for landmine detection.

A decade of monitoring at Swiss Long-Term Forest Ecosystem Research (LWF) sites: can we observe trends in atmospheric acid deposition and in soil solution acidity?

PubMed

Pannatier, Elisabeth Graf; Thimonier, Anne; Schmitt, Maria; Walthert, Lorenz; Waldner, Peter

2011-03-01

Trends in atmospheric acid deposition and in soil solution acidity from 1995 or later until 2007 were investigated at several forest sites throughout Switzerland to assess the effects of air pollution abatements on deposition and the response of the soil solution chemistry. Deposition of the major elements was estimated from throughfall and bulk deposition measurements at nine sites of the Swiss Long-Term Forest Ecosystem Research network (LWF) since 1995 or later. Soil solution was measured at seven plots at four soil depths since 1998 or later. Trends in the molar ratio of base cations to aluminum (BC/Al) in soil solutions and in concentrations and fluxes of inorganic N (NO(3)-N + NH(4)-N), sulfate (SO(4)-S), and base cations (BC) were used to detect changes in soil solution chemistry. Acid deposition significantly decreased at three out of the nine study sites due to a decrease in total N deposition. Total SO(4)-S deposition decreased at the nine sites, but due to the relatively low amount of SO(4)-S load compared to N deposition, it did not contribute to decrease acid deposition significantly. No trend in total BC deposition was detected. In the soil solution, no trend in concentrations and fluxes of BC, SO(4)-S, and inorganic N were found at most soil depths at five out of the seven sites. This suggests that the soil solution reacted very little to the changes in atmospheric deposition. A stronger reduction in base cations compared to aluminum was detected at two sites, which might indicate that acidification of the soil solution was proceeding faster at these sites.

Long-Term Monitoring Research Needs: A DOE Perspective

NASA Astrophysics Data System (ADS)

Moore, B.; Davis, C. B.

2002-05-01

The U.S. Department of Energy's Office of Environmental Management is responsible for dealing with the nation's legacy of Cold War radioactive and hazardous waste and contamination. Major efforts are underway to deal with this legacy; these are expected to last up to decades and cost up to billions of dollars at some sites. At all sites, however, active remediation must eventually cease; if hazards then remain, the site must enter into a long-term stewardship mode. In this talk we discuss aspects of long-term monitoring pertinent to DOE sites, focusing on challenges to be faced, specific goals or targets to be met, and research needs to be addressed in order to enable DOE to meet its long-term stewardship obligations. DOE LTM research needs fall into three major categories: doing what we can do now much more efficiently; doing things we cannot do now; and proving the validity of our monitoring programs. Given the enormity of the DOE obligations, it will be highly desirable to develop much more efficient monitoring paradigms. Doing so will demand developing autonomous, remote monitoring networks of in situ sensors capable of replacing (or at least supplementing to a large extent) conventional groundwater and soil gas sampling and analysis programs. The challenges involved range from basic science (e.g., inventing in situ sensors for TCE that do not demand routine maintenance) to engineering (attaining superior reliability in data reporting in remote networks) to ergonomics (developing decent ways of selecting and presenting the "right" information from the monitoring network) to regulatory affairs (presenting convincing evidence that the more efficient systems actually provide superior monitoring). We explore these challenges in some detail, focusing on the "long" in long-term monitoring as it applies to DOE sites. Monitoring system performance validation and, ultimately, regulator and stakeholder acceptance of site closure and long-term stewardship plans depend critically on the validity and uncertainty in models used to predict contaminant fate and transport. This is an area of active research at the present time. We survey joint research initiatives in this area involving DOE along with USGS, U.S. EPA, U.S. NRC, and U.S. DOA and non-Federal collaborators, and explore their potential for furthering DOE long-term monitoring needs and objectives.

Drought-induced uplift in the western United States as observed by the EarthScope Plate Boundary Observatory GPS network

NASA Astrophysics Data System (ADS)

Borsa, A. A.; Agnew, D. C.; Cayan, D. R.

2014-12-01

The western United States (WUS) has been experiencing severe drought since 2013. The solid earth response to the accompanying loss of surface and near-surface water mass should be a broad region of uplift. We use seasonally-adjusted time series from continuously operating GPS stations in the EarthScope Plate Boundary Observatory and several smaller networks to measure this uplift, which reaches 15 mm in the California Coastal Ranges and Sierra Nevada and has a median value of 4 mm over the entire WUS. The pattern of mass loss due to the drought, which we recover from an inversion of uplift observations, ranges up to 50 cm of water equivalent and is consistent with observed decreases in precipitation and streamflow. We estimate the total deficit to be 240 Gt, equivalent to a uniform 10 cm layer of water over the entire region, or the magnitude of the current annual mass loss from the Greenland Ice Sheet. In the WUS, interannual changes in crustal loading are driven by changes in cool-season precipitation, which cause variations in surface water, snowpack, soil moisture, and groundwater. The results here demonstrate that the existing network of continuous GPS stations can be used to recover loading changes due to both wet and dry climate patterns. This suggests a new role for GPS networks such as that of the Plate Boundary Observatory. The exceptional stability of the GPS monumentation means that this network is also capable of monitoring the long-term effects of regional climate change. Surface displacement observations from GPS have the potential to expand the capabilities of the current hydrological observing network for monitoring current and future hydrological changes, with obvious social and economic benefits.

International Soil Carbon Network (ISCN) Database v3-1

DOE Data Explorer

Nave, Luke [University of Michigan] (ORCID:0000000182588335); Johnson, Kris [USDA-Forest Service; van Ingen, Catharine [Microsoft Research; Agarwal, Deborah [Lawrence Berkeley National Laboratory] (ORCID:0000000150452396); Humphrey, Marty [University of Virginia; Beekwilder, Norman [University of Virginia

2016-01-01

The ISCN is an international scientific community devoted to the advancement of soil carbon research. The ISCN manages an open-access, community-driven soil carbon database. This is version 3-1 of the ISCN Database, released in December 2015. It gathers 38 separate dataset contributions, totalling 67,112 sites with data from 71,198 soil profiles and 431,324 soil layers. For more information about the ISCN, its scientific community and resources, data policies and partner networks visit: http://iscn.fluxdata.org/.

An alternative tensiometer design for deep vadose zone monitoring

NASA Astrophysics Data System (ADS)

Moradi, A. B.; Kandelous, M. M.; Hopmans, J. W.

2015-12-01

The conventional tensiometer is among the most accurate devices for soil water matric potential measurements, as well as for estimations of soil water flux from soil water potential gradients. Uncertainties associated with conventional tensiometers such as caused by ambient temperature effects and the draining of the tensiometer tube, as well as their limitation for deep soil monitoring has prevented their widespread use for vadose zone monitoring, despite their superior accuracy, in general. We introduce an alternative tensiometer design that offers the accuracy of the conventional tensiometer, while minimizing afore-mentioned uncertainties and limitations. The proposed alternative tensiometer largely eliminates temperature-induced diurnal fluctuations and uncertainties associated with the draining of the tensiometer tube, and removes the limitation in installation depth. In addition, the manufacturing costs of this alternative tensiometer design is close to that of the conventional tensiometer, while it is especially suited for monitoring of soil water potential gradients as required for soil water flux measurements.

Transregional Collaborative Research Centre 32: Patterns in Soil-Vegetation-Atmosphere-Systems

NASA Astrophysics Data System (ADS)

Masbou, M.; Simmer, C.; Kollet, S.; Boessenkool, K.; Crewell, S.; Diekkrüger, B.; Huber, K.; Klitzsch, N.; Koyama, C.; Vereecken, H.

2012-04-01

The soil-vegetation-atmosphere system is characterized by non-linear exchanges of mass, momentum and energy with complex patterns, structures and processes that act at different temporal and spatial scales. Under the TR32 framework, the characterisation of these structures and patterns will lead to a deeper qualitative and quantitative understanding of the SVA system, and ultimately to better predictions of the SVA state. Research in TR32 is based on three methodological pillars: Monitoring, Modelling and Data Assimilation. Focusing our research on the Rur Catchment (Germany), patterns are monitored since 2006 continuously using existing and novel geophysical and remote sensing techniques from the local to the catchment scale based on ground penetrating radar methods, induced polarization, radiomagnetotellurics, electrical resistivity tomography, boundary layer scintillometry, lidar techniques, cosmic-ray, microwave radiometry, and precipitation radars with polarization diversity. Modelling approaches involve development of scaled consistent coupled model platform: high resolution numerical weather prediction (NWP; 400m) and hydrological models (few meters). In the second phase (2011-2014), the focus is on the integration of models from the groundwater to the atmosphere for both the m- and km-scale and the extension of the experimental monitoring in respect to vegetation. The coupled modelling platform is based on the atmospheric model COSMO, the land surface model CLM and the hydrological model ParFlow. A scale consistent two-way coupling is performed using the external OASIS coupler. Example work includes the transfer of laboratory methods to the field; the measurements of patterns of soil-carbon, evapotranspiration and respiration measured in the field; catchment-scale modeling of exchange processes and the setup of an atmospheric boundary layer monitoring network. These modern and predominantly non-invasive measurement techniques are exploited in combination with advanced modelling systems by data assimilation to yield improved numerical models for the prediction of water-, energy and CO2-transfer by accounting for the patterns occurring at various scales.

Methods of soil resampling to monitor changes in the chemical concentrations of forest soils

Treesearch

Gregory B. Lawrence; Ivan J. Fernandez; Paul W. Hazlett; Scott W. Bailey; Donald S. Ross; Thomas R. Villars; Angelica Quintana; Rock Ouimet; Michael R. McHale; Chris E. Johnson; Russell D. Briggs; Robert A. Colter; Jason Siemion; Olivia L. Bartlett; Olga Vargas; Michael R. Antidormi; Mary M. Koppers

2016-01-01

Recent soils research has shown that important chemical soil characteristics can change in less than a decade, often the result of broad environmental changes. Repeated sampling to monitor these changes in forest soils is a relatively new practice that is not well documented in the literature and has only recently been broadly embraced by the scientific community. The...

Monitoring Mountain Meteorology without Much Money (Invited)

NASA Astrophysics Data System (ADS)

Lundquist, J. D.

2009-12-01

Mountains are the water towers of the world, storing winter precipitation in the form of snow until summer, when it can be used for agriculture and cities. However, mountain weather is highly variable, and measurements are sparsely distributed. In order adequately sample snow and climate variables in complex terrain, we need as many measurements as possible. This means that instruments must be inexpensive and relatively simple to deploy. Here, we demonstrate how dime-sized temperature sensors developed for the refrigeration industry can be used to monitor air temperature (using evergreen trees as radiation shields) and snow cover duration (using the diurnal cycle in near-surface soil temperature). Together, these measurements can be used to recreate accumulated snow water equivalent over the prior year. We also demonstrate how buckets of water may be placed under networked acoustic snow depth sensors to provide an index of daily evaporation rates at SNOTEL stations. (a) Temperature sensor sealed for deployment in the soil. (b) Launching a temperature sensor into a tree. (c) Pulley system to keep sensor above the snow. (a) Photo of bucket underneath acoustic snow depth sensor. (b) Water depth in the bucket as calculated by the snow depth sensor and by a pressure sensor inside the bucket.

[Prediction of soil nutrients spatial distribution based on neural network model combined with goestatistics].

PubMed

Li, Qi-Quan; Wang, Chang-Quan; Zhang, Wen-Jiang; Yu, Yong; Li, Bing; Yang, Juan; Bai, Gen-Chuan; Cai, Yan

2013-02-01

In this study, a radial basis function neural network model combined with ordinary kriging (RBFNN_OK) was adopted to predict the spatial distribution of soil nutrients (organic matter and total N) in a typical hilly region of Sichuan Basin, Southwest China, and the performance of this method was compared with that of ordinary kriging (OK) and regression kriging (RK). All the three methods produced the similar soil nutrient maps. However, as compared with those obtained by multiple linear regression model, the correlation coefficients between the measured values and the predicted values of soil organic matter and total N obtained by neural network model increased by 12. 3% and 16. 5% , respectively, suggesting that neural network model could more accurately capture the complicated relationships between soil nutrients and quantitative environmental factors. The error analyses of the prediction values of 469 validation points indicated that the mean absolute error (MAE) , mean relative error (MRE), and root mean squared error (RMSE) of RBFNN_OK were 6.9%, 7.4%, and 5. 1% (for soil organic matter), and 4.9%, 6.1% , and 4.6% (for soil total N) smaller than those of OK (P<0.01), and 2.4%, 2.6% , and 1.8% (for soil organic matter), and 2.1%, 2.8%, and 2.2% (for soil total N) smaller than those of RK, respectively (P<0.05).

Advances in Measuring Soil Moisture using Global Navigation Satellite Systems Interferometric Reflectometry (GNSS-IR)

NASA Astrophysics Data System (ADS)

Moore, A. W.; Small, E. E.; Owen, S. E.; Hardman, S. H.; Wong, C.; Freeborn, D. J.; Larson, K. M.

2016-12-01

GNSS Interferometric Reflectometry (GNSS-IR) uses GNSS signals reflected off the land to infer changes in the near-antenna environment and monitor fluctuations in soil moisture, as well as other related hydrologic variables: snow depth/snow water equivalent (SWE), vegetation water content, and water level [Larson and Small, 2013; McCreight, et al., 2014; Larson et al., 2013]. GNSS instruments installed by geoscientists and surveyors to measure land motions can measure soil moisture fluctuations with accuracy (RMSE <0.04 cm3/cm3 [Small et al., 2016]) and latency sufficient for many applications (e.g., weather forecasting, climate studies, satellite validation). The soil moisture products have a unique and complementary footprint intermediate in scale between satellite and standard in situ sensors. Variations in vegetation conditions introduce considerable errors, but algorithms have been developed to address this issue [Small et al., 2016]. A pilot project (PBO H2O) using 100+ GPS sites in the western U.S. (Figure 1) from a single network (the Plate Boundary Observatory) has been operated by the University of Colorado (CU) at http://xenon.colorado.edu/portal since October 2012. JPL and CU are funded by NASA ESTO to refactor the PBO H2O software within an Apache OODT framework for robust operational analysis of soil moisture data and auto-configuration when new stations are added. We will report progress on the new GNSS H2O analysis portal, and plans to expand to global networks and from GPS to other GNSS signals. ReferencesLarson, K. M., & Small, E. E. (2013) Eos, 94(52), 505-512. McCreight, J. L., Small, E. E., & Larson, K. M. (2014). Water Resour. Res., 50(8), 6892-6909. Larson, K. M., Ray, R. D., Nievinski, F. G., & Freymueller, J. T. (2013). IEEE Geosci Remote S, 10(5), 1200-1204. Small, E. E., Larson, K. M., Chew, C. C., Dong, J., & Ochsner, T. E. (2016). IEEE J Sel. Top. Appl. PP(39). Figure 1: (R) Western U.S. GPS-IR soil moisture sites. (L): Products derived from GNSS reflection data for (clockwise from upper left) vegetation water content, SWE, sea level, and volumetric soil moisture.

Review and Future Research Directions about Major Monitoring Method of Soil Erosion

NASA Astrophysics Data System (ADS)

LI, Yue; Bai, Xiaoyong; Tian, Yichao; Luo, Guangjie

2017-05-01

Soil erosion is a highly serious ecological problem that occurs worldwide. Hence,scientific methods for accurate monitoring are needed to obtain soil erosion data. At present,numerous methods on soil erosion monitoring are being used internationally. In this paper, wepresent a systematic classification of these methods based on the date of establishment andtype of approach. This classification comprises five categories: runoff plot method, erosion pinmethod, radionuclide tracer method, model estimation, and 3S technology combined method.The backgrounds of their establishment are briefly introduced, the history of their developmentis reviewed, and the conditions for their application are enumerated. Their respectiveadvantages and disadvantages are compared and analysed, and future prospects regarding theirdevelopment are discussed. We conclude that the methods of soil erosion monitoring in the past 100 years of their development constantly considered the needs of the time. According to the progress of soil erosion monitoring technology throughout its history, we predict that the future trend in this field would move toward the development of quantitative, precise, and composite methods. This report serves as a valuable reference for scientific and technological workers globally, especially those engaged in soil erosion research.

Using a soil moisture and precipitation network for satellite validation

USDA-ARS?s Scientific Manuscript database

A long term in situ network for the study of soil moisture and precipitation was deployed in north central Iowa, in cooperation between USDA and NASA. A total of 20 dual precipitation gages were established across a watershed landscape with an area of approximately 600 km2. In addition, four soil mo...

Validating the BERMS in situ soil moisture network with a large scale temporary network

USDA-ARS?s Scientific Manuscript database

Calibration and validation of soil moisture satellite products requires data records of large spatial and temporal extent, but obtaining this data can be challenging. These challenges can include remote locations, and expense of equipment. One location with a long record of soil moisture data is th...

Using Color, Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown

PubMed Central

Ymeti, Irena; van der Werff, Harald; Shrestha, Dhruba Pikha; Jetten, Victor G.; Lievens, Caroline; van der Meer, Freek

2017-01-01

Remote sensing has shown its potential to assess soil properties and is a fast and non-destructive method for monitoring soil surface changes. In this paper, we monitor soil aggregate breakdown under natural conditions. From November 2014 to February 2015, images and weather data were collected on a daily basis from five soils susceptible to detachment (Silty Loam with various organic matter content, Loam and Sandy Loam). Three techniques that vary in image processing complexity and user interaction were tested for the ability of monitoring aggregate breakdown. Considering that the soil surface roughness causes shadow cast, the blue/red band ratio is utilized to observe the soil aggregate changes. Dealing with images with high spatial resolution, image texture entropy, which reflects the process of soil aggregate breakdown, is used. In addition, the Huang thresholding technique, which allows estimation of the image area occupied by soil aggregate, is performed. Our results show that all three techniques indicate soil aggregate breakdown over time. The shadow ratio shows a gradual change over time with no details related to weather conditions. Both the entropy and the Huang thresholding technique show variations of soil aggregate breakdown responding to weather conditions. Using data obtained with a regular camera, we found that freezing–thawing cycles are the cause of soil aggregate breakdown. PMID:28556803

Determining the frequency, depth and velocity of preferential flow by high frequency soil moisture monitoring

NASA Astrophysics Data System (ADS)

Hardie, Marcus; Lisson, Shaun; Doyle, Richard; Cotching, William

2013-01-01

Preferential flow in agricultural soils has been demonstrated to result in agrochemical mobilisation to shallow ground water. Land managers and environmental regulators need simple cost effective techniques for identifying soil - land use combinations in which preferential flow occurs. Existing techniques for identifying preferential flow have a range of limitations including; often being destructive, non in situ, small sampling volumes, or are subject to artificial boundary conditions. This study demonstrated that high frequency soil moisture monitoring using a multi-sensory capacitance probe mounted within a vertically rammed access tube, was able to determine the occurrence, depth, and wetting front velocity of preferential flow events following rainfall. Occurrence of preferential flow was not related to either rainfall intensity or rainfall amount, rather preferential flow occurred when antecedent soil moisture content was below 226 mm soil moisture storage (0-70 cm). Results indicate that high temporal frequency soil moisture monitoring may be used to identify soil type - land use combinations in which the presence of preferential flow increases the risk of shallow groundwater contamination by rapid transport of agrochemicals through the soil profile. However use of high frequency based soil moisture monitoring to determine agrochemical mobilisation risk may be limited by, inability to determine the volume of preferential flow, difficulty observing macropore flow at high antecedent soil moisture content, and creation of artificial voids during installation of access tubes in stony soils.

Using Color, Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown.

PubMed

Ymeti, Irena; van der Werff, Harald; Shrestha, Dhruba Pikha; Jetten, Victor G; Lievens, Caroline; van der Meer, Freek

2017-05-30

Remote sensing has shown its potential to assess soil properties and is a fast and non-destructive method for monitoring soil surface changes. In this paper, we monitor soil aggregate breakdown under natural conditions. From November 2014 to February 2015, images and weather data were collected on a daily basis from five soils susceptible to detachment (Silty Loam with various organic matter content, Loam and Sandy Loam). Three techniques that vary in image processing complexity and user interaction were tested for the ability of monitoring aggregate breakdown. Considering that the soil surface roughness causes shadow cast, the blue/red band ratio is utilized to observe the soil aggregate changes. Dealing with images with high spatial resolution, image texture entropy, which reflects the process of soil aggregate breakdown, is used. In addition, the Huang thresholding technique, which allows estimation of the image area occupied by soil aggregate, is performed. Our results show that all three techniques indicate soil aggregate breakdown over time. The shadow ratio shows a gradual change over time with no details related to weather conditions. Both the entropy and the Huang thresholding technique show variations of soil aggregate breakdown responding to weather conditions. Using data obtained with a regular camera, we found that freezing-thawing cycles are the cause of soil aggregate breakdown.

Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery

USGS Publications Warehouse

Gillan, Jeffrey K.; Karl, Jason W.; Barger, Nichole N.; Elaksher, Ahmed; Duniway, Michael C.

2016-01-01

Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to quantitatively monitor surface change over time relative to management activities.

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

PubMed

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

2016-03-01

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

Planting increases the abundance and structure complexity of soil core functional genes relevant to carbon and nitrogen cycling

PubMed Central

Wang, Feng; Liang, Yuting; Jiang, Yuji; Yang, Yunfeng; Xue, Kai; Xiong, Jinbo; Zhou, Jizhong; Sun, Bo

2015-01-01

Plants have an important impact on soil microbial communities and their functions. However, how plants determine the microbial composition and network interactions is still poorly understood. During a four-year field experiment, we investigated the functional gene composition of three types of soils (Phaeozem, Cambisols and Acrisol) under maize planting and bare fallow regimes located in cold temperate, warm temperate and subtropical regions, respectively. The core genes were identified using high-throughput functional gene microarray (GeoChip 3.0), and functional molecular ecological networks (fMENs) were subsequently developed with the random matrix theory (RMT)-based conceptual framework. Our results demonstrated that planting significantly (P < 0.05) increased the gene alpha-diversity in terms of richness and Shannon – Simpson’s indexes for all three types of soils and 83.5% of microbial alpha-diversity can be explained by the plant factor. Moreover, planting had significant impacts on the microbial community structure and the network interactions of the microbial communities. The calculated network complexity was higher under maize planting than under bare fallow regimes. The increase of the functional genes led to an increase in both soil respiration and nitrification potential with maize planting, indicating that changes in the soil microbial communities and network interactions influenced ecological functioning. PMID:26396042

Methodological approach for evaluating the response of soil hydrological behavior to irrigation with treated municipal wastewater

NASA Astrophysics Data System (ADS)

Coppola, A.; Santini, A.; Botti, P.; Vacca, S.; Comegna, V.; Severino, G.

2004-06-01

This paper aims mainly to provide experimental evidence of the consequences of urban wastewater reuse in irrigation practices on the hydrological behavior of soils. The effects on both the hydraulic and dispersive properties of representative soils in southern Sardinia are illustrated. Ten undisturbed soil monoliths, 120 cm in height and 40 cm in diameter, were collected from plots previously selected through a soil survey. Soil hydraulic and solute transport properties were determined before and after application of wastewater using transient water infiltration and steady state-solute transport column experiments. Detailed spatial-temporal information on the propagation of water and solute through the soil profiles were obtained by monitoring soil water contents, θ, pressure heads, h, and solute concentrations, C, measured by a network of time domain reflectometry probes, tensiometers and solution samplers horizontally inserted in each column at different depths. A disturbed layer at the soil surface, which expands in depth with time, was observed, characterized by reduced soil porosity, translation of pore size distribution towards narrower pores and consequent decrease in water retention, hydraulic conductivity and hydrodynamic dispersion. It is shown that these changes occurring in the disturbed soil layer, although local by nature, affect the hydrological behavior of the whole soil profile. Due to the disturbed layer formation, the soil beneath never saturates. Such behavior has important consequences on the solute transport in soils, as unsaturated conditions mean higher residence times of solutes, even of those normally characterized by considerable mobility (e.g. boron), which may accumulate along the profile. The results mainly provide experimental evidence that knowledge of the chemical and microbiological composition of the water is not sufficient to evaluate its suitability for irrigation. Other factors, mainly soil physical and hydrological characteristics, should be considered in order to define appropriate guidelines for wastewater management.

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.

Introduction of Drought Monitoring and Forecasting System based on Real-time Water Information Using ICT

NASA Astrophysics Data System (ADS)

Lee, Y., II; Kim, H. S.; Chun, G.

2016-12-01

There were severe damages such as restriction on water supply caused by continuous drought from 2014 to 2015 in South Korea. Through this drought event, government of South Korea decided to establish National Drought Information Analysis Center in K-water(Korea Water Resources Corporation) and introduce a national drought monitoring and early warning system to mitigate those damages. Drought index such as SPI(Standard Precipitation Index), PDSI(Palmer Drought Severity Index) and SMI(Soil Moisture Index) etc. have been developed and are widely used to provide drought information in many countries. However, drought indexes are not appropriate for drought monitoring and early warning in civilized countries with high population density such as South Korea because it could not consider complicated water supply network. For the national drought monitoring and forecasting of South Korea, `Drought Information Analysis System' (D.I.A.S) which is based on the real time data(storage, flowrate, waterlevel etc.) was developed. Based on its advanced methodology, `DIAS' is changing the paradigm of drought monitoring and early warning systems. Because `D.I.A.S' contains the information of water supply network from water sources to the people across the nation and provides drought information considering the real-time hydrological conditions of each and every water source. For instance, in case the water level of a specific dam declines to predetermined level of caution, `D.I.A.S' will notify people who uses the dam as a source of residential or industrial water. It is expected to provide credible drought monitoring and forecasting information with a strong relationship between drought information and the feelings of people rely on water users by `D.I.A.S'.

Observational needs for estimating Alaskan soil carbon stocks under current and future climate

DOE PAGES

Vitharana, U. W. A.; Mishra, U.; Jastrow, J. D.; ...

2017-01-24

Representing land surface spatial heterogeneity when designing observation networks is a critical scientific challenge. Here we present a geospatial approach that utilizes the multivariate spatial heterogeneity of soil-forming factors—namely, climate, topography, land cover types, and surficial geology—to identify observation sites to improve soil organic carbon (SOC) stock estimates across the State of Alaska, USA. Standard deviations in existing SOC samples indicated that 657, 870, and 906 randomly distributed pedons would be required to quantify the average SOC stocks for 0–1 m, 0–2 m, and whole-profile depths, respectively, at a confidence interval of 5 kg C m -2. Using the spatialmore » correlation range of existing SOC samples, we identified that 309, 446, and 484 new observation sites are needed to estimate current SOC stocks to 1 m, 2 m, and whole-profile depths, respectively. We also investigated whether the identified sites might change under future climate by using eight decadal (2020–2099) projections of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change. These analyses determined that 12 to 41 additional sites (906 + 12 to 41; depending upon the emission scenarios) would be needed to capture the impact of future climate on Alaskan whole-profile SOC stocks by 2100. The identified observation sites represent spatially distributed locations across Alaska that captures the multivariate heterogeneity of soil-forming factors under current and future climatic conditions. This information is needed for designing monitoring networks and benchmarking of Earth system model results.« less

Observational needs for estimating Alaskan soil carbon stocks under current and future climate

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

Vitharana, U. W. A.; Mishra, U.; Jastrow, J. D.

Representing land surface spatial heterogeneity when designing observation networks is a critical scientific challenge. Here we present a geospatial approach that utilizes the multivariate spatial heterogeneity of soil-forming factors—namely, climate, topography, land cover types, and surficial geology—to identify observation sites to improve soil organic carbon (SOC) stock estimates across the State of Alaska, USA. Standard deviations in existing SOC samples indicated that 657, 870, and 906 randomly distributed pedons would be required to quantify the average SOC stocks for 0–1 m, 0–2 m, and whole-profile depths, respectively, at a confidence interval of 5 kg C m -2. Using the spatialmore » correlation range of existing SOC samples, we identified that 309, 446, and 484 new observation sites are needed to estimate current SOC stocks to 1 m, 2 m, and whole-profile depths, respectively. We also investigated whether the identified sites might change under future climate by using eight decadal (2020–2099) projections of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change. These analyses determined that 12 to 41 additional sites (906 + 12 to 41; depending upon the emission scenarios) would be needed to capture the impact of future climate on Alaskan whole-profile SOC stocks by 2100. The identified observation sites represent spatially distributed locations across Alaska that captures the multivariate heterogeneity of soil-forming factors under current and future climatic conditions. This information is needed for designing monitoring networks and benchmarking of Earth system model results.« less

Technical-Environmental Permafrost Observatories (TEPO) of northern West Siberia

NASA Astrophysics Data System (ADS)

Kurchatova, A. N.; Griva, G. I.; Osokin, A. B.; Smolov, G. K.

2005-12-01

During the last decade one of the most developed topics in environmental studies was the effect of global climate change. This has been shown to be especially pronounced in northern regions, having an important influence on the subsequent transformation of frozen soil distribution and potential permafrost degradation. In West Siberia such studies are especially important with the prospect of plans for development of oil-gas fields (Yamal, Gydan and Kara Sea shelf). Presently the enterprises independently determine the necessary research for ecological control of the territory. Therefore, the Tyumen State Oil and Gas University (TSOGU) together with one of the leading gas enterprises "Nadymgasprom" started to create an observational network along the meridian transect of northern West Siberia (Yamal-Nenets administrative district). Observational network consists from a number of monitoring sites - Technical-Environmental permafrost Observatories (TEPO). The research complex includes temperature observations in boreholes (depths of 30) equipped with automatic systems for registration and data collection; seasonal field investigations on spatial distribution and temporal variability of the snow cover and vegetation and soil distribution. TSOGU and "Nadymgasprom" plan for the realization of long-term monitoring to obtain representative results on permafrost-climate interaction. At present there are three monitoring observatories located in the main landscape types and gas fields in use since 1972 (Medvezhye), 1992 (Yubileynoe) and in development (Harasavey). The next contribution to International Polar Year (2007-2008) will be renewal of one of the former monitoring sites (established in 1972) with a long-term period of observation and creation of a new site at the Yamal peninsula (Arctic tundra zone). At the last site the installation of an automatic Climate-Soil Station is being planned in the framework of the INTAS Infrastructure Action project with cooperation of the Alfred Wegener Institute for Polar and Marine Research and the University of Hamburg, Germany. One of the responsibilities of TEPO is to provide assistance to students taking part in scientific research (undergraduate and post-graduate practical work and organization of summer schools and seminars). In 2005 a joint summer student field excursion with the Moscow State University Department of Cryolithology and Glaciology took place at TEPO headquarters. The teaching courses consist of the following main topics: 1. Environment and Permafrost of northern West Siberia; 2. Paleocryogenic Formation of Alluvial Terraces; 3. Hydrology and Hydrogeological Conditions of the Territory; 4. Geotechnical Monitoring of Gas Fields; 5. Geotechnical Dangers in the Cryolithozone. The workshop "Stability of Pipelines in the Cryolithozone" held in Nadym at August, 29-31 with participation of "Nadymgasprom", TSOGU and Hokkaido University, Graduate School of Engineering (Japan) included a field excursion. TEPO is expected to be the basis for scientific and educational exchange with national and foreign universities and research institutes and part of the global international monitoring in the northern regions.

Evaluating new SMAP soil moisture for drought monitoring in the rangelands of the US High Plains

USGS Publications Warehouse

Velpuri, Naga Manohar; Senay, Gabriel B.; Morisette, Jeffrey T.

2016-01-01

Level 3 soil moisture datasets from the recently launched Soil Moisture Active Passive (SMAP) satellite are evaluated for drought monitoring in rangelands.Validation of SMAP soil moisture (SSM) with in situ and modeled estimates showed high level of agreement.SSM showed the highest correlation with surface soil moisture (0-5 cm) and a strong correlation to depths up to 20 cm.SSM showed a reliable and expected response of capturing seasonal dynamics in relation to precipitation, land surface temperature, and evapotranspiration.Further evaluation using multi-year SMAP datasets is necessary to quantify the full benefits and limitations for drought monitoring in rangelands.

Prediction of Suspended Sediment in Rivers Using Artificial Neural Networks: Implications for Development of Sediment Budgets

NASA Astrophysics Data System (ADS)

Hamshaw, S. D.; Underwood, K.; Rizzo, D.; Wemple, B. C.; Dewoolkar, M.

2013-12-01

Over 1,000 river miles in Vermont are either impaired or stressed by excessive sedimentation. The higher streamflows and incised river channels have resulted in increased bed and bank erosion. As the climate in Vermont is expected to feature greater and more frequent precipitation events and winter rainfall, the potential for increased sediment loading from erosion processes in the watershed and along the channel are high and a major concern for water resource managers. Typical sediment monitoring comprises periodic sampling during storm events and is often limited to gauged streams with flow data. Continuous turbidity monitoring enhances our understanding of river dynamics by offering high-resolution, temporal measurements to better quantify the total sediment loading occurring during and between storm events. Artificial neural networks, that mimic learning patterns of the human brain, have been effective at predicting flow in small, ungauged rivers using local climate data. This study advances this technology by using an ANN algorithm known as a counter-propagation neural network (CPNN) to predict discharge and suspended sediment in small streams. The first distributed network of continuous turbidity sensors (DTS-12) was deployed in Vermont in the Mad River Watershed, located in Central Vermont. The Mad River and five tributaries were selected as a test bed because seven years of periodic turbidity sampling data are available, it represents a range of watershed characteristics, and because the watershed is also being used for hydrologic model development using the Distributed-Hydrology-Soils-Vegetation Model (DHSVM). Comparison with the DHSVM simulations will allow estimation of the most-likely sources of sediment from the entire watershed and individual subwatersheds. In addition, recent field studies have commenced the quantification of erosion occurring from unpaved roads and streambanks in the same watershed. Periodic water quality sampling during storm events enabled turbidity versus TSS relationships to be established. Sub-watersheds with monitored turbidity and stage also have 15-minute precipitation, soil moisture and air and water temperature data being collected. Stage sensors and theoretical rating curves developed using HEC-RAS and calibrated with discharge measurements are used to validate the flow predictions from the CPNN. The real-time turbidity data are used to train and test the suspended sediment predictions from the CPNN network at each site. The turbidity data are also used to train the CPNN on a subset of tributaries and test on the remaining subwatersheds. Reasonable estimates of suspended sediment discharged from the tributaries and the main stem of the Mad River are calculated and compared enabling a more accurate foundation for building a sediment budget. Results of this study will assist managers in prioritizing mitigation projects to reduce impacts of sediment loading.

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

2016-04-01

Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.

On the temporal and spatial variability of near-surface soil moisture for the identification of representative in situ soil moisture monitoring stations

USDA-ARS?s Scientific Manuscript database

The high spatio-temporal variability of soil moisture complicates the validation of remotely sensed soil moisture products using in-situ monitoring stations. Therefore, a standard methodology for selecting the most repre- sentative stations for the purpose of validating satellites and land surface ...

Integrated monitoring and assessment of soil restoration treatments in the Lake Tahoe Basin.

PubMed

Grismer, M E; Schnurrenberger, C; Arst, R; Hogan, M P

2009-03-01

Revegetation and soil restoration efforts, often associated with erosion control measures on disturbed soils, are rarely monitored or otherwise evaluated in terms of improved hydrologic, much less, ecologic function and longer term sustainability. As in many watersheds, sediment is a key parameter of concern in the Tahoe Basin, particularly fine sediments less than about ten microns. Numerous erosion control measures deployed in the Basin during the past several decades have under-performed, or simply failed after a few years and new soil restoration methods of erosion control are under investigation. We outline a comprehensive, integrated field-based evaluation and assessment of the hydrologic function associated with these soil restoration methods with the hypothesis that restoration of sustainable function will result in longer term erosion control benefits than that currently achieved with more commonly used surface treatment methods (e.g. straw/mulch covers and hydroseeding). The monitoring includes cover-point and ocular assessments of plant cover, species type and diversity; soil sampling for nutrient status; rainfall simulation measurement of infiltration and runoff rates; cone penetrometer measurements of soil compaction and thickness of mulch layer depths. Through multi-year hydrologic and vegetation monitoring at ten sites and 120 plots, we illustrate the results obtained from the integrated monitoring program and describe how it might guide future restoration efforts and monitoring assessments.

Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts

NASA Astrophysics Data System (ADS)

Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.

2012-04-01

Soil moisture is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about soil moisture status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's soil moisture ocean salinity (SMOS) mission in November 2009, about 2 years of soil moisture retrievals has been collected. SMOS is believed to be the currently best satellite sensors for soil moisture remote sensing. Therefore, it becomes interesting to examine how the collected SMOS soil moisture data are compared with other satellite-sensed soil moisture retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ soil moisture measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS soil moisture observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ soil moisture measurements from ground networks (such as USDA Soil Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS soil moisture simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS soil moisture data products over other satellite soil moisture data sets will be evaluated. The next step toward operationally assimilating soil moisture and other land observations into GFS will also be discussed.

On the use of L-band microwave and multi-mission EO data for high resolution soil moisture

NASA Astrophysics Data System (ADS)

Bitar, Ahmad Al; Merlin, Olivier; Malbeteau, Yoann; Molero-Rodenas, Beatriz; Zribi, Mehrez; Sekhar, Muddu; Tomer, Sat Kumar; José Escorihuela, Maria; Stefan, Vivien; Suere, Christophe; Mialon, Arnaud; Kerr, Yann

2017-04-01

Sub-kilometric soil moisture maps have been increasingly mentioned as a need in the scientific community for many applications ranging from agronomical and hydrological (Wood et al. 2011). For example, this type of dataset will become essential to support the current evolution of the land surface and hydrologic modelling communities towards high resolution global modelling. But the ability of the different sensors to monitor soil moisture is different. The L-Band microwave EO provides, at a coarse resolution, the most sensitive information to surface soil moisture when compared to C-Band microwave, optical or C-band SAR. On the other hand the optical and radar sensors provide the spatial distribution of associated variables like surface soil moisture,surface temperature or vegetation leaf area index. This paper describes two complementary fusion approaches to obtain such data from optical or SAR in combination to microwave EO, and more precisely L-Band microwave from the SMOS mission. The first approach, called MAPSM, is based on the use of high resolution soil moisture from SAR and microwave. The two types of sensors have all weather capabilities. The approach uses the new concept of water change capacity (Tomer et al. 2015, 2016). It has been applied to the Berambadi watershed in South-India which is characterised by high cloud coverage. The second approach, called Dispatch, is based on the use of optical sensors in a physical disaggregation approach. It is a well-established approach (Merlin et al. 2012, Malbeteau et al. 2015) that has been implemented operationally in the CATDS (Centre Aval de Traitement des Données SMOS) processing centre (Molero et al. 2016). An analysis on the complementarity of the approaches is discussed. The results show the performances of the methods when compared to existing soil moisture monitoring networks in arid, sub-tropical and humid environments. They emphasis on the need for large inter-comparison studied for the qualification of such products on different climatic zones and on the need of an adaptative multisensor approach. The availability of the recent Sentinel-1 2 and 3 missions from ESA provides an exceptional environment to apply such algorithms at larger scales.

Advanced multivariate analysis to assess remediation of hydrocarbons in soils.

PubMed

Lin, Deborah S; Taylor, Peter; Tibbett, Mark

2014-10-01

Accurate monitoring of degradation levels in soils is essential in order to understand and achieve complete degradation of petroleum hydrocarbons in contaminated soils. We aimed to develop the use of multivariate methods for the monitoring of biodegradation of diesel in soils and to determine if diesel contaminated soils could be remediated to a chemical composition similar to that of an uncontaminated soil. An incubation experiment was set up with three contrasting soil types. Each soil was exposed to diesel at varying stages of degradation and then analysed for key hydrocarbons throughout 161 days of incubation. Hydrocarbon distributions were analysed by Principal Coordinate Analysis and similar samples grouped by cluster analysis. Variation and differences between samples were determined using permutational multivariate analysis of variance. It was found that all soils followed trajectories approaching the chemical composition of the unpolluted soil. Some contaminated soils were no longer significantly different to that of uncontaminated soil after 161 days of incubation. The use of cluster analysis allows the assignment of a percentage chemical similarity of a diesel contaminated soil to an uncontaminated soil sample. This will aid in the monitoring of hydrocarbon contaminated sites and the establishment of potential endpoints for successful remediation.

An efficient approach to imaging underground hydraulic networks

NASA Astrophysics Data System (ADS)

Kumar, Mohi

2012-07-01

To better locate natural resources, treat pollution, and monitor underground networks associated with geothermal plants, nuclear waste repositories, and carbon dioxide sequestration sites, scientists need to be able to accurately characterize and image fluid seepage pathways below ground. With these images, scientists can gain knowledge of soil moisture content, the porosity of geologic formations, concentrations and locations of dissolved pollutants, and the locations of oil fields or buried liquid contaminants. Creating images of the unknown hydraulic environments underfoot is a difficult task that has typically relied on broad extrapolations from characteristics and tests of rock units penetrated by sparsely positioned boreholes. Such methods, however, cannot identify small-scale features and are very expensive to reproduce over a broad area. Further, the techniques through which information is extrapolated rely on clunky and mathematically complex statistical approaches requiring large amounts of computational power.

Forest Soil Disturbance Monitoring Protocol: Volume I: Rapid assessment

Treesearch

Deborah S. Page-Dumroese; Ann M. Abbott; Thomas M. Rice

2009-01-01

This volume of the Forest Soil Disturbance Monitoring Protocol (FSDMP) describes how to monitor forest sites before and after ground disturbing management activities for physical attributes that could influence site resilience and long-term sustainability. The attributes describe surface conditions that affect site sustainability and hydrologic function. Monitoring the...

In situ soil moisture and matrix potential - what do we measure?

NASA Astrophysics Data System (ADS)

Jackisch, Conrad; Durner, Wolfgang

2017-04-01

Soil moisture and matric potential are often regarded as state variables that are simple to monitor at the Darcy-scale. At the same time unproven believes about the capabilities and reliabilities of specific sensing methods or sensor systems exist. A consortium of ten institutions conducted a comparison study of currently available sensors for soil moisture and matrix potential at a specially homogenised field site with sandy loam soil, which was kept free of vegetation. In total 57 probes of 15 different systems measuring soil moisture, and 50 probes of 14 different systems measuring matric potential have been installed in a 0.5 meter grid to monitor the moisture state in 0.2 meter depth. The results give rise to a series of substantial questions about the state of the art in hydrological monitoring, the heterogeneity problem and the meaning of soil water retention at the field scale: A) For soil moisture, most sensors recorded highly plausible data. However, they do not agree in absolute values and reaction timing. For matric potential, only tensiometers were able to capture the quick reactions during rainfall events. All indirect sensors reacted comparably slowly and thus introduced a bias with respect to the sensing of soil water state under highly dynamic conditions. B) Under natural field conditions, a better homogeneity than in our setup can hardly be realised. While the homogeneity assumption held for the first weeks, it collapsed after a heavy storm event. The event exceeded the infiltration capacity, initiated the generation of redistribution networks at the surface, which altered the local surface properties on a very small scale. If this is the reality at a 40 m2 plot, what representativity have single point observations referencing the state of whole basins? C) A comparison of in situ and lab-measured retention curves marks systematic differences. Given the general practice of soil water retention parameterisation in almost any hydrological model this poses quite some concern about deriving field parameters from lab measurements. We will present some insights from the comparison study and highlight the conceptual concerns arising from it. Through this we hope to stimulate a discussion towards more critical revision of measurement assumptions and towards the development of alternative techniques to monitor subsurface states. The sensor comparison study consortium is a cooperation of Wolfgang Durner2, Ines Andrä2, Kai Germer2, Katrin Schulz2, Marcus Schiedung2, Jaqueline Haller-Jans2, Jonas Schneider2, Julia Jaquemotte2, Philipp Helmer2, Leander Lotz2, Thomas Graeff3, Andreas Bauer3, Irene Hahn3, Conrad Jackisch1, Martin Sanda4, Monika Kumpan5, Johann Dorner5, Gerrit de Rooij6, Stephan Wessel-Bothe7, Lorenz Kottmann8, and Siegfried Schittenhelm8. The great support by the team and the Thünen Institute Braunschweig is gratefully acknowledged. 1 Karlsruhe Institute of Technology, 2 Technical University of Braunschweig, 3 University of Potsdam, 4 Technical University of Prague, 5 Federal Department for Water Management Petzenkirchen, 6 Helmholtz Centre for Environmental Research Halle, 7 ecoTech GmbH Bonn, 8 Julius Kühn Institute Braunschweig

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Development of web-based GIS services for sustainable soil resource management at farm level

NASA Astrophysics Data System (ADS)

Papadopoulos, Antonis; Kolovos, Chronis; Troyanos, Yerasimos; Doula, Maria

2017-09-01

Modern farms situated in urban or suburban areas, include various and in most cases diverse land covers. Land uses in such farms may serve residential, structured, aesthetic and agricultural purposes, usually delimited inside the boundaries of a single property. The environmental conditions across a farm, especially if it is situated on an irregular terrain, can be highly differentiated. Managing soil resources in a small scale diverse farm environment in a holistic and sustainable way should have spatial and temporal reference and take advantage of cut-edge geospatial technologies. In present study, an 8 hectare farm with various land uses in the southern suburbs of Attica Prefecture, Greece was systematically monitored regarding its soil, water and plant resources. Almost 80% of the farm's area is covered with trees, shrubs and low vegetation planted in a mosaic of parterres. Farm data collected concerned soil and water physicochemical characteristics, plant species, topographical features, irrigation network, valves and infrastructure. All data were imported and developed in a GIS geodatabase. Furthermore, web GIS services and a mobile GIS app were developed in order to monitor, update and synchronize present status and future changes performed in the farm. Through the web services and using the mobile GIS app, the user has access to all data stored in the geodatabase and according to access rights he can view or edit the spatial entities. The user can easily make query to specific features, combine their properties with other overlaying spatial data and reach accurate decisions. The app can be downloaded and implemented in mobile devices like smartphones and tablets for extending its functionality. As proven in this study, web GIS services and mobile GIS apps constitute an attractive suite of methodologies for effective and user friendly management of natural resources at farm level.

Monitoring and evaluation of soil bioengineering interventions for watershed management, disaster mitigation and environmental restoration in Latin America

NASA Astrophysics Data System (ADS)

Petrone, Alessandro; Preti, Federico

2013-04-01

In recent decades the institutions responsible for land management and civil protection have showed a great interest in relation to the use of more environmentally friendly techniques to mitigate the risk of landslides and floods. Soil bioengineering has responded to this need and several research groups are carrying out experimentations using the techniques of this discipline in the countries in the developing world. The Deistaf from University of Florence has concentrated its activities in this area over the past decade promoting the use of the techniques of Soil bioengineering in Latin America through the implementation of training and experimentation programmes. Numerous works have been completed both in riverbanks and on slopes in Nicaragua, Guatemala, Ecuador and Colombia. It was decided to make a census of interventions in Latin America from different institutions that may be related to Soil bioengineering in order to obtain an overview of the state of the art in the specific context taking into account also environmental and socio-economic issues. Taking advantage of its network of contacts, DEISTAF has collected dozens of sheets that describe interventions. These sheets describe, among other fields focused on the environment in which the work has been carried out, the materials and techniques used, and the impact of the intervention. In the sheets we present also the monitoring that has been realized for some of these works in the months of October and November 2012; we include the identification of the current condition and functionality of the intervention and, in the case of the presence of some damages, the formulation of instructions to fix them as well as the economic quantification of the repairs to be carried out.

Silicification of holocene soils in northern Monitor Valley, Nevada

NASA Astrophysics Data System (ADS)

Chadwick, O. A.; Hendricks, D. M.; Nettleton, W. D.

1989-02-01

Chemical, physical, and microscopic data for three soils in the northern Monitor Valley are analyzed. The soils ranked in order of increasing age are: Mule, Rotinom, and Nayped. The procedures and techniques used to obtain and study that data are described. It is observed that: (1) redistribution of carbonate is detectable in all soils; (2) clay illuviation is insignificant in the Mule soil, weak but identifiable in the Rotinom soil, and significant in the Nayped soil; and (3) the maximum sodium adsorption ratio (SAR) and electrical conductivity (EC) for the Mule soil is between 64-89 cm, for the Rotinom soil the values are below 100 cm, and for Nayped the maximum SAR values range from 51-117 cm and maximum EC values are between 117-152 cm. The relationship between volcanic glass weathering and the amount of silica cementation in the soils is studied. It is noted that silicification of Monitor Valley holocene soils is due to there being enough moisture to release silica from volcanic glass, but not enough to leach the weathering products from the profile.

Silicification of holocene soils in northern Monitor Valley, Nevada

NASA Technical Reports Server (NTRS)

Chadwick, O. A.; Hendricks, D. M.; Nettleton, W. D.

1989-01-01

Chemical, physical, and microscopic data for three soils in the northern Monitor Valley are analyzed. The soils ranked in order of increasing age are: Mule, Rotinom, and Nayped. The procedures and techniques used to obtain and study that data are described. It is observed that: (1) redistribution of carbonate is detectable in all soils; (2) clay illuviation is insignificant in the Mule soil, weak but identifiable in the Rotinom soil, and significant in the Nayped soil; and (3) the maximum sodium adsorption ratio (SAR) and electrical conductivity (EC) for the Mule soil is between 64-89 cm, for the Rotinom soil the values are below 100 cm, and for Nayped the maximum SAR values range from 51-117 cm and maximum EC values are between 117-152 cm. The relationship between volcanic glass weathering and the amount of silica cementation in the soils is studied. It is noted that silicification of Monitor Valley holocene soils is due to there being enough moisture to release silica from volcanic glass, but not enough to leach the weathering products from the profile.

Volcanic gas impacts on vegetation at Turrialba Volcano, Costa Rica

NASA Astrophysics Data System (ADS)

Teasdale, R.; Jenkins, M.; Pushnik, J.; Houpis, J. L.; Brown, D. L.

2010-12-01

Turrialba volcano is an active composite stratovolcano that is located approximately 40 km east of San Jose, Costa Rica. Seismic activity and degassing have increased since 2005, and gas compositions reflect further increased activity since 2007 peaking in January 2010 with a phreatic eruption. Gas fumes dispersed by trade winds toward the west, northwest, and southwest flanks of Turrialba volcano have caused significant vegetation kill zones, in areas important to local agriculture, including dairy pastures and potato fields, wildlife and human populations. In addition to extensive vegetative degradation is the potential for soil and water contamination and soil erosion. Summit fumarole temperatures have been measured over 200 degrees C and gas emissions are dominated by SO2; gas and vapor plumes reach up to 2 km (fumaroles and gases are measured regularly by OVSICORI-UNA). A recent network of passive air sampling, monitoring of water temperatures of hydrothermal systems, and soil pH measurements coupled with measurement of the physiological status of surrounding plants using gas exchange and fluorescence measurements to: (1) identify physiological correlations between leaf-level gas exchange and chlorophyll fluorescence measurements of plants under long term stress induced by the volcanic gas emissions, and (2) use measurements in tandem with remotely sensed reflectance-derived fluorescence ratio indices to track natural photo inhibition caused by volcanic gas emissions, for use in monitoring plant stress and photosynthetic function. Results may prove helpful in developing potential land management strategies to maintain the biological health of the area.

Evaluation of radiocaesium wash-off by soil erosion from various land uses using USLE plots.

PubMed

Yoshimura, Kazuya; Onda, Yuichi; Kato, Hiroaki

2015-01-01

Radiocaesium wash-off associated with soil erosion in different land use was monitored using USLE plots in Kawamata, Fukushima Prefecture, Japan after the Fukushima Dai-ichi Nuclear Power Plant accident. Parameters and factors relating to soil erosion and (137)Cs concentration in the eroded soil were evaluated based on the field monitoring and presented. The erosion of fine soil, which is defined as the fraction of soil overflowed along with discharged water from a sediment-trap tank, constituted a large proportion of the discharged radiocaesium. This indicated that the quantitative monitoring of fine soil erosion is greatly important for the accurate evaluation of radiocaesium wash-off. An exponential relationship was found between vegetation cover and the amount of eroded soil. Moreover, the radiocaesium concentrations in the discharged soil were greatly affected by the land use. These results indicate that radiocaesium wash-off related to vegetation cover and land use is crucially important in modelling radiocaesium migration. Copyright © 2014 Elsevier Ltd. All rights reserved.

Estimating Soil Cation Exchange Capacity from Soil Physical and Chemical Properties

NASA Astrophysics Data System (ADS)

Bateni, S. M.; Emamgholizadeh, S.; Shahsavani, D.

2014-12-01

The soil Cation Exchange Capacity (CEC) is an important soil characteristic that has many applications in soil science and environmental studies. For example, CEC influences soil fertility by controlling the exchange of ions in the soil. Measurement of CEC is costly and difficult. Consequently, several studies attempted to obtain CEC from readily measurable soil physical and chemical properties such as soil pH, organic matter, soil texture, bulk density, and particle size distribution. These studies have often used multiple regression or artificial neural network models. Regression-based models cannot capture the intricate relationship between CEC and soil physical and chemical attributes and provide inaccurate CEC estimates. Although neural network models perform better than regression methods, they act like a black-box and cannot generate an explicit expression for retrieval of CEC from soil properties. In a departure with regression and neural network models, this study uses Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS) to estimate CEC from easily measurable soil variables such as clay, pH, and OM. CEC estimates from GEP and MARS are compared with measurements at two field sites in Iran. Results show that GEP and MARS can estimate CEC accurately. Also, the MARS model performs slightly better than GEP. Finally, a sensitivity test indicates that organic matter and pH have respectively the least and the most significant impact on CEC.

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Monitoring network completion. 58.13... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a) The network of NCore multipollutant sites must be physically established no later than January 1, 2011...

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Monitoring network completion. 58.13... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a) The network of NCore multipollutant sites must be physically established no later than January 1, 2011...

The influence of e-waste recycling on the molecular ecological network of soil microbial communities in Pakistan and China.

PubMed

Jiang, Longfei; Cheng, Zhineng; Zhang, Dayi; Song, Mengke; Wang, Yujie; Luo, Chunling; Yin, Hua; Li, Jun; Zhang, Gan

2017-12-01

Primitive electronic waste (e-waste) recycling releases large amounts of organic pollutants and heavy metals into the environment. As crucial moderators of geochemical cycling processes and pollutant remediation, soil microbes may be affected by these contaminants. We collected soil samples heavily contaminated by e-waste recycling in China and Pakistan, and analyzed the indigenous microbial communities. The results of this work revealed that the microbial community composition and diversity, at both whole and core community levels, were affected significantly by polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs) and heavy metals (e.g., Cu, Zn, and Pb). The geographical distance showed limited impacts on microbial communities compared with geochemical factors. The constructed ecological network of soil microbial communities illustrated microbial co-occurrence, competition and antagonism across soils, revealing the response of microbes to soil properties and pollutants. Two of the three main modules constructed with core operational taxonomic units (OTUs) were sensitive to nutrition (total organic carbon and total nitrogen) and pollutants. Five key OTUs assigned to Acidobacteria, Proteobacteria, and Nitrospirae in ecological network were identified. This is the first study to report the effects of e-waste pollutants on soil microbial network, providing a deeper understanding of the ecological influence of crude e-waste recycling activities on soil ecological functions. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Designing a low-cost effective network for monitoring large scale regional seismicity in a soft-soil region (Alsace, France)

NASA Astrophysics Data System (ADS)

Bès de Berc, M.; Doubre, C.; Wodling, H.; Jund, H.; Hernandez, A.; Blumentritt, H.

2015-12-01

The Seismological Observatory of the North-East of France (ObSNEF) is developing its monitoring network within the framework of several projects. Among these project, RESIF (Réseau sismologique et géodésique français) allows the instrumentation of broad-band seismic stations, separated by 50-100 km. With the recent and future development of geothermal industrial projects in the Alsace region, the ObSNEF is responsible for designing, building and operating a dense regional seismic network in order to detect and localize earthquakes with both a completeness magnitude of 1.5 and no clipping for M6.0. The realization of the project has to be done prior to the summer 2016Several complex technical and financial constraints constitute such a projet. First, most of the Alsace Région (150x150 km2), particularly the whole Upper Rhine Graben, is a soft-soil plain where seismic signals are dominated by a high frequency noise level. Second, all the signals have to be transmitted in near real-time. And finally, the total cost of the project must not exceed $450,000.Regarding the noise level in Alsace, in order to make a reduction of 40 dB for frequencies above 1Hz, we program to instrument into 50m deep well with post-hole sensor for 5 stations out of 8 plane new stations. The 3 remaining would be located on bedrock along the Vosges piedmont. In order to be sensitive to low-magnitude regional events, we plan to install a low-noise short-period post-hole velocimeter. In order to avoid saturation for high potentiel local events (M6.0 at 10km), this velocimeter will be coupled with a surface strong-motion sensor. Regarding the connectivity, these stations will have no wired network, which reduces linking costs and delays. We will therefore use solar panels and a 3G/GPRS network. The infrastructure will be minimal and reduced to an outdoor box on a secured parcel of land. In addition to the data-logger, we will use a 12V ruggedized computer, hosting a seed-link server for near real-time transmission and a rsync daemon for delayed-time transmission.We plan to install and validate our first pilot station during the fall of 2015, and have an effective network by the summer of 2016.

Network analysis reveals that bacteria and fungi form modules that correlate independently with soil parameters.

PubMed

de Menezes, Alexandre B; Prendergast-Miller, Miranda T; Richardson, Alan E; Toscas, Peter; Farrell, Mark; Macdonald, Lynne M; Baker, Geoff; Wark, Tim; Thrall, Peter H

2015-08-01

Network and multivariate statistical analyses were performed to determine interactions between bacterial and fungal community terminal restriction length polymorphisms as well as soil properties in paired woodland and pasture sites. Canonical correspondence analysis (CCA) revealed that shifts in woodland community composition correlated with soil dissolved organic carbon, while changes in pasture community composition correlated with moisture, nitrogen and phosphorus. Weighted correlation network analysis detected two distinct microbial modules per land use. Bacterial and fungal ribotypes did not group separately, rather all modules comprised of both bacterial and fungal ribotypes. Woodland modules had a similar fungal : bacterial ribotype ratio, while in the pasture, one module was fungal dominated. There was no correspondence between pasture and woodland modules in their ribotype composition. The modules had different relationships to soil variables, and these contrasts were not detected without the use of network analysis. This study demonstrated that fungi and bacteria, components of the soil microbial communities usually treated as separate functional groups as in a CCA approach, were co-correlated and formed distinct associations in these adjacent habitats. Understanding these distinct modular associations may shed more light on their niche space in the soil environment, and allow a more realistic description of soil microbial ecology and function. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Drivers of inverse DOC-nitrate loss patterns in forest soils and streams

NASA Astrophysics Data System (ADS)

Goodale, C. L.

2013-12-01

Nitrate loss from forested catchments varies greatly across sites and over time, with few reliable correlates. One of the few recurring patterns, however, is the negative nonlinear relationship that occurs regularly between surface water nitrate and dissolved organic carbon (DOC) concentrations: that is, nitrate declines sharply as DOC concentrations increase, and high nitrate levels occur only at low DOC concentrations. Several hypotheses have been proposed to explain this pattern, but its cause has remained speculative. It is likely to be driven by C- or N-limitation of biological processes such as assimilation or denitrification, but the identity of which biological process or the main landscape position of their activity are not known. We examined whether DOC and nitrate are both driven by soil C content, at scales of both soil blocks and across catchments, by measuring soil, soil extract, and surface water chemistry across nine catchments selected from long-term monitoring networks in the Catskill and Adirondack Mountains. We measured soil C and N status and solution nitrate, DOC, bioavailable DOC (bDOC), and isotopic composition (13C-DOC, 15N- and 18O-NO3) to examine whether variation in stocks of soil C partly controls DOC and nitrate loss from forested catchments in New York State. These measurements showed that surface soil C and C:N ratio together determine soil production of DOC and nitrate, reflecting assimilative demand for N by heterotrophic microbes. Yet, they also show that these processes do not produce the inverse DOC-NO3 curve observed at the catchment scale. Rather, catchment-scale DOC-nitrate patterns are more likely to be governed by the balance between excess nitrate production and its bDOC-mediated loss to denitrification.

Closing the Knowledge Gap: Effects of Land Use Conversion on Belowground Carbon near the 100th Meridian

NASA Astrophysics Data System (ADS)

Waldron, S. E.; Phillips, R. L.; Dell, R.; Suddick, E. C.

2012-12-01

Native prairie of the northern Great Plains near the 100th meridian is currently under land use conversion pressure due to high commodity prices. From 2002 to 2007, approximately 303,515 hectares of prairie were converted to crop production in the Prairie Pothole Region (PPR) from Montana to the Dakotas. The spatiotemporal effects of land-use conversion on soil organic matter are still unclear for the PPR. Effects will vary with management, soil properties and time, making regional experiments and simulation modeling necessary. Grassland conservationists are interested in soil carbon data and soil carbon simulation models to inform potential voluntary carbon credit programs. These programs require quantification of changes in soil carbon associated with land-use conversion and management. We addressed this issue by 1) designing a regional-scale experiment, 2) collecting and analyzing soil data, and 3) interviewing producers about land management practices, as required for regional, process-based biogeochemical models. We selected farms at random within a 29,000 km2 area of interest and measured soil properties at multiple depths for native prairie and adjacent annual crop fields. The cores were processed at six different depths (between 0 and 100 cm) for bulk density, pH, texture, total carbon, inorganic carbon, and total nitrogen. We found that the largest difference in soil organic carbon occurred at the 0-10 cm depth, but the magnitude of the effect of land use varied with soil properties and land management. Results from this project, coupled with regional model simulations (Denitrification-Decomposition, DNDC) represent the baseline data needed for future voluntary carbon credit programs and long-term carbon monitoring networks. Enrollment in such programs could help ranchers and farmers realize a new income stream from maintaining their native prairie and the carbon stored beneath it.

Hydrologic modeling for monitoring water availability in Eastern and Southern Africa

NASA Astrophysics Data System (ADS)

McNally, A.; Harrison, L.; Shukla, S.; Pricope, N. G.; Peters-Lidard, C. D.

2017-12-01

Severe droughts in 2015, 2016 and 2017 in Ethiopia, Southern Africa, and Somalia have negatively impacted agriculture and municipal water supplies resulting in food and water insecurity. Information from remotely sensed data and field reports indicated that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation (FLDAS) accurately tracked both the anomalously low soil moisture, evapotranspiration and runoff conditions. This work presents efforts to more precisely monitor how the water balance responds to water availability deficits (i.e. drought) as estimated by the FLDAS with CHIRPS precipitation, MERRA-2 meteorological forcing and the Noah33 land surface model.Preliminary results indicate that FLDAS streamflow estimates are well correlated with observed streamflow where irrigation and other channel modifications are not present; FLDAS evapotranspiration (ET) is well correlated with ET from the Operational Simplified Surface Energy Balance model (SSEBop) in Eastern and Southern Africa. We then use these results to monitor availability, and explore trends in water supply and demand.

Data Quality Objectives Supporting the Environmental Soil Monitoring Program for the Idaho National Laboratory Site

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

Haney, Thomas Jay

This document describes the process used to develop data quality objectives for the Idaho National Laboratory (INL) Environmental Soil Monitoring Program in accordance with U.S. Environmental Protection Agency guidance. This document also develops and presents the logic that was used to determine the specific number of soil monitoring locations at the INL Site, at locations bordering the INL Site, and at locations in the surrounding regional area. The monitoring location logic follows the guidance from the U.S. Department of Energy for environmental surveillance of its facilities.

Polycyclic aromatic hydrocarbons pollution effect on soil biological activity in the anthropogenic contaminated area

NASA Astrophysics Data System (ADS)

Batukaev, Abdulmalik; Sushkova, Svetlana; Minkina, Tatiana; Antonenko, Elena; Salamova, Anzhelika; Gimp, Alina; Deryabkina, Irina

2017-04-01

Polycyclic aromatic hydrocarbons (PAHs) are one of the most significant environmental contaminants with mutagenic and carcinogenic properties to all living organisms. The changes in microbial community structure in technogenic polluted soil may be used as tools for predicting and monitoring natural degradation and for search the most effective and appropriate pathways of bioremediation. The present study is aimed to research the biological activity of the soil in the emission zone of Novocherkassk Power station (NPs) (Russia) polluted by PAHs in 2015. The NPs is one of the largest thermal power stations in the south of Russia burning low-quality coal appurtenant the enterprises of I hazardous class. Monitoring plots were located on virgin or no-till fallow areas and not subject to the sanitary-protection zone of the NPs. Soil samples were taken from a depth of 0- to 20-cm, because the major part of PAHs are accumulated in the surface soil layer. The soils of the plots mainly include Chernozems Calcic (plots 1, 4, 5, 7, 9 and 10), Phaeozems Haplic (plots 3, 6, 8 and 11) Fluvisols Umbric (plots 2 and 12). In the soil of 12 monitoring plots located around NPs there were determined the main enzymes, abundance of soil bacteria and 17 priority PAHs. PAHs extraction from soil was performed by new developed ecologically clean method of subcritical water extraction without organic solvents (Sushkova et al., 2015). The level of PAHs around NPs is high at the nearest to factory monitoring plots situated at distance 1,0-1,2 km and reaches from 1600,1±14,7 up to 373,6±7,1 mkg/kg in the 20-cm soil layer. Gradually decrease of PAHs contamination is observed while increasing the distance from the NPs. The level of highmolecular PAHs (4-6 aromatic rings) exceeds the level of lowmolecular (2-3 aromatic rings) PAHs in all monitoring plots situated though the prevailing wind direction from NPs. The close correlations were found between PAHs content and biological activity parameters in the monitoring plots situated through the prevailing wind direction from NPs. Level of dehydrogenases has high positive correlation with technogenic accumulated biphenyl, acenaphthene and negative correlation with anthracene content in studied soil. The lowmolecular PAHs content of soil influenced activity of dehydrogenases positively. Urease activity of monitoring plots has a high positive correlation with 12 PAHs exclude biphenyl, benzo(a)anthracene, naphthalene. Negative dependence of urease activity was observed for lowmolecular PAHs. The abundance of soil bacteria has a negative correlation with PAHs level. Anthracene has no correlations with abundance of soil bacteria and negatively influences on dehydrogenase, urease. Thus, the most subjected to technogenic pollution in 2015 were monitoring plots situated through the prevailing wind direction from NPs. It was established that ratio of low- and highmolecular PAHs content in soils of monitoring plots is the indicator of technogenic pollution soils. Contamination by PAHs in the affected zone has negative influence at the abundance of soil bacteria. The most number of PAHs has positive correlation with biological activity parameters of soil. This work was supported by grant of the Russian Scientific Foundation № 16-14-10217.

A network of experimental forests and ranges: Providing soil solutions for a changing world

Treesearch

Mary Beth Adams

2010-01-01

The network of experimental forests and ranges of the USDA Forest Service represents significant opportunities to provide soil solutions to critical issues of a changing world. This network of 81 experimental forests and ranges encompasses broad geographic, biological, climatic and physical scales, and includes long-term data sets, and long-term experimental...

Soil Monitor: an open source web application for real-time soil sealing monitoring and assessment

NASA Astrophysics Data System (ADS)

Langella, Giuliano; Basile, Angelo; Giannecchini, Simone; Iamarino, Michela; Munafò, Michele; Terribile, Fabio

2016-04-01

Soil sealing is one of the most important causes of land degradation and desertification. In Europe, soil covered by impermeable materials has increased by about 80% from the Second World War till nowadays, while population has only grown by one third. There is an increasing concern at the high political levels about the need to attenuate imperviousness itself and its effects on soil functions. European Commission promulgated a roadmap (COM(2011) 571) by which the net land take would be zero by 2050. Furthermore, European Commission also published a report in 2011 providing best practices and guidelines for limiting soil sealing and imperviousness. In this scenario, we developed an open source and an open source based Soil Sealing Geospatial Cyber Infrastructure (SS-GCI) named as "Soil Monitor". This tool merges a webGIS with parallel geospatial computation in a fast and dynamic fashion in order to provide real-time assessments of soil sealing at high spatial resolution (20 meters and below) over the whole Italy. Common open source webGIS packages are used to implement both the data management and visualization infrastructures, such as GeoServer and MapStore. The high-speed geospatial computation is ensured by a GPU parallelism using the CUDA (Computing Unified Device Architecture) framework by NVIDIA®. This kind of parallelism required the writing - from scratch - all codes needed to fulfil the geospatial computation built behind the soil sealing toolbox. The combination of GPU computing with webGIS infrastructures is relatively novel and required particular attention at the Java-CUDA programming interface. As a result, Soil Monitor is smart because it can perform very high time-consuming calculations (querying for instance an Italian administrative region as area of interest) in less than one minute. The web application is embedded in a web browser and nothing must be installed before using it. Potentially everybody can use it, but the main targets are the stakeholders dealing with sealing, such as policy makers, land owners and asphalt/cement companies. As a matter of fact, Soil Monitor can be used to improve the spatial planning therefore limiting the progression of disordered soil sealing which causes both the direct loss of soils due to imperviousness but also the indirect loss caused by fragmentation of soils (which has different negative effects on the durability of soil functions, such as habitat corridors). Further, in a future version, Soil Monitor would estimate the best location for a new building or help compensating soil losses by actions in other areas to offset drawbacks at zero. The presented SS-GCI dealing with soil sealing - if opportunely scaled - would aid the implementation of best practices for limiting soil sealing or mitigating its effects on soil functions.

Pollution monitoring using networks of honey bees

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

Bromenshenk, J.J.; Dewart, M.L.; Thomas, J.M.

1983-08-01

Each year thousands of chemicals in large quantities are introduced into the global environment and the need for effective methods of monitoring these substances has steadily increased. Most monitoring programs rely upon instrumentation to measure specific contaminants in air, water, or soil. However, it has become apparent that humans and their environment are exposed to complex mixtures of chemicals rather than single entities. As our ability to detect ever smaller quantities of pollutants has increased, the biological significance of these findings has become more uncertain. Also, it is clear that monitoring efforts should shift from short-term studies of easily identifiablemore » sources in localized areas to long-term studies of multiple sources over widespread regions. Our investigations aim at providing better tools to meet these exigencies. Honey bees are discussed as an effective, long-term, self-sustaining system for monitoring environmental impacts. Our results indicate that the use of regional, and possibly national or international, capability can be realized with the aid of beekeepers in obtaining samples and conducting measurements. This approach has the added advantage of public involvement in environmental problem solving and protection of human health and environmental quality.« less

Geophysical methods for monitoring soil stabilization processes

NASA Astrophysics Data System (ADS)

Saneiyan, Sina; Ntarlagiannis, Dimitrios; Werkema, D. Dale; Ustra, Andréa

2018-01-01

Soil stabilization involves methods used to turn unconsolidated and unstable soil into a stiffer, consolidated medium that could support engineered structures, alter permeability, change subsurface flow, or immobilize contamination through mineral precipitation. Among the variety of available methods carbonate precipitation is a very promising one, especially when it is being induced through common soil borne microbes (MICP - microbial induced carbonate precipitation). Such microbial mediated precipitation has the added benefit of not harming the environment as other methods can be environmentally detrimental. Carbonate precipitation, typically in the form of calcite, is a naturally occurring process that can be manipulated to deliver the expected soil strengthening results or permeability changes. This study investigates the ability of spectral induced polarization and shear-wave velocity for monitoring calcite driven soil strengthening processes. The results support the use of these geophysical methods as soil strengthening characterization and long term monitoring tools, which is a requirement for viable soil stabilization projects. Both tested methods are sensitive to calcite precipitation, with SIP offering additional information related to long term stability of precipitated carbonate. Carbonate precipitation has been confirmed with direct methods, such as direct sampling and scanning electron microscopy (SEM). This study advances our understanding of soil strengthening processes and permeability alterations, and is a crucial step for the use of geophysical methods as monitoring tools in microbial induced soil alterations through carbonate precipitation.

A Unified Experimental Approach for Estimation of Irrigationwater and Nitrate Leaching in Tree Crops

NASA Astrophysics Data System (ADS)

Hopmans, J. W.; Kandelous, M. M.; Moradi, A. B.

2014-12-01

Groundwater quality is specifically vulnerable in irrigated agricultural lands in California and many other(semi-)arid regions of the world. The routine application of nitrogen fertilizers with irrigation water in California is likely responsible for the high nitrate concentrations in groundwater, underlying much of its main agricultural areas. To optimize irrigation/fertigation practices, it is essential that irrigation and fertilizers are applied at the optimal concentration, place, and time to ensure maximum root uptake and minimize leaching losses to the groundwater. The applied irrigation water and dissolved fertilizer, as well as root growth and associated nitrate and water uptake, interact with soil properties and fertilizer source(s) in a complex manner that cannot easily be resolved. It is therefore that coupled experimental-modeling studies are required to allow for unraveling of the relevant complexities that result from typical field-wide spatial variations of soil texture and layering across farmer-managed fields. We present experimental approaches across a network of tree crop orchards in the San Joaquin Valley, that provide the necessary soil data of soil moisture, water potential and nitrate concentration to evaluate and optimize irrigation water management practices. Specifically, deep tensiometers were used to monitor in-situ continuous soil water potential gradients, for the purpose to compute leaching fluxes of water and nitrate at both the individual tree and field scale.

Smap Soil Moisture Data Assimilation for the Continental United States and Eastern Africa

NASA Astrophysics Data System (ADS)

Blankenship, C. B.; Case, J.; Zavodsky, B.; Crosson, W. L.

2016-12-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center manages near-real-time runs of the Noah Land Surface Model within the NASA Land Information System (LIS) over Continental U.S. (CONUS) and Eastern Africa domains. Soil moisture products from the CONUS model run are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. The baseline LIS configuration is the Noah model driven by atmospheric and combined radar/gauge precipitation analyses, and input satellite-derived real-time green vegetation fraction on a 3-km grid for the CONUS. This configuration is being enhanced by adding the assimilation of Level 2 Soil Moisture Active/Passive (SMAP) soil moisture retrievals in a parallel run beginning on 1 April 2015. Our implementation of SMAP assimilation includes a cumulative distribution function (CDF) matching approach that aggregates points with similar soil types. This method allows creation of robust CDFs with a short data record, and also permits the correction of local anomalies that may arise from poor forcing data (e.g., quality-control problems with rain gauges). Validation results using in situ soil monitoring networks in the CONUS are shown, with comparisons to the baseline SPoRT-LIS run. Initial results are also presented from a modeling run in eastern Africa, forced by Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation data. Strategies for spatial downscaling and for dealing with effective depth of the retrieval product are also discussed.

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.

Relative skills of soil moisture and vegetation optical depth retrievals for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

Soil moisture condition is an important indicator for agricultural drought monitoring. Through the Land Parameter Retrieval Model (LPRM), vegetation optical depth (VOD) as well as surface soil moisture (SM) can be retrieved simultaneously from brightness temperature observations from the Advanced Mi...

Functional resilience of microbial ecosystems in soil: How important is a spatial analysis?

NASA Astrophysics Data System (ADS)

König, Sara; Banitz, Thomas; Centler, Florian; Frank, Karin; Thullner, Martin

2015-04-01

Microbial life in soil is exposed to fluctuating environmental conditions influencing the performance of microbially mediated ecosystem services such as biodegradation of contaminants. However, as this environment is typically very heterogeneous, spatial aspects can be expected to play a major role for the ability to recover from a stress event. To determine key processes for functional resilience, simple scenarios with varying stress intensities were simulated within a microbial simulation model and the biodegradation rate in the recovery phase monitored. Parameters including microbial growth and dispersal rates were varied over a typical range to consider microorganisms with varying properties. Besides an aggregated temporal monitoring, the explicit observation of the spatio-temporal dynamics proved essential to understand the recovery process. For a mechanistic understanding of the model system, scenarios were also simulated with selected processes being switched-off. Results of the mechanistic and the spatial view show that the key factors for functional recovery with respect to biodegradation after a simple stress event depend on the location of the observed habitats. The limiting factors near unstressed areas are spatial processes - the mobility of the bacteria as well as substrate diffusion - the longer the distance to the unstressed region the more important becomes the process growth. Furthermore, recovery depends on the stress intensity - after a low stress event the spatial configuration has no influence on the key factors for functional resilience. To confirm these results, we repeated the stress scenarios but this time including an additional dispersal network representing a fungal network in soil. The system benefits from an increased spatial performance due to the higher mobility of the degrading microorganisms. However, this effect appears only in scenarios where the spatial distribution of the stressed area plays a role. With these simulations we show that spatial aspects play a main role for recovering after a severe stress event in a highly heterogeneous environment such as soil, and thus the relevance of the exact distribution of the stressed area. In consequence a spatial-mechanistic view is necessary for examining the functional resilience as the aggregated temporal view alone could not have led to these conclusions. Further research should explore the importance of a spatial view for quantifying the recovery of the ecosystem service also after more complex stress regimes.

Calibration of Cosmic Ray Neutron Probes in complex systems: open research issues

NASA Astrophysics Data System (ADS)

Piussi, Laura; Tomelleri, Enrico; Bertoldi, Giacomo; Zebisch, Marc; Niedrist, Georg; Tonon, Giustino

2017-04-01

Soil moisture is a key variable for environmental monitoring, hydrological and climate change research as it controls mass and energy fluxes in the soil-plant-atmosphere continuum. Actual soil moisture monitoring methods are capable of providing observations either at a very big spatial scale and timely spotty satellite observations or at a very small scale and timely continuous point measurements. In this framework, meso-scale timely continuous measurements appear of key relevance, thus, recently, Cosmic Ray Neutron Sensing (CRNS) is gaining more and more importance, because of its capacity to deliver long time-series of observations within a footprint of 500m of diameter. Even if during the last years a remarkable number of papers have been published, the calibration of Cosmic Ray Neutron Probes (CRPs) in heterogeneous ecosystems is still an open issue. The CRP is sensitive to all the Hydrogen species and their distribution within the footprint, thus in environments that can be assumed as homogeneous a good accordance between the CRNS data and observed soil moisture can be reached, but, where Hydrogen distributions are complex, different calibration campaigns lead to different results. In order to improve the efficiency of the method, a better understanding of the effects of combined spatial and temporal variability has to be reached. The aim of the actual work is to better understand the effects of multiple Hydrogen sources that vary in time and space and evaluate different approaches in calibration over complex terrain in a mountain area. We present different calibration approaches used for an alpine pasture, which is a research site of the LTER network in South-Tyrol (Italy). In the study site long-term soil moisture observations are present and are used for remote-sensing data validation. For this specific and highly heterogeneous site, the effects of heterogeneous land-cover and topography on CRP calibration are evaluated and some hypotheses on the major sources of uncertainty are formulated.

Optimal river monitoring network using optimal partition analysis: a case study of Hun River, Northeast China.

PubMed

Wang, Hui; Liu, Chunyue; Rong, Luge; Wang, Xiaoxu; Sun, Lina; Luo, Qing; Wu, Hao

2018-01-09

River monitoring networks play an important role in water environmental management and assessment, and it is critical to develop an appropriate method to optimize the monitoring network. In this study, an effective method was proposed based on the attainment rate of National Grade III water quality, optimal partition analysis and Euclidean distance, and Hun River was taken as a method validation case. There were 7 sampling sites in the monitoring network of the Hun River, and 17 monitoring items were analyzed once a month during January 2009 to December 2010. The results showed that the main monitoring items in the surface water of Hun River were ammonia nitrogen (NH 4 + -N), chemical oxygen demand, and biochemical oxygen demand. After optimization, the required number of monitoring sites was reduced from seven to three, and 57% of the cost was saved. In addition, there were no significant differences between non-optimized and optimized monitoring networks, and the optimized monitoring networks could correctly represent the original monitoring network. The duplicate setting degree of monitoring sites decreased after optimization, and the rationality of the monitoring network was improved. Therefore, the optimal method was identified as feasible, efficient, and economic.

Developing an operational rangeland water requirement satisfaction index

USGS Publications Warehouse

Senay, Gabriel B.; Verdin, James P.; Rowland, James

2011-01-01

Developing an operational water requirement satisfaction index (WRSI) for rangeland monitoring is an important goal of the famine early warning systems network. An operational WRSI has been developed for crop monitoring, but until recently a comparable WRSI for rangeland was not successful because of the extremely poor performance of the index when based on published crop coefficients (K c) for rangelands. To improve the rangeland WRSI, we developed a simple calibration technique that adjusts the K c values for rangeland monitoring using long-term rainfall distribution and reference evapotranspiration data. The premise for adjusting the K c values is based on the assumption that a viable rangeland should exhibit above-average WRSI (values >80%) during a normal year. The normal year was represented by a median dekadal rainfall distribution (satellite rainfall estimate from 1996 to 2006). Similarly, a long-term average for potential evapotranspiration was used as input to the famine early warning systems network WRSI model in combination with soil-water-holding capacity data. A dekadal rangeland WRSI has been operational for east and west Africa since 2005. User feedback has been encouraging, especially with regard to the end-of-season WRSI anomaly products that compare the index's performance to ‘normal’ years. Currently, rangeland WRSI products are generated on a dekadal basis and posted for free distribution on the US Geological Survey early warning website at http://earlywarning.usgs.gov/adds/

Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

NASA Astrophysics Data System (ADS)

Perrier, E. M. A.; Bird, N. R. A.; Rieutord, T. B.

2010-04-01

Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a Critical Filtration Size (CFS) delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009). Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

NASA Astrophysics Data System (ADS)

Perrier, E. M. A.; Bird, N. R. A.; Rieutord, T. B.

2010-10-01

Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a critical filtration size (CFS) delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009). Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

Precision, accuracy, and efficiency of four tools for measuring soil bulk density or strength.

Treesearch

Richard E. Miller; John Hazard; Steven Howes

2001-01-01

Monitoring soil compaction is time consuming. A desire for speed and lower costs, however, must be balanced with the appropriate precision and accuracy required of the monitoring task. We compared three core samplers and a cone penetrometer for measuring soil compaction after clearcut harvest on a stone-free and a stony soil. Precision (i.e., consistency) of each tool...

Challenges in Ecohydrological Monitoring at Soil-Vegetation Interfaces: Exploiting the Potential for Fibre Optic Technologies

NASA Astrophysics Data System (ADS)

Chalari, A.; Ciocca, F.; Krause, S.; Hannah, D. M.; Blaen, P.; Coleman, T. I.; Mondanos, M.

2015-12-01

The Birmingham Institute of Forestry Research (BIFoR) is using Free-Air Carbon Enrichment (FACE) experiments to quantify the long-term impact and resilience of forests into rising atmospheric CO2 concentrations. The FACE campaign critically relies on a successful monitoring and understanding of the large variety of ecohydrological processes occurring across many interfaces, from deep soil to above the tree canopy. At the land-atmosphere interface, soil moisture and temperature are key variables to determine the heat and water exchanges, crucial to the vegetation dynamics as well as to groundwater recharge. Traditional solutions for monitoring soil moisture and temperature such as remote techniques and point sensors show limitations in fast acquisition rates and spatial coverage, respectively. Hence, spatial patterns and temporal dynamics of heat and water fluxes at this interface can only be monitored to a certain degree, limiting deeper knowledge in dynamically evolving systems (e.g. in impact of growing vegetation). Fibre optics Distributed Temperature Sensors (DTS) can measure soil temperatures at high spatiotemporal resolutions and accuracy, along kilometers of optical cable buried in the soil. Heat pulse methods applied to electrical elements embedded in the optical cable can be used to obtain the soil moisture. In July 2015 a monitoring system based on DTS has been installed in a recently forested hillslope at BIFoR in order to quantify high-resolution spatial patterns and high-frequency temporal dynamics of soil heat fluxes and soil moisture conditions. Therefore, 1500m of optical cables have been carefully deployed in three overlapped loops at 0.05m, 0.25m and 0.4m from the soil surface and an electrical system to send heat pulses along the optical cable has been developed. This paper discussed both, installation and design details along with first results of the soil moisture and temperature monitoring carried out since July 2015. Moreover, interpretations of the collected data to investigate the impact on soil moisture dynamics of i) forest evolution (long timescale), (ii) seasonality and, (iii) high-frequency forcing, are discussed.

Broccoli/weed/soil discrimination by optical reflectance using neural networks

NASA Astrophysics Data System (ADS)

Hahn, Federico

1995-04-01

Broccoli is grown extensively in Scotland, and has become one of the main vegetables cropped, due to its high yields and profits. Broccoli, weed and soil samples from 6 different farms were collected and their spectra obtained and analyzed using discriminant analysis. High crop/weed/soil discrimination success rates were encountered in each farm, but the selected wavelengths varied in each farm due to differences in broccoli variety, weed species incidence and soil type. In order to use only three wavelengths, neural networks were introduced and high crop/weed/soil discrimination accuracies for each farm were achieved.

Understanding processes that generate flash floods in the arid Judean Desert to the Dead Sea - a measurement network

NASA Astrophysics Data System (ADS)

Hennig, Hanna; Rödiger, Tino; Laronne, Jonathan B.; Geyer, Stefan; Merz, Ralf

2016-04-01

Flash floods in (semi-) arid regions are fascinating in their suddenness and can be harmful for humans, infrastructure, industry and tourism. Generated within minutes, an early warning system is essential. A hydrological model is required to quantify flash floods. Current models to predict flash floods are often based on simplified concepts and/or on concepts which were developed for humid regions. To more closely relate such models to local conditions, processes within catchments where flash floods occur require consideration. In this study we present a monitoring approach to decipher different flash flood generating processes in the ephemeral Wadi Arugot on the western side of the Dead Sea. To understand rainfall input a dense rain gauge network was installed. Locations of rain gauges were chosen based on land use, slope and soil cover. The spatiotemporal variation of rain intensity will also be available from radar backscatter. Level pressure sensors located at the outlet of major tributaries have been deployed to analyze in which part of the catchment water is generated. To identify the importance of soil moisture preconditions, two cosmic ray sensors have been deployed. At the outlet of the Arugot water is sampled and level is monitored. To more accurately determine water discharge, water velocity is measured using portable radar velocimetry. A first analysis of flash flood processes will be presented following the FLEX-Topo concept .(Savenije, 2010), where each landscape type is represented using an individual hydrological model according to the processes within the three hydrological response units: plateau, desert and outlet. References: Savenije, H. H. G.: HESS Opinions "Topography driven conceptual modelling (FLEX-Topo)", Hydrol. Earth Syst. Sci., 14, 2681-2692, doi:10.5194/hess-14-2681-2010, 2010.

An adaptive management process for forest soil conservation.

Treesearch

Michael P. Curran; Douglas G. Maynard; Ronald L. Heninger; Thomas A. Terry; Steven W. Howes; Douglas M. Stone; Thomas Niemann; Richard E. Miller; Robert F. Powers

2005-01-01

Soil disturbance guidelines should be based on comparable disturbance categories adapted to specific local soil conditions, validated by monitoring and research. Guidelines, standards, and practices should be continually improved based on an adaptive management process, which is presented in this paper. Core components of this process include: reliable monitoring...

Monitoring the Vadose Zone Moisture Regime Below a Surface Barrier

NASA Astrophysics Data System (ADS)

Zhang, Z. F.; Strickland, C. E.; Field, J. G.

2009-12-01

A 6000 m2 interim surface barrier has been constructed over a portion of the T Tank Farm in the Depart of Energy’s Hanford site. The purpose of using a surface barrier was to reduce or eliminate the infiltration of meteoric precipitation into the contaminated soil zone due to past leaks from Tank T-106 and hence to reduce the rate of movement of the plume. As part of the demonstration effort, vadose zone moisture is being monitored to assess the effectiveness of the barrier on the reduction of soil moisture flow. A vadose zone monitoring system was installed to measure soil water conditions at four horizontal locations (i.e., instrument Nests A, B, C, and D) outside, near the edge of, and beneath the barrier. Each instrument nest consists of a capacitance probe with multiple sensors, multiple heat-dissipation units, and a neutron probe access tube used to measure soil-water content and soil-water pressure. Nest A serves as a control by providing subsurface conditions outside the influence of the surface barrier. Nest B provides subsurface measurements to assess barrier edge effects. Nests C and D are used to assess the impact of the surface barrier on soil-moisture conditions beneath it. Monitoring began in September 2006 and continues to the present. To date, the monitoring system has provided high-quality data. Results show that the soil beneath the barrier has been draining from the shallower depth. The lack of climate-caused seasonal variation of soil water condition beneath the barrier indicates that the surface barrier has minimized water exchange between the soil and the atmosphere.

[Current situation of soil-transmitted nematodiasis monitoring in China and working keys in future].

PubMed

Chen, Ying-dan; Zang, Wei

2015-04-01

Soil-transmitted nematodiasis is widely epidemic in rural areas in China. It was showed that the infection rate of soil-transmitted nematodes was 19.56% while the overall number of persons infected was 129,000,000, which was supported by the results of the National Survey of Current Situation of Major Human Parasitic Diseases in China in 2005 published by former Ministry of Health. Therefore, soil-transmitted nematodiasis was included in the national infectious diseases and pathogenic media monitoring system by Chinese Center for Disease Control and Prevention in 2006, and subsequently 22 monitoring spots were established nationwide. From 2006 to 2013, the human infection rate of intestinal nematodes in national monitoring spots decreased from 20.88% to 3.12%, which showed a declining trend year by year. Meanwhile, the infection rates of Ascaris lumbricoides, Trichuris trichiura, hookworm, Enterobius vermicularis decreased from 10.10%, 5.88%, 8.88%, 10.00% in 2006 to 0.76%, 0.42%, 2.04%, 6.78% in 2013 respectively. In this paper, the current situation of soil-transmitted nematodiasis is overviewed based on a summary of the 8 years' monitoring work, as well as the experiences, challenges and key of monitoring work in the future.

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 6 2012-07-01 2012-07-01 false Monitoring network completion. 58.13 Section 58.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a...

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 6 2014-07-01 2014-07-01 false Monitoring network completion. 58.13 Section 58.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a...

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 6 2013-07-01 2013-07-01 false Monitoring network completion. 58.13 Section 58.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a...

Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

NASA Technical Reports Server (NTRS)

Wang, Shin-Ywan

2012-01-01

The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

Predicting the spatial distribution of soil profile in Adapazari/Turkey by artificial neural networks using CPT data

NASA Astrophysics Data System (ADS)

Arel, Ersin

2012-06-01

The infamous soils of Adapazari, Turkey, that failed extensively during the 46-s long magnitude 7.4 earthquake in 1999 have since been the subject of a research program. Boreholes, piezocone soundings and voluminous laboratory testing have enabled researchers to apply sophisticated methods to determine the soil profiles in the city using the existing database. This paper describes the use of the artificial neural network (ANN) model to predict the complex soil profiles of Adapazari, based on cone penetration test (CPT) results. More than 3236 field CPT readings have been collected from 117 soundings spread over an area of 26 km2. An attempt has been made to develop the ANN model using multilayer perceptrons trained with a feed-forward back-propagation algorithm. The results show that the ANN model is fairly accurate in predicting complex soil profiles. Soil identification using CPT test results has principally been based on the Robertson charts. Applying neural network systems using the chart offers a powerful and rapid route to reliable prediction of the soil profiles.

Long-Term Oil Contamination Alters the Molecular Ecological Networks of Soil Microbial Functional Genes

PubMed Central

Liang, Yuting; Zhao, Huihui; Deng, Ye; Zhou, Jizhong; Li, Guanghe; Sun, Bo

2016-01-01

With knowledge on microbial composition and diversity, investigation of within-community interactions is a further step to elucidate microbial ecological functions, such as the biodegradation of hazardous contaminants. In this work, microbial functional molecular ecological networks were studied in both contaminated and uncontaminated soils to determine the possible influences of oil contamination on microbial interactions and potential functions. Soil samples were obtained from an oil-exploring site located in South China, and the microbial functional genes were analyzed with GeoChip, a high-throughput functional microarray. By building random networks based on null model, we demonstrated that overall network structures and properties were significantly different between contaminated and uncontaminated soils (P < 0.001). Network connectivity, module numbers, and modularity were all reduced with contamination. Moreover, the topological roles of the genes (module hub and connectors) were altered with oil contamination. Subnetworks of genes involved in alkane and polycyclic aromatic hydrocarbon degradation were also constructed. Negative co-occurrence patterns prevailed among functional genes, thereby indicating probable competition relationships. The potential “keystone” genes, defined as either “hubs” or genes with highest connectivities in the network, were further identified. The network constructed in this study predicted the potential effects of anthropogenic contamination on microbial community co-occurrence interactions. PMID:26870020

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

Networks Depicting the Fine-Scale Co-Occurrences of Fungi in Soil Horizons.

PubMed

Toju, Hirokazu; Kishida, Osamu; Katayama, Noboru; Takagi, Kentaro

2016-01-01

Fungi in soil play pivotal roles in nutrient cycling, pest controls, and plant community succession in terrestrial ecosystems. Despite the ecosystem functions provided by soil fungi, our knowledge of the assembly processes of belowground fungi has been limited. In particular, we still have limited knowledge of how diverse functional groups of fungi interact with each other in facilitative and competitive ways in soil. Based on the high-throughput sequencing data of fungi in a cool-temperate forest in northern Japan, we analyzed how taxonomically and functionally diverse fungi showed correlated fine-scale distributions in soil. By uncovering pairs of fungi that frequently co-occurred in the same soil samples, networks depicting fine-scale co-occurrences of fungi were inferred at the O (organic matter) and A (surface soil) horizons. The results then led to the working hypothesis that mycorrhizal, endophytic, saprotrophic, and pathogenic fungi could form compartmentalized (modular) networks of facilitative, antagonistic, and/or competitive interactions in belowground ecosystems. Overall, this study provides a research basis for further understanding how interspecific interactions, along with sharing of niches among fungi, drive the dynamics of poorly explored biospheres in soil.

Prediction of near-surface soil moisture at large scale by digital terrain modeling and neural networks.

PubMed

Lavado Contador, J F; Maneta, M; Schnabel, S

2006-10-01

The capability of Artificial Neural Network models to forecast near-surface soil moisture at fine spatial scale resolution has been tested for a 99.5 ha watershed located in SW Spain using several easy to achieve digital models of topographic and land cover variables as inputs and a series of soil moisture measurements as training data set. The study methods were designed in order to determining the potentials of the neural network model as a tool to gain insight into soil moisture distribution factors and also in order to optimize the data sampling scheme finding the optimum size of the training data set. Results suggest the efficiency of the methods in forecasting soil moisture, as a tool to assess the optimum number of field samples, and the importance of the variables selected in explaining the final map obtained.

Informing soil models using pedotransfer functions: challenges and perspectives

NASA Astrophysics Data System (ADS)

Pachepsky, Yakov; Romano, Nunzio

2015-04-01

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

Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index

NASA Astrophysics Data System (ADS)

Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.

2018-04-01

Soil moisture is an important parameter for agricultural production. Efficient and accurate monitoring of soil moisture is an important link to ensure the safety of agricultural production. Remote sensing technology has been widely used in agricultural moisture monitoring because of its timeliness, cyclicality, dynamic tracking of changes in things, easy access to data, and extensive monitoring. Vegetation index and surface temperature are important parameters for moisture monitoring. Based on NDVI, this paper introduces land surface temperature and average temperature for optimization. This article takes the soil moisture in winter wheat growing area in Henan Province as the research object, dividing Henan Province into three main regions producing winter wheat and dividing the growth period of winter wheat into the early, middle and late stages on the basis of phenological characteristics and regional characteristics. Introducing appropriate correction factor during the corresponding growth period of winter wheat, correcting the vegetation index in the corresponding area, this paper establishes regression models of soil moisture on NDVI and soil moisture on modified NDVI based on correlation analysis and compare models. It shows that modified NDVI is more suitable as a indicator of soil moisture because of the better correlation between soil moisture and modified NDVI and the higher prediction accuracy of the regression model of soil moisture on modified NDVI. The research in this paper has certain reference value for winter wheat farmland management and decision-making.

Assessing the risk of foliar injury from ozone on vegetation in parks in the U.S. National Park Service's Vital Signs Network.

PubMed

Kohut, Robert

2007-10-01

The risk of ozone injury to plants was assessed in support of the National Park Service's Vital Signs Monitoring Network program. The assessment examined bioindicator species, evaluated levels of ozone exposure, and investigated soil moisture conditions during periods of exposure for a 5-year period in each park. The assessment assigned each park a risk rating of high, moderate, or low. For the 244 parks for which assessments were conducted, the risk of foliar injury was high in 65 parks, moderate in 46 parks, and low in 131 parks. Among the well-known parks with a high risk of ozone injury are Gettysburg, Valley Forge, Delaware Water Gap, Cape Cod, Fire Island, Antietam, Harpers Ferry, Manassas, Wolf Trap Farm Park, Mammoth Cave, Shiloh, Sleeping Bear Dunes, Great Smoky Mountains, Joshua Tree, Sequoia and Kings Canyon, and Yosemite.

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.

Long-term monitoring of temperature in the subsoil using Fiber Optic Distributed Sensing

NASA Astrophysics Data System (ADS)

Susanto, Kusnahadi; Malet, Jean-Philippe; Gance, Julien; Marc, Vincent

2017-04-01

Monitoring changes in soil water content in the vadose zone of soils is a great importance for various hydrological, agronomical, ecological and environmental studies. By using soil temperature measurements with Fiber-Optic Distributed Temperature Sensing (FO-DTS), we can indirectly document soil water changes at high spatial and temporal frequency. In this research, we installed an observatory of soil temperature on a representative black marl slope of the long-term Draix-Bléone hydrological observatory (South French Alps, Réseau de Basins-Versants / RBV). A 350 m long reinforced fiber optic cable was buried at 0.05, 0.10 and 0.15 m of depths and installed at the soil surface. The total length of the monitored profile is 60 m, and it three different soil units consisting of argillaceous weathered black marls, silty colluvium under grass and silty colluvium under forest. Soil temperature is measured every 6 minutes at a spatial resolution of 0.50 m using a double-ended configuration. Both passive and active (heating of the FO) is used to document soil water changes. We present the analysis of a period of 6 months of temperature measurements (January-July 2016). Changes in soil temperature at various temporal scales (rainfall event, season) and for the three units are discussed. These changes indicate different processes of water infiltration at different velocities in relation to the presence of roots and the soil permeability. We further test several inversion strategies to estimate soil water content from the thermal diffusivity of the soils using simple and more complex thermal models. Some limitations of using this indirect technique for long-term monitoring are also presented. The work is supported by the research project HYDROSLIDE and the large infrastructure project CRITEX funded by the French Research Agency (ANR).

A network monitor for HTTPS protocol based on proxy

NASA Astrophysics Data System (ADS)

Liu, Yangxin; Zhang, Lingcui; Zhou, Shuguang; Li, Fenghua

2016-10-01

With the explosive growth of harmful Internet information such as pornography, violence, and hate messages, network monitoring is essential. Traditional network monitors is based mainly on bypass monitoring. However, we can't filter network traffic using bypass monitoring. Meanwhile, only few studies focus on the network monitoring for HTTPS protocol. That is because HTTPS data is in the encrypted traffic, which makes it difficult to monitor. This paper proposes a network monitor for HTTPS protocol based on proxy. We adopt OpenSSL to establish TLS secure tunes between clients and servers. Epoll is used to handle a large number of concurrent client connections. We also adopt Knuth- Morris-Pratt string searching algorithm (or KMP algorithm) to speed up the search process. Besides, we modify request packets to reduce the risk of errors and modify response packets to improve security. Experiments show that our proxy can monitor the content of all tested HTTPS websites efficiently with little loss of network performance.

Remote Assessment of Forest Ecosystem Stress (RAFES): Development of a Real Time Decision Support Tool for the Eastern U.S

NASA Astrophysics Data System (ADS)

Clinton, B.; Vose, J.; Novick, K.; Liu, Y.

2011-12-01

Drier and warmer conditions predicted with climate change models are likely to significantly impact forest ecosystems over the next several decades. The U.S. has experienced significant droughts over the past several years that have increased the susceptibility of forests to insect outbreaks, disease, and wildfire. Weather data collected with traditional approaches provide an indirect measure of drought or temperature stress; however, the significance of short-term or prolonged climate-related stress varies considerably across the landscape as topography, elevations, edaphic condition and antecedent conditions vary. This limits the capacity of land managers to anticipate and initiate management activities that could offset the impacts of climate-related forest stress. Decision support tools are needed that allow fine scale monitoring of stress conditions in forest ecosystems in real time to help land managers evaluate response strategies. To assist land managers in managing the impacts of climate change, we are developing a stress monitoring and decision support system across multiple sites in the eastern U.S. that (1) provides remote data capture of environmental parameters that quantify climate-related forest stress, (2) links remotely captured data with physiologically-based indices of tree water stress, and (3) provides a PC-based analytical tool for land managers to monitor and assess the severity of climate-related stress. Currently the network represents southern coastal plain pine plantation, Atlantic coastal flatwoods mixed pine-hardwood, southern piedmont upland mixed pine-hardwood, southern Appalachian dry ridge and mesic riparian, southern Arkansas managed mature pine, and northern Minnesota mature aspen. The strategy for selecting additional sites for the network will be a focus on at-risk ecosystems deemed particularly vulnerable to the affects of predicted climate change such as those in ecotonal transition regions, or those at the fringes of their ranges. The sensor arrays at each site detect water and temperature stress variables and transmit those data to a field office. Sensors include air and soil temperature, relative humidity, fuel moisture and temperature, xylem sap flux density, soil moisture and matric potential, precipitation, and solar radiation. Data are transmitted in real-time to the NOAA Geostationary Operational Environmental Satellite (GOES). A PC-based software program that downloads monitoring data from the GOES satellite, analyzes the data, and provides the land manager with an assessment of climate-related stress conditions and potential forest health threat levels in real time is under development. Data collection began in early 2010 on most sites, and we have at least one year of data from all nine sites within the network. We are currently comparing estimates of stress levels on our sites with estimates of stress from common drought indices. For this presentation, we are comparing and contrasting four sites representing an environmental gradient within the network.

Advanced Soil Moisture Network Technologies; Developments in Collecting in situ Measurements for Remote Sensing Missions

NASA Astrophysics Data System (ADS)

Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.

2015-12-01

The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.

Design and field tests of a directly coupled waveguide-on-access-tube soil water sensor

USDA-ARS?s Scientific Manuscript database

Sensor systems capable of monitoring soil water content can provide a useful tool for irrigation control. Current systems are limited by installation depth, labor, accuracy, and cost. Time domain reflectometry (TDR) is an approach for monitoring soil water content that relates the travel time of an ...

Linking Carbon Flux Dynamics and Soil Structure in Dryland Soils

NASA Astrophysics Data System (ADS)

DeCarlo, K. F.; Caylor, K. K.

2016-12-01

Biological sources in the form of microbes and plants play a fundamental role in determining the magnitude of carbon flux. However, the geophysical structure of the soil (which the carbon must pass through before entering the atmosphere) often serves as a constraining entity, which has the potential to serve as instigators or mitigators of those carbon and hydrologic flux processes. We characterized soil carbon dynamics in three dryland soil systems: bioturbated soils, biocompacted soils, and undisturbed soils. Carbon fluxes were characterized using a closed-system respiration chamber, with CO2 concentration differences measured using an infrared gas analyzer (IRGA). Structure of the soil systems, with a focus on the macro-crack structure, were characterized using a combined resin-casting/X-ray imaging technique. Results show fundamental differences in carbon dynamics between the different soil systems/structures: control soils have gaussian distributions of carbon flux that decrease with progressive drying of the soil, while biocompacted soils exhibit exponentially distributed fluxes that do not regularly decrease with increased drying of the soil. Bioturbated soils also exhibit an exponential distribution of carbon flux, though at a much higher magnitude. These differences are evaluated in the context of the underlying soil structure: while the control soils exhibit a shallow and narrow crack structure, the biocompacted soils exhibit a "systematic" crack network with moderate cracking intensity and large depth. The deep crack networks of the biocompacted soils may serve to physically enhance an otherwise weak source of carbon via advection and/or convection, inducing fluxes that are equal or greater than an otherwise carbon-rich soil. The bioturbated soils exhibit a "surficial" crack network that is shallow but extensive, but additionally have deep holes known to convectively vent carbon, which may explain their periodically large carbon fluxes. Our results suggest that variability in soil structure, as well as carbon source, plays a fundamental role in carbon flux dynamics, and the importance of evaluating biological carbon source and geophysical soil structure in a dryland environment.

A survey of topsoil arsenic and mercury concentrations across France.

PubMed

Marchant, B P; Saby, N P A; Arrouays, D

2017-08-01

Even at low concentrations, the presence of arsenic and mercury in soils can lead to ecological and health impacts. The recent European-wide LUCAS Topsoil Survey found that the arsenic concentration of a large proportion of French soils exceeded a threshold which indicated that further investigation was required. A much smaller proportion of soils exceeded the corresponding threshold for mercury but the impacts of mining and industrial activities on mercury concentrations are not well understood. We use samples from the French national soil monitoring network (RMQS: Réseau de Mesures de la Qualité des Sols) to explore the variation of topsoil arsenic and mercury concentrations across mainland France at a finer spatial resolution than was reported by LUCAS Topsoil. We use geostatistical methods to map the expected concentrations of these elements in the topsoil and the probabilities that the legislative thresholds are exceeded. We find that, with the exception of some areas where the geogenic concentrations and soil adsorption capacities are very low, arsenic concentrations are generally larger than the threshold which indicates that further assessment of the area is required. The lower of two other guideline values indicating risks to ecology or health is exceeded in fewer than 5% of RMQS samples. These exceedances occur in localised hot-spots primarily associated with mining and mineralization. The probabilities of mercury concentrations exceeding the further assessment threshold value are everywhere less than 0.01 and none of the RMQS samples exceed either of the ecological and health risk thresholds. However, there are some regions with elevated concentrations which can be related to volcanic material, natural mineralizations and industrial contamination. These regions are more diffuse than the hot-spots of arsenic reflecting the greater volatility of mercury and therefore the greater ease with which it can be transported and redeposited. The maps provide a baseline against which future phases of the RMQS can be compared and highlight regions where the threat of soil contamination and its impacts should be more closely monitored. Copyright © 2017 Elsevier Ltd. All rights reserved.

Monitoring the subsurface hydrologic response to shallow landsliding in the San Francisco Bay Area, California

NASA Astrophysics Data System (ADS)

Collins, B. D.; Stock, J. D.; Foster, K. A.; Knepprath, N.; Reid, M. E.; Schmidt, K. M.; Whitman, M. W.

2011-12-01

Intense or prolonged rainfall triggers shallow landslides in steeplands of the San Francisco Bay Area each year. These landslides cause damage to built infrastructure and housing, and in some cases, lead to fatalities. Although our ability to forecast and map the distribution of rainfall has improved (e.g., NEXRAD, SMART-R), our ability to estimate landslide susceptibility is limited by a lack of information about the subsurface response to rainfall. In particular, the role of antecedent soil moisture content in setting the timing of shallow landslide failures remains unconstrained. Advances in instrumentation and telemetry have substantially reduced the cost of such monitoring, making it feasible to set up and maintain networks of such instruments in areas with a documented history of shallow landslides. In 2008, the U.S. Geological Survey initiated a pilot project to establish a series of shallow landslide monitoring stations in the San Francisco Bay area. The goal of this project is to obtain a long-term (multi-year) record of subsurface hydrologic conditions that occur from winter storms. Three monitoring sites are now installed in key landslide prone regions of the Bay Area (East Bay Hills, Marin County, and San Francisco Peninsula Hills) each consisting of a rain gage and multiple nests of soil-moisture sensors, matric-potential sensors, and piezometers. The sites were selected with similar characteristics in mind consisting of: (1) convergent bedrock hollow topographic settings located near ridge tops, (2) underlying sandstone bedrock substrates, (3) similar topographic gradients (~30°), (4) vegetative assemblages of grasses with minor chaparral, and (5) a documented history of landsliding in the vicinity of each site. These characteristics are representative of shallow-landslide-prone regions of the San Francisco Bay Area and also provide some constraint on the ability to compare and contrast subsurface response across different regions. Data streams from two of the sites, one operational in 2009 and one in 2010 have been analyzed and showcase both the seasonal patterns of moisture increase and decrease between summer-winter-summer conditions, as well as patterns of cyclical short-term wetting and drying as storms pass through the region. Further, the data show that at one location (East Bay Hills), storm-generated antecedent soil moisture conditions led to positive pore water pressures that correlate directly to shallow landsliding observed in the immediate vicinity of the monitoring site. This information, along with more extensive and continued monitoring and analysis should provide a basis and methodology for performing future shallow landslide assessments which depend not only on forecast rainfall, but also on pre-storm antecedent, subsurface soil moisture conditions.

New-generation security network with synergistic IP sensors

NASA Astrophysics Data System (ADS)

Peshko, Igor

2007-09-01

Global Dynamic Monitoring and Security Network (GDMSN) for real-time monitoring of (1) environmental and atmospheric conditions: chemical, biological, radiological and nuclear hazards, climate/man-induced catastrophe areas and terrorism threats; (2) water, soil, food chain quantifiers, and public health care; (3) large government/public/ industrial/ military areas is proposed. Each GDMSN branch contains stationary or mobile terminals (ground, sea, air, or space manned/unmanned vehicles) equipped with portable sensors. The sensory data are transferred via telephone, Internet, TV, security camera and other wire/wireless or optical communication lines. Each sensor is a self-registering, self-reporting, plug-and-play, portable unit that uses unified electrical and/or optical connectors and operates with IP communication protocol. The variant of the system based just on optical technologies cannot be disabled by artificial high-power radio- or gamma-pulses or sunbursts. Each sensor, being supplied with a battery and monitoring means, can be used as a separate portable unit. Military personnel, police officers, firefighters, miners, rescue teams, and nuclear power plant personnel may individually use these sensors. Terminals may be supplied with sensors essential for that specific location. A miniature "universal" optical gas sensor for specific applications in life support and monitoring systems was designed and tested. The sensor is based on the physics of absorption and/or luminescence spectroscopy. It can operate at high pressures and elevated temperatures, such as in professional and military diving equipment, submarines, underground shelters, mines, command stations, aircraft, space shuttles, etc. To enable this capability, the multiple light emitters, detectors and data processing electronics are located within a specially protected chamber.

Variability, drivers, and effects of atmospheric nitrogen inputs across an urban area: Emerging patterns among human activities, the atmosphere, and soils.

PubMed

Decina, Stephen M; Templer, Pamela H; Hutyra, Lucy R; Gately, Conor K; Rao, Preeti

2017-12-31

Atmospheric deposition of nitrogen (N) is a major input of N to the biosphere and is elevated beyond preindustrial levels throughout many ecosystems. Deposition monitoring networks in the United States generally avoid urban areas in order to capture regional patterns of N deposition, and studies measuring N deposition in cities usually include only one or two urban sites in an urban-rural comparison or as an anchor along an urban-to-rural gradient. Describing patterns and drivers of atmospheric N inputs is crucial for understanding the effects of N deposition; however, little is known about the variability and drivers of atmospheric N inputs or their effects on soil biogeochemistry within urban ecosystems. We measured rates of canopy throughfall N as a measure of atmospheric N inputs, as well as soil net N mineralization and nitrification, soil solution N, and soil respiration at 15 sites across the greater Boston, Massachusetts area. Rates of throughfall N are 8.70±0.68kgNha -1 yr -1 , vary 3.5-fold across sites, and are positively correlated with rates of local vehicle N emissions. Ammonium (NH 4 + ) composes 69.9±2.2% of inorganic throughfall N inputs and is highest in late spring, suggesting a contribution from local fertilizer inputs. Soil solution NO 3 - is positively correlated with throughfall NO 3 - inputs. In contrast, soil solution NH 4 + , net N mineralization, nitrification, and soil respiration are not correlated with rates of throughfall N inputs. Rather, these processes are correlated with soil properties such as soil organic matter. Our results demonstrate high variability in rates of urban throughfall N inputs, correlation of throughfall N inputs with local vehicle N emissions, and a decoupling of urban soil biogeochemistry and throughfall N inputs. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying the main sediment sources in agricultural landscapes of Southern Brazil cultivated with conventional and conservation practices

NASA Astrophysics Data System (ADS)

Evrard, Olivier; Le Gall, Marion; Tiecher, Tales; Gomes Minella, Jean Paolo; Laceby, J. Patrick; Ayrault, Sophie

2017-04-01

Agricultural expansion that occurred in the 1960s in Southern Brazil significantly increased soil erosion and sediment supply to the river networks. To limit the deleterious impacts of soil erosion, conservation practices were progressively implemented in the 1990s, including the direct sowing of crops on a soil densely covered with plant residues, contour farming, the installation of ponds to trap sediment in the landscape and the use of crop rotations. However, there remains a lack of observational data to investigate the impact of these conservation practices on soil erosion and sediment supply. This data is crucial to protect soil resources and maintain the sustainability of food production systems in this region of the world characterized by a rapidly increasing population. Accordingly, sediment sources were investigated in the Guaporé catchment (2,032 km2) representative of the cultivated environments found in this part of the world. In the upper catchment, the landscape is characterized by gentle slopes and deep soils (Ferralsols, Nitisols) corresponding to the edge of the basaltic plateau. Soybean, corn and wheat under direct sowing are the main crops in this area. In contrast, steep and shallow soils (Luvisols, Acrisols, Leptosols) highly connected to the rivers are found in the lower catchment, where tobacco and corn fields are cultivated with conventional ploughing. These soil types were characterized by elemental geochemistry and 87Sr/86Sr ratios. Sediment sources were then modelled using the optimal suite of properties (87Sr/86Sr ratios, K, Ti, Co, As, Ba, and Pb). The results demonstrate that sediment collected at the catchment outlet during two hydrological years (2012-2014) mainly originated from downstream soils (Luvisols, Acrisols, Leptosols; 92±3%), with this proportion remaining stable throughout the monitoring period. This research indicates that conservation practices implemented in the upper catchment are effective and that similar methods should be applied to downstream soils in order to conserve soil resources and limit the degradation of freshwater environments.

Modelling study of soil C, N and pH response to air pollution and climate change using European LTER site observations.

PubMed

Holmberg, Maria; Aherne, Julian; Austnes, Kari; Beloica, Jelena; De Marco, Alessandra; Dirnböck, Thomas; Fornasier, Maria Francesca; Goergen, Klaus; Futter, Martyn; Lindroos, Antti-Jussi; Krám, Pavel; Neirynck, Johan; Nieminen, Tiina Maileena; Pecka, Tomasz; Posch, Maximilian; Pröll, Gisela; Rowe, Ed C; Scheuschner, Thomas; Schlutow, Angela; Valinia, Salar; Forsius, Martin

2018-05-31

Current climate warming is expected to continue in coming decades, whereas high N deposition may stabilize, in contrast to the clear decrease in S deposition. These pressures have distinctive regional patterns and their resulting impact on soil conditions is modified by local site characteristics. We have applied the VSD+ soil dynamic model to study impacts of deposition and climate change on soil properties, using MetHyd and GrowUp as pre-processors to provide input to VSD+. The single-layer soil model VSD+ accounts for processes of organic C and N turnover, as well as charge and mass balances of elements, cation exchange and base cation weathering. We calibrated VSD+ at 26 ecosystem study sites throughout Europe using observed conditions, and simulated key soil properties: soil solution pH (pH), soil base saturation (BS) and soil organic carbon and nitrogen ratio (C:N) under projected deposition of N and S, and climate warming until 2100. The sites are forested, located in the Mediterranean, forested alpine, Atlantic, continental and boreal regions. They represent the long-term ecological research (LTER) Europe network, including sites of the ICP Forests and ICP Integrated Monitoring (IM) programmes under the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP), providing high quality long-term data on ecosystem response. Simulated future soil conditions improved under projected decrease in deposition and current climate conditions: higher pH, BS and C:N at 21, 16 and 12 of the sites, respectively. When climate change was included in the scenario analysis, the variability of the results increased. Climate warming resulted in higher simulated pH in most cases, and higher BS and C:N in roughly half of the cases. Especially the increase in C:N was more marked with climate warming. The study illustrates the value of LTER sites for applying models to predict soil responses to multiple environmental changes. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS

NASA Astrophysics Data System (ADS)

Tobin, Kenneth J.; Torres, Roberto; Crow, Wade T.; Bennett, Marvin E.

2017-09-01

This study applied the exponential filter to produce an estimate of root-zone soil moisture (RZSM). Four types of microwave-based, surface satellite soil moisture were used. The core remotely sensed data for this study came from NASA's long-lasting AMSR-E mission. Additionally, three other products were obtained from the European Space Agency Climate Change Initiative (CCI). These datasets were blended based on all available satellite observations (CCI-active, CCI-passive, and CCI-combined). All of these products were 0.25° and taken daily. We applied the filter to produce a soil moisture index (SWI) that others have successfully used to estimate RZSM. The only unknown in this approach was the characteristic time of soil moisture variation (T). We examined five different eras (1997-2002; 2002-2005; 2005-2008; 2008-2011; 2011-2014) that represented periods with different satellite data sensors. SWI values were compared with in situ soil moisture data from the International Soil Moisture Network at a depth ranging from 20 to 25 cm. Selected networks included the US Department of Energy Atmospheric Radiation Measurement (ARM) program (25 cm), Soil Climate Analysis Network (SCAN; 20.32 cm), SNOwpack TELemetry (SNOTEL; 20.32 cm), and the US Climate Reference Network (USCRN; 20 cm). We selected in situ stations that had reasonable completeness. These datasets were used to filter out periods with freezing temperatures and rainfall using data from the Parameter elevation Regression on Independent Slopes Model (PRISM). Additionally, we only examined sites where surface and root-zone soil moisture had a reasonably high lagged r value (r > 0. 5). The unknown T value was constrained based on two approaches: optimization of root mean square error (RMSE) and calculation based on the normalized difference vegetation index (NDVI) value. Both approaches yielded comparable results; although, as to be expected, the optimization approach generally outperformed NDVI-based estimates. The best results were noted at stations that had an absolute bias within 10 %. SWI estimates were more impacted by the in situ network than the surface satellite product used to drive the exponential filter. The average Nash-Sutcliffe coefficients (NSs) for ARM ranged from -0. 1 to 0.3 and were similar to the results obtained from the USCRN network (0.2-0.3). NS values from the SCAN and SNOTEL networks were slightly higher (0.1-0.5). These results indicated that this approach had some skill in providing an estimate of RZSM. In terms of RMSE (in volumetric soil moisture), ARM values actually outperformed those from other networks (0.02-0.04). SCAN and USCRN RMSE average values ranged from 0.04 to 0.06 and SNOTEL average RMSE values were higher (0.05-0.07). These values were close to 0.04, which is the baseline value for accuracy designated for many satellite soil moisture missions.

Monitoring Soil Bacteria with Community-Level Physiological Profiles Using Biolog™ ECO-Plates in the Republic of Tatarstan (Russia)

NASA Astrophysics Data System (ADS)

Galieva, G. Sh; Gilmutdinova, I. M.; Fomin, V. P.; Selivanovskaya, S. Yu; Galitskaya, P. Yu

2018-01-01

Conservation of soil fertility is one of the most important tasks of the present time. As microorganisms are among the key factors in forming soil fertility, monitoring their state in natural and anthropogenically changed soils is an important component of compulsory environmental monitoring. Modern methods make it possible to evaluate the diversity and the functions of soil microorganisms, however, unfortunately, not all the soils are analyzed with their help up to the present moment. The present investigation is aimed to evaluate the functional diversity of five natural soil samples in the Republic of Tatarstan (belonging to sod-podzol, sod-carbonate, alluvial, and gray types) using the method of Biolog EcoPlate according to the index of average well color development, alpha-biodiversiry Shannon index (H), amount of substrates consumed ®, and strategy of consumption of various carbon substrate groups. It was shown that the highest AWCD index was found in sample No 3 - alluvial soil type (3.159±0.460), the lowest one - in sample No 5 - gray soil type (0.572±0.230). Correlation of biological activity of microorganisms with organic matter content in soil was shown.

[Application of simulated annealing method and neural network on optimizing soil sampling schemes based on road distribution].

PubMed

Han, Zong-wei; Huang, Wei; Luo, Yun; Zhang, Chun-di; Qi, Da-cheng

2015-03-01

Taking the soil organic matter in eastern Zhongxiang County, Hubei Province, as a research object, thirteen sample sets from different regions were arranged surrounding the road network, the spatial configuration of which was optimized by the simulated annealing approach. The topographic factors of these thirteen sample sets, including slope, plane curvature, profile curvature, topographic wetness index, stream power index and sediment transport index, were extracted by the terrain analysis. Based on the results of optimization, a multiple linear regression model with topographic factors as independent variables was built. At the same time, a multilayer perception model on the basis of neural network approach was implemented. The comparison between these two models was carried out then. The results revealed that the proposed approach was practicable in optimizing soil sampling scheme. The optimal configuration was capable of gaining soil-landscape knowledge exactly, and the accuracy of optimal configuration was better than that of original samples. This study designed a sampling configuration to study the soil attribute distribution by referring to the spatial layout of road network, historical samples, and digital elevation data, which provided an effective means as well as a theoretical basis for determining the sampling configuration and displaying spatial distribution of soil organic matter with low cost and high efficiency.

Soil geohazard mapping for improved asset management of UK local roads

NASA Astrophysics Data System (ADS)

Pritchard, O. G.; Hallett, S. H.; Farewell, T. S.

2015-09-01

Unclassified roads comprise 60 % of the road network in the United Kingdom (UK). The resilience of this locally important network is declining. It is considered by the Institution of Civil Engineers to be "at risk" and is ranked 26th in the world. Many factors contribute to the degradation and ultimate failure of particular road sections. However, several UK local authorities have identified that in drought conditions, road sections founded upon shrink-swell susceptible clay soils undergo significant deterioration compared with sections on non-susceptible soils. This arises from the local road network having little, if any, structural foundations. Consequently, droughts in East Anglia have resulted in millions of pounds of damage, leading authorities to seek emergency governmental funding. This paper assesses the use of soil-related geohazard assessments in providing soil-informed maintenance strategies for the asset management of the locally important road network of the UK. A case study draws upon the UK administrative county of Lincolnshire, where road assessment data have been analysed against mapped clay-subsidence risk. This reveals a statistically significant relationship between road condition and susceptible clay soils. Furthermore, incorporation of UKCP09 future climate projections within the geohazard models has highlighted roads likely to be at future risk of clay-related subsidence.

Soil geohazard mapping for improved asset management of UK local roads

NASA Astrophysics Data System (ADS)

Pritchard, O. G.; Hallett, S. H.; Farewell, T. S.

2015-05-01

Unclassified roads comprise 60% of the road network in the United Kingdom (UK). The resilience of this locally important network is declining. It is considered by the Institution of Civil Engineers to be "at risk" and is ranked 26th in the world. Many factors contribute to the degradation and ultimate failure of particular road sections. However, several UK local authorities have identified that in drought conditions, road sections founded upon shrink/swell susceptible clay soils undergo significant deterioration compared with sections on non-susceptible soils. This arises from the local road network having little, if any structural foundations. Consequently, droughts in East Anglia have resulted in millions of pounds of damage, leading authorities to seek emergency governmental funding. This paper assesses the use of soil-related geohazard assessments in providing soil-informed maintenance strategies for the asset management of the locally important road network of the UK. A case study draws upon the UK administrative county of Lincolnshire, where road assessment data have been analysed against mapped clay-subsidence risk. This reveals a statistically significant relationship between road condition and susceptible clay soils. Furthermore, incorporation of UKCP09 future climate projections within the geohazard models has highlighted roads likely to be at future risk of clay-related subsidence.

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.

Wireless sensor networks to assess the impacts of global change in Sierra Nevada (Spain) mountains

NASA Astrophysics Data System (ADS)

Sánchez-Cano, Francisco M.; Bonet-García, Francisco J.; Pérez-Luque, Antonio J.; Suárez-Muñoz, María

2017-04-01

Sierra Nevada Global Change Observatory (southern Spain) aims to improve the ability of ecosystems to address the impacts of global change. To this end, a monitoring program has been implemented based on the collection of long time series on a multitude of biophysical variables. This initiative is part of the Long Term Ecological Research network and is connected to similar ones at national and international level. One of the specific objectives of this LTER site is to improve understanding of the relationships between abiotic factors and ecosystem functioning / structure. Wireless sensor networks are a key instrument for achieving this aim. This contribution describes the design and management of a sensor network that is intended to monitor several biophysical variables with high temporal and spatial resolution in Quercus pyrenaica forests located in this mountain region. The following solution has been adopted in order to obtain the observational data (physical and biological variables). The biological variables will be monitored by PAR sensors (photosynthetically active radiation), and the physical variables will be acquired by a meteorological station and a sensor network composed of temperature and soil moisture sensors, as well as air temperature and humidity ones. To complete the monitoring of the biological variables, a NDVI (Normalized Difference Vegetation Index) camera will be deployed focusing to a Quercus pyrenaica forest from the opposite slope. It should be noted that all monitoring systems exposed will be powered by solar energy. The management of the sensor network covers the deployment of more than 100 sensors, guaranteeing both remote accessibility and reliability of the data. The chosen solution is provided by the company Adevice whose ONE-GO communication system ensures a consistent and efficient sending of those values read by the different sensors towards a central point, from where the information (RAW data) is accessible through WiFi/3G. RAW data is dumped daily in our data center for further processing with the open source software Get-IT. Get-IT was developed by the CNR (National Research Council of Italy) in the context of the RITMARE Flagship Project and LifeWatch Italy in order to combine geographic information with observational data by coupling GeoNode with SOS implementation by 52° North. This solution conforms to our requirements for two reasons, the first is that it provides data persistence, metadata editing and data visualisation tools. The second is that it is the solution adopted by LTER, platform previously mentioned in which we are integrated. This research has been funded by eLTER (Integrated European Long-Term Ecosystem & Socio-Ecological Research Infrastructure) Horizon 2020 EU project, and Sierra Nevada Global Change Observatory (LTER-site).

Sampling history and 2009--2010 results for pesticides and inorganic constituents monitored by the Lake Wales Ridge Groundwater Network, central Florida

USGS Publications Warehouse

Choquette, Anne F.; Freiwald, R. Scott; Kraft, Carol L.

2012-01-01

The Lake Wales Ridge Monitoring (LWRM) Network was established to provide a long-term record of water quality of the surficial aquifer in one of the principal citrus-production areas of Florida. This region is underlain by sandy soils that contain minimal organic matter and are highly vulnerable to leaching of chemicals into the subsurface. This report documents the 1989 through May 2010 sampling history of the LWRM Network and summarizes monitoring results for 38 Network wells that were sampled during the period January 2009 through May 2010. During 1989 through May 2010, the Network’s citrus land-use wells were sampled intermittently to 1999, quarterly from April 1999 to October 2009, and thereafter quarterly to semiannually. The water-quality summaries in this report focus on the period January 2009 through May 2010, during which the Network’s citrus land-use wells were sampled six times and the non-citrus land-use wells were sampled two times. Within the citrus land-use wells sampled, a total of 13 pesticide compounds (8 parent pesticides and 5 degradates) were detected of the 37 pesticide compounds analyzed during this period. The most frequently detected compounds included demethyl norflurazon (83 percent of wells), norflurazon (79 percent), aldicarb sulfoxide (41 percent), aldicarb sulfone (38 percent), imidacloprid (38 percent), and diuron (28 percent). Agrichemical concentrations in samples from the citrus land-use wells during the 2009 through May 2010 period exceeded Federal drinking-water standards (maximum contaminant levels, MCLs) in 1.5 to 24 percent of samples for aldicarb and its degradates (sulfone and sulfoxide), and in 68 percent of the samples for nitrate. Florida statutes restrict the distance of aldicarb applications to drinking-water wells; however, these statutes do not apply to monitoring wells. Health-screening benchmark levels that identify unregulated chemicals of potential concern were exceeded for norflurazon and diuron in 29 and 7 percent, respectively, of the 2009–2010 samples. A comparison of agrichemical land-use effects on groundwater quality, determined on the basis of samples from LWRM Network wells in citrus and in non-citrus land-use areas, indicated significantly higher (p<0.05) concentrations of inorganic constituents in samples from citrus land-use areas compared to samples from non-citrus areas. These inorganic constituents include calcium, magnesium, chloride, sulfate, potassium, nitrate, aluminum, manganese, strontium, and total nitrogen, and also specific conductance, an indicator of total dissolved solutes in water. In addition to land use, including irrigation, site differences such as soils and groundwater reduction/oxidation conditions might have contributed to the differences in some of these constituents. Pesticide detections were primarily restricted to the citrus land-use wells, where 22 of 23 wells yielded pesticide detections, with a median of four detected pesticide compounds per well. For the non-citrus land-use wells, typically surrounded by mixed land use including developed and undeveloped land, one of the eight sampled wells yielded pesticide detections consisting of norflurazon and its degradate, and the source(s) of these detections might have been active or recently active citrus orchards in the vicinity of this well. Results from the LWRM Network during the 1989 through May 2010 period have provided early warning of chemicals prone to leaching, guidance for developing or modifying chemical usage practices to minimize impacts to groundwater, and a mechanism for prioritizing State sampling of domestic wells to assure safe drinking-water supplies. Given the typically long time period (years to tens of years or longer) required to remove chemical contamination once it enters the groundwater system, groundwater monitoring is important to protect drinking-water sources as well as the numerous lakes in this region, which are closely connected with the surficial aquifer. Long-term monitoring of the LWRM Network is planned to continue providing early warning of potential for groundwater contamination, and to assess spatial and temporal trends in water quality resulting from changes in pesticide-use patterns and in land use.

Using Satellite Data and Land Surface Models to Monitor and Forecast Drought Conditions in Africa and Middle East

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Shukla, S.; Getirana, A.; Peters-Lidard, C. D.; Kumar, S.; McNally, A.; Zaitchik, B. F.; Badr, H. S.; Funk, C. C.; Koster, R. D.; Narapusetty, B.; Jung, H. C.; Roningen, J. M.

2017-12-01

Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. In addition, these regions typically have sparse ground-based data networks, where sometimes remotely sensed observations may be the only data available. Long-term satellite records can help with determining historic and current drought conditions. In recent years, several new satellites have come on-line that monitor different hydrological variables, including soil moisture and terrestrial water storage. Though these recent data records may be considered too short for the use in identifying major droughts, they do provide additional information that can better characterize where water deficits may occur. We utilize recent satellite data records of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) and the European Space Agency's Advanced Scatterometer (ASCAT) soil moisture retrievals. Combining these records with land surface models (LSMs), NASA's Catchment and the Noah Multi-Physics (MP), is aimed at improving the land model states and initialization for seasonal drought forecasts. The LSMs' total runoff is routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics, which can provide an additional means of validation against in situ streamflow data. The NASA Land Information System (LIS) software framework drives the LSMs and HyMAP and also supports the capability to assimilate these satellite retrievals, such as soil moisture and TWS. The LSMs are driven for 30+ years with NASA's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS/UCSB Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall dataset. The seasonal water deficit forecasts are generated using downscaled and bias-corrected versions of NASA's Goddard Earth Observing System Model (GEOS-5), and NOAA's Climate Forecast System (CFSv2) forecasts. These combined satellite and model records and forecasts are intended for use in different decision support tools, like the Famine Early Warning Systems Network (FEWS NET) and the Middle East-North Africa (MENA) Regional Drought Management System, for aiding and forecasting in water and food insecure regions.

Arbuscular-mycorrhizal networks inhibit Eucalyptus tetrodonta seedlings in rain forest soil microcosms.

PubMed

Janos, David P; Scott, John; Aristizábal, Catalina; Bowman, David M J S

2013-01-01

Eucalyptus tetrodonta, a co-dominant tree species of tropical, northern Australian savannas, does not invade adjacent monsoon rain forest unless the forest is burnt intensely. Such facilitation by fire of seedling establishment is known as the "ashbed effect." Because the ashbed effect might involve disruption of common mycorrhizal networks, we hypothesized that in the absence of fire, intact rain forest arbuscular mycorrhizal (AM) networks inhibit E. tetrodonta seedlings. Although arbuscular mycorrhizas predominate in the rain forest, common tree species of the northern Australian savannas (including adult E. tetrodonta) host ectomycorrhizas. To test our hypothesis, we grew E. tetrodonta and Ceiba pentandra (an AM-responsive species used to confirm treatments) separately in microcosms of ambient or methyl-bromide fumigated rain forest soil with or without severing potential mycorrhizal fungus connections to an AM nurse plant, Litsea glutinosa. As expected, C. pentandra formed mycorrhizas in all treatments but had the most root colonization and grew fastest in ambient soil. E. tetrodonta seedlings also formed AM in all treatments, but severing hyphae in fumigated soil produced the least colonization and the best growth. Three of ten E. tetrodonta seedlings in ambient soil with intact network hyphae died. Because foliar chlorosis was symptomatic of iron deficiency, after 130 days we began to fertilize half the E. tetrodonta seedlings in ambient soil with an iron solution. Iron fertilization completely remedied chlorosis and stimulated leaf growth. Our microcosm results suggest that in intact rain forest, common AM networks mediate belowground competition and AM fungi may exacerbate iron deficiency, thereby enhancing resistance to E. tetrodonta invasion. Common AM networks-previously unrecognized as contributors to the ashbed effect-probably help to maintain the rain forest-savanna boundary.

Spatial and monthly trends in speciated fine particle concentration in the United States

NASA Astrophysics Data System (ADS)

Malm, William C.; Schichtel, Bret A.; Pitchford, Marc L.; Ashbaugh, Lowell L.; Eldred, Robert A.

2004-02-01

In the spring of 1985 an interagency consortium of federal land management agencies and the Environmental Protection Agency established the Interagency Monitoring of Protected Visual Environments (IMPROVE) network to assess visibility and aerosol monitoring for the purpose of tracking spatial and temporal trends of visibility and visibility-impairing particles in rural areas. The program was initiated with 20 monitoring sites and was expanded to 165 sites between 2000 and 2003. This paper reports on fine aerosol data collected in the year 2001 at 143 sites. The major fine (dp < 2.5 μm) particle aerosol species, sulfates, nitrates, organics, light-absorbing carbon, and wind-blown dust, and coarse gravimetric mass are monitored, and at some sites, light scattering and/or extinction are measured. Sulfates, carbon, and crustal material are responsible for most of the fine mass at the majority of locations throughout the United States, while at sites in southern California and the midwestern United States, nitrates can contribute significantly. In the eastern United States, sulfates contribute between 50 and 60% of the fine mass. Sulfate concentrations tend to be highest in the summer months while organic concentrations can be high in the spring, summer, or fall seasons, depending upon fire-related emissions. However, at the two urban sites, Phoenix, Arizona, and Puget Sound, Washington, organics peak during the winter months. Nitrate concentrations also tend to be highest during the winter months. During the spring months in many areas of the western United States, fine soil can contribute as much as 40% of fine mass. The temporal changes in soil concentration that occur simultaneously over much of the western United States including the Rocky Mountain region suggest a large source region, possibly long-range transport of Asian dust.

A conceptual ground-water-quality monitoring network for San Fernando Valley, California

USGS Publications Warehouse

Setmire, J.G.

1985-01-01

A conceptual groundwater-quality monitoring network was developed for San Fernando Valley to provide the California State Water Resources Control Board with an integrated, basinwide control system to monitor the quality of groundwater. The geology, occurrence and movement of groundwater, land use, background water quality, and potential sources of pollution were described and then considered in designing the conceptual monitoring network. The network was designed to monitor major known and potential point and nonpoint sources of groundwater contamination over time. The network is composed of 291 sites where wells are needed to define the groundwater quality. The ideal network includes four specific-purpose networks to monitor (1) ambient water quality, (2) nonpoint sources of pollution, (3) point sources of pollution, and (4) line sources of pollution. (USGS)

Terrestrial origin of bacterial communities in complex boreal freshwater networks.

PubMed

Ruiz-González, Clara; Niño-García, Juan Pablo; Del Giorgio, Paul A

2015-08-25

Bacteria inhabiting boreal freshwaters are part of metacommunities where local assemblages are often linked by the flow of water in the landscape, yet the resulting spatial structure and the boundaries of the network metacommunity have never been explored. Here, we reconstruct the spatial structure of the bacterial metacommunity in a complex boreal aquatic network by determining the taxonomic composition of bacterial communities along the entire terrestrial/aquatic continuum, including soil and soilwaters, headwater streams, large rivers and lakes. We show that the network metacommunity has a directional spatial structure driven by a common terrestrial origin of aquatic communities, which are numerically dominated by taxa recruited from soils. Local community assembly is driven by variations along the hydrological continuum in the balance between mass effects and species sorting of terrestrial taxa, and seems further influenced by priority effects related to the spatial sequence of entry of soil bacteria into the network. © 2015 John Wiley & Sons Ltd/CNRS.

Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture

NASA Technical Reports Server (NTRS)

Bolten, John; Crow, Wade

2012-01-01

The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Saltwater intrusion monitoring in Florida

USGS Publications Warehouse

Prinos, Scott T.

2016-01-01

Florida's communities are largely dependent on freshwater from groundwater aquifers. Existing saltwater in the aquifers, or seawater that intrudes parts of the aquifers that were fresh, can make the water unusable without additional processing. The quality of Florida's saltwater intrusion monitoring networks varies. In Miami-Dade and Broward Counties, for example, there is a well-designed network with recently constructed short open-interval monitoring wells that bracket the saltwater interface in the Biscayne aquifer. Geochemical analyses of water samples from the network help scientists evaluate pathways of saltwater intrusion and movement of the saltwater interface. Geophysical measurements, collected in these counties, aid the mapping of the saltwater interface and the design of monitoring networks. In comparison, deficiencies in the Collier County monitoring network include the positioning of monitoring wells, reliance on wells with long open intervals that when sampled might provide questionable results, and the inability of existing analyses to differentiate between multiple pathways of saltwater intrusion. A state-wide saltwater intrusion monitoring network is being planned; the planned network could improve saltwater intrusion monitoring by adopting the applicable strategies of the networks of Miami-Dade and Broward Counties, and by addressing deficiencies such as those described for the Collier County network.

Optimization of water-level monitoring networks in the eastern Snake River Plain aquifer using a kriging-based genetic algorithm method

USGS Publications Warehouse

Fisher, Jason C.

2013-01-01

Long-term groundwater monitoring networks can provide essential information for the planning and management of water resources. Budget constraints in water resource management agencies often mean a reduction in the number of observation wells included in a monitoring network. A network design tool, distributed as an R package, was developed to determine which wells to exclude from a monitoring network because they add little or no beneficial information. A kriging-based genetic algorithm method was used to optimize the monitoring network. The algorithm was used to find the set of wells whose removal leads to the smallest increase in the weighted sum of the (1) mean standard error at all nodes in the kriging grid where the water table is estimated, (2) root-mean-squared-error between the measured and estimated water-level elevation at the removed sites, (3) mean standard deviation of measurements across time at the removed sites, and (4) mean measurement error of wells in the reduced network. The solution to the optimization problem (the best wells to retain in the monitoring network) depends on the total number of wells removed; this number is a management decision. The network design tool was applied to optimize two observation well networks monitoring the water table of the eastern Snake River Plain aquifer, Idaho; these networks include the 2008 Federal-State Cooperative water-level monitoring network (Co-op network) with 166 observation wells, and the 2008 U.S. Geological Survey-Idaho National Laboratory water-level monitoring network (USGS-INL network) with 171 wells. Each water-level monitoring network was optimized five times: by removing (1) 10, (2) 20, (3) 40, (4) 60, and (5) 80 observation wells from the original network. An examination of the trade-offs associated with changes in the number of wells to remove indicates that 20 wells can be removed from the Co-op network with a relatively small degradation of the estimated water table map, and 40 wells can be removed from the USGS-INL network before the water table map degradation accelerates. The optimal network designs indicate the robustness of the network design tool. Observation wells were removed from high well-density areas of the network while retaining the spatial pattern of the existing water-table map.

Diagnosing soil moisture anomalies and neglected soil moisture source/sink processes via a thermal infrared-based two-source energy balance model

USDA-ARS?s Scientific Manuscript database

Atmospheric processes, especially those that occur in the surface and boundary layer, are significantly impacted by soil moisture (SM). Due to the observational gaps in the ground-based monitoring of SM, methodologies have been developed to monitor SM from satellite platforms. While many have focuse...

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.

Geochemical evidence for a magmatic CO2 degassing event at Mammoth Mountain, California, September-December 1997

USGS Publications Warehouse

McGee, K.A.; Gerlach, T.M.; Kessler, R.; Doukas, M.P.

2000-01-01

Recent time series soil CO2 concentration data from monitoring stations in the vicinity of Mammoth Mountain, California, reveal strong evidence for a magmatic degassing event during the fall of 1997 lasting more than 2 months. Two sensors at Horseshoe Lake first recorded the episode on September 23, 1997, followed 10 days later by a sensor on the north flank of Mammoth Mountain. Direct degassing from shallow intruding magma seems an implausible cause of the degassing event, since the gas released at Horseshoe Lake continued to be cold and barren of other magmatic gases, except for He. We suggest that an increase in compressional strain on the area south of Mammoth Mountain driven by movement of major fault blocks in Long Valley caldera may have triggered an episode of increased degassing by squeezing additional accumulated CO2 from a shallow gas reservoir to the surface along faults and other structures where it could be detected by the CO2 monitoring network. Recharge of the gas reservoir by CO2 emanating from the deep intrusions that probably triggered deep long-period earthquakes may also have contributed to the degassing event. The nature of CO2 discharge at the soil-air interface is influenced by the porous character of High Sierra soils and by meteorological processes. Solar insolation is the primary source of energy for the Earth atmosphere and plays a significant role in most diurnal processes at the Earth surface. Data from this study suggest that external forcing due largely to local orographic winds influences the fine structure of the recorded CO2 signals.

Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska

NASA Astrophysics Data System (ADS)

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

1999-01-01

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

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

PubMed

Lagos-Avid, María Paz; Bonilla, Carlos A

2017-03-01

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

Reducing sediment inputs to Scottish streams: a review of the efficacy of soil conservation practices in upland forestry.

PubMed

Carling, P A; Irvine, B J; Hill, A; Wood, M

2001-01-29

The historical process by which a soil conservation strategy has evolved within the UK forestry industry is briefly reviewed. Particular attention is given to the development of practical and effective guidelines to prevent both soil damage and sediment entering water courses. It is concluded that the 'Forest and Water Guidelines', together with other forest industry manuals, largely provide adequate protection for aquatic habitats from pre-afforestation cultivation and from harvesting activities. The problem of soil erosion owing to ploughing of open furrows has largely been obviated by improved drainage network design coupled with the use of vegetated buffer strips and sediment catchpits. Alternative site preparation techniques, such as 'moling' or 'dolloping' of afforestation sites, are now preferred. However, the effects on slope hydrology and the improved soil conservation associated with these methods require quantifying. Additional understanding of effective buffer strip function, for example, on a variety of slope angles, soil types and vegetation associations would be beneficial. The design of forest roads and the associated network of drains, culverts and sediment catchpits is addressed in forestry guidelines. Future potential in this area may involve the use of Geographical Information Systems in the effective design of road networks which minimise adverse effects on slope hydrology. Similarly computer simulation of flow routing might aid in the design of road drain networks. At the more local scale there remains scope for further research aimed at minimising soil disturbance by machinery. Consideration should also be given to the long-term sustainability of the soil structure through second and subsequent crop rotations.

Rock-Eval analysis of French forest soils: the influence of depth, soil and vegetation types on SOC thermal stability and bulk chemistry

NASA Astrophysics Data System (ADS)

Soucemarianadin, Laure; Cécillon, Lauric; Baudin, François; Cecchini, Sébastien; Chenu, Claire; Mériguet, Jacques; Nicolas, Manuel; Savignac, Florence; Barré, Pierre

2017-04-01

Soil organic matter (SOM) is the largest terrestrial carbon pool and SOM degradation has multiple consequences on key ecosystem properties like nutrients cycling, soil emissions of greenhouse gases or carbon sequestration potential. With the strong feedbacks between SOM and climate change, it becomes particularly urgent to develop reliable routine methodologies capable of indicating the turnover time of soil organic carbon (SOC) stocks. Thermal analyses have been used to characterize SOM and among them, Rock-Eval 6 (RE6) analysis of soil has shown promising results in the determination of in-situ SOC biogeochemical stability. This technique combines a phase of pyrolysis followed by a phase of oxidation to provide information on both the SOC bulk chemistry and thermal stability. We analyzed with RE6 a set of 495 soils samples from 102 permanent forest sites of the French national network for the long-term monitoring of forest ecosystems (''RENECOFOR'' network). Along with covering pedoclimatic variability at a national level, these samples include a range of 5 depths up to 1 meter (0-10 cm, 10-20 cm, 20-40 cm, 40-80 cm and 80-100 cm). Using RE6 parameters that were previously shown to be correlated to short-term (hydrogen index, HI; T50 CH pyrolysis) or long-term (T50 CO2 oxidation and HI) SOC persistence, and that characterize SOM bulk chemical composition (oxygen index, OI and HI), we tested the influence of depth (n = 5), soil class (n = 6) and vegetation type (n = 3; deciduous, coniferous-fir, coniferous-pine) on SOM thermal stability and bulk chemistry. Results showed that depth was the dominant discriminating factor, affecting significantly all RE6 parameters. With depth, we observed a decrease of the thermally labile SOC pool and an increase of the thermally stable SOC pool, along with an oxidation and a depletion of hydrogen-rich moieties of the SOC. Soil class and vegetation type had contrasted effects on the RE6 parameters but both affected significantly T50 CO2 oxidation with, for instance, entic Podzols and dystric Cambisols containing relatively more thermally stable SOC in the deepest layer than hypereutric/calcaric Cambisols. Moreover, soils in deciduous plots contained a higher proportion of thermally stable SOC than soils in coniferous plots. This study shows that RE6 analysis constitutes a fast and cost effective way to qualitatively estimate SOM turnover and to discuss its ecosystem drivers. It offers promising prospects towards a quantitative estimation of SOC turnover and the development of RE6-based indicators related to the size of the different SOC kinetic pools.

40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Annual monitoring network plan and periodic network assessment. 58.10 Section 58.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.10 Annual...

40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Annual monitoring network plan and periodic network assessment. 58.10 Section 58.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.10 Annual...

Dust emissions from unpaved roads on the Colorado Plateau

NASA Astrophysics Data System (ADS)

Duniway, M.; Flagg, C.; Belnap, J.

2013-12-01

On the Colorado Plateau, elevated levels of aeolian dust have become a major land management and policy concern due to its influence on climate, weather, terrestrial ecosystem dynamics, landscape development and fertility, melting of snow and ice, air quality, and human health. Most desert soil surfaces are stabilized by plants, rocks, and/or physical or biological soil crusts, but once disturbed, sediment production from these surfaces can increase dramatically. Road development and use is a common surface disturbing activity in the region. The extent and density of roads and road networks is rapidly increasing due to continued energy exploration, infrastructure development, and off-highway recreation activities. Though it is well known that unpaved roads produce dust, the relative contribution of dust from existing roads or the implications of future road development to regional dust loading is unknown. To address this need, we have initiated a multifaceted research effort to evaluating dust emissions from unpaved roads regionally. At 34 sites arranged across various road surfaces and soil textures in southeastern Utah, we are: 1) monitoring dust emissions, local wind conditions, and vehicle traffic and 2) evaluating fugitive dust potential using a portable wind tunnel and measuring road characteristics that affect dust production. We will then 3) develop a GIS-based model that integrates results from 1 & 2 to estimate potential dust contributions from current and future scenarios of regional road development. Passive, horizontal sediment traps were installed at three distances downwind from the road edge. One control trap was placed upwind of the samplers to account for local, non-road dust emissions. An electronic vehicle counter and anemometer were also installed at monitoring sites. Dust samples were collected every three months at fixed heights, 15 cm up to 100 cm above the soil surface, from March 2010 to the present. Threshold friction velocities (TFV), the minimum wind velocity required to initiate erosion, and sediment production were also quantified using a portable wind tunnel at monitoring sites. Additionally, numerous characteristics including gravel cover, particle-size distribution, soil compaction, and loose-erodible material were measured on road surfaces at monitoring sites. Preliminary results suggest that roads are an important regional dust source, as emissions from roads are comparable to non-road, rural sources that are being monitored concurrently. While gravel roads produce more dust per day on average, per vehicle emissions are larger on dirt roads. Dust flux decreases with distance from the road edge on all road types, however this decline is less pronounced on dirt roads. Portable wind tunnel results indicate that TFV is consistently lower on dirt versus gravel roads across all soil types. Fugitive dust flux is generally larger and more variable on dirt roads compared to gravel roads. Initial analyses suggest that several easily measurable road surface characteristics can potentially be used to predict both TFV and sediment production, including: total gravel cover, gravel particle-size classes, clay content, and road compaction. The relation between TFV and total gravel cover in particular appears to be non-linear, with TFV increasing rapidly above ~40% gravel cover.

Monitoring water stable isotopic composition in soils using gas-permeable tubing and infrared laser absorption spectroscopy

NASA Astrophysics Data System (ADS)

Rothfuss, Youri; Vereecken, Harry; Brüggemann, Nicolas

2013-06-01

In soils, the isotopic composition of water (δ2H and δ18O) provides qualitative (e.g., location of the evaporation front) and quantitative (e.g., evaporation flux and root water uptake depths) information. However, the main disadvantage of the isotope methodology is that contrary to other soil state variables that can be monitored over long time periods, δ2H and δ18O are typically analyzed following destructive sampling. Here we present a nondestructive method for monitoring soil liquid water δ2H and δ18O over a wide range of water availability conditions and temperatures by sampling water vapor equilibrated with soil water using gas-permeable polypropylene tubing and a cavity ring-down laser absorption spectrometer. By analyzing water vapor δ2H and δ18O sampled with the tubing from a fine sand for temperatures ranging between 8°C and 24°C, we demonstrate that our new method is capable of monitoring δ2H and δ18O in soils online with high precision and after calibration, also with high accuracy. Our sampling protocol enabled detecting changes of δ2H and δ18O following nonfractionating addition and removal of liquid water and water vapor of different isotopic compositions. Finally, the time needed for the tubing to monitor these changes is compatible with the observed variations of δ2H and δ18O in soils under natural conditions.

Designing a network of critical zone observatories to explore the living skin of the terrestrial Earth

NASA Astrophysics Data System (ADS)

Brantley, Susan L.; McDowell, William H.; Dietrich, William E.; White, Timothy S.; Kumar, Praveen; Anderson, Suzanne P.; Chorover, Jon; Lohse, Kathleen Ann; Bales, Roger C.; Richter, Daniel D.; Grant, Gordon; Gaillardet, Jérôme

2017-12-01

The critical zone (CZ), the dynamic living skin of the Earth, extends from the top of the vegetative canopy through the soil and down to fresh bedrock and the bottom of the groundwater. All humans live in and depend on the CZ. This zone has three co-evolving surfaces: the top of the vegetative canopy, the ground surface, and a deep subsurface below which Earth's materials are unweathered. The network of nine CZ observatories supported by the US National Science Foundation has made advances in three broad areas of CZ research relating to the co-evolving surfaces. First, monitoring has revealed how natural and anthropogenic inputs at the vegetation canopy and ground surface cause subsurface responses in water, regolith structure, minerals, and biotic activity to considerable depths. This response, in turn, impacts aboveground biota and climate. Second, drilling and geophysical imaging now reveal how the deep subsurface of the CZ varies across landscapes, which in turn influences aboveground ecosystems. Third, several new mechanistic models now provide quantitative predictions of the spatial structure of the subsurface of the CZ.Many countries fund critical zone observatories (CZOs) to measure the fluxes of solutes, water, energy, gases, and sediments in the CZ and some relate these observations to the histories of those fluxes recorded in landforms, biota, soils, sediments, and rocks. Each US observatory has succeeded in (i) synthesizing research across disciplines into convergent approaches; (ii) providing long-term measurements to compare across sites; (iii) testing and developing models; (iv) collecting and measuring baseline data for comparison to catastrophic events; (v) stimulating new process-based hypotheses; (vi) catalyzing development of new techniques and instrumentation; (vii) informing the public about the CZ; (viii) mentoring students and teaching about emerging multidisciplinary CZ science; and (ix) discovering new insights about the CZ. Many of these activities can only be accomplished with observatories. Here we review the CZO enterprise in the United States and identify how such observatories could operate in the future as a network designed to generate critical scientific insights. Specifically, we recognize the need for the network to study network-level questions, expand the environments under investigation, accommodate both hypothesis testing and monitoring, and involve more stakeholders. We propose a driving question for future CZ science and a hubs-and-campaigns model to address that question and target the CZ as one unit. Only with such integrative efforts will we learn to steward the life-sustaining critical zone now and into the future.

Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

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

Harden, Jennifer W.; Hugelius, Gustaf; Ahlstrom, Anders

Here, soil organic matter supports the Earth’s ability to sustain terrestrial ecosystems, provide food and fiber, and retain the largest pool of actively cycling carbon (C). Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance land productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerablemore » to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well-established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of soil organic matter and C and their management for sustained production and climate regulation.« less

An Integrated Insight into the Relationship between Soil Microbial Community and Tobacco Bacterial Wilt Disease

PubMed Central

Yang, Hongwu; Li, Juan; Xiao, Yunhua; Gu, Yabing; Liu, Hongwei; Liang, Yili; Liu, Xueduan; Hu, Jin; Meng, Delong; Yin, Huaqun

2017-01-01

The soil microbial communities play an important role in plant health, however, the relationship between the below-ground microbiome and above-ground plant health remains unclear. To reveal such a relationship, we analyzed soil microbial communities through sequencing of 16S rRNA gene amplicons from 15 different tobacco fields with different levels of wilt disease in the central south part of China. We found that plant health was related to the soil microbial diversity as plants may benefit from the diverse microbial communities. Also, those 15 fields were grouped into ‘healthy’ and ‘infected’ samples based upon soil microbial community composition analyses such as unweighted paired-group method with arithmetic means (UPGMA) and principle component analysis, and furthermore, molecular ecological network analysis indicated that some potential plant-beneficial microbial groups, e.g., Bacillus and Actinobacteria could act as network key taxa, thus reducing the chance of plant soil-borne pathogen invasion. In addition, we propose that a more complex soil ecology network may help suppress tobacco wilt, which was also consistent with highly diversity and composition with plant-beneficial microbial groups. This study provides new insights into our understanding the relationship between the soil microbiome and plant health. PMID:29163453

Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

DOE PAGES

Harden, Jennifer W.; Hugelius, Gustaf; Ahlstrom, Anders; ...

2017-10-05

Here, soil organic matter supports the Earth’s ability to sustain terrestrial ecosystems, provide food and fiber, and retain the largest pool of actively cycling carbon (C). Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance land productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerablemore » to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well-established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of soil organic matter and C and their management for sustained production and climate regulation.« less

SBIR Phase II Final Report: Low cost Autonomous NMR and Multi-sensor Soil Monitoring Instrument

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

Walsh, David O.

In this 32-month SBIR Phase 2 program, Vista Clara designed, assembled and successfully tested four new NMR instruments for soil moisture measurement and monitoring: An enhanced performance man-portable Dart NMR logging probe and control unit for rapid, mobile measurement in core holes and 2” PVC access wells; A prototype 4-level Dart NMR monitoring probe and prototype multi-sensor soil monitoring control unit for long-term unattended monitoring of soil moisture and other measurements in-situ; A non-invasive 1m x 1m Discus NMR soil moisture sensor with surface based magnet/coil array for rapid measurement of soil moisture in the top 50 cm of themore » subsurface; A non-invasive, ultra-lightweight Earth’s field surface NMR instrument for non-invasive measurement and mapping of soil moisture in the top 3 meters of the subsurface. The Phase 2 research and development achieved most, but not all of our technical objectives. The single-coil Dart in-situ sensor and control unit were fully developed, demonstrated and successfully commercialized within the Phase 2 period of performance. The multi-level version of the Dart probe was designed, assembled and demonstrated in Phase 2, but its final assembly and testing were delayed until close to the end of the Phase 2 performance period, which limited our opportunities for demonstration in field settings. Likewise, the multi-sensor version of the Dart control unit was designed and assembled, but not in time for it to be deployed for any long-term monitoring demonstrations. The prototype ultra-lightweight surface NMR instrument was developed and demonstrated, and this result will be carried forward into the development of a new flexible surface NMR instrument and commercial product in 2018.« less

The loss of ecosystem services due to land degradation. Integration of mechanistic and probabilistic models in an Ethiopian case study

NASA Astrophysics Data System (ADS)

Cerretelli, Stefania; Poggio, Laura; Gimona, Alessandro; Peressotti, Alessandro; Black, Helaina

2017-04-01

Land and soil degradation are widespread especially in dry and developing countries such as Ethiopia. Land degradation leads to ecosystems services (ESS) degradation, because it causes the depletion and loss of several soil functions. Ethiopia's farmland faces intense degradation due to deforestation, agricultural land expansion, land overexploitation and overgrazing. In this study we modelled the impact of physical factors on ESS degradation, in particular soil erodibility, carbon storage and nutrient retention, in the Ethiopian Great Rift Valley, northwestern of Hawassa. We used models of the Sediment retention/loss, the Nutrient Retention/loss (from the software suite InVEST) and Carbon Storage. To run the models we coupled soil local data (such as soil organic carbon, soil texture) with remote sensing data as input in the parametrization phase, e.g. to derive a land use map, to calculate the aboveground and belowground carbon, the evapotraspiration coefficient and the capacity of vegetation to retain nutrient. We then used spatialised Bayesian Belief Networks (sBBNs) predicting ecosystem services degradation on the basis of the results of the three mechanistic models. The results show i) the importance of mapping of ESS degradation taking into consideration the spatial heterogeneity and the cross-correlations between impacts ii) the fundamental role of remote sensing data in monitoring and modelling in remote, data-poor areas and iii) the important role of spatial BBNs in providing spatially explicit measures of risk and uncertainty. This approach could help decision makers to identify priority areas for intervention in order to reduce land and ecosystem services degradation.

Value of Available Global Soil Moisture Products for Agricultural Monitoring

NASA Astrophysics Data System (ADS)

Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard

2016-04-01

The first operationally derived and publicly distributed global soil moil moisture product was initiated with the launch of the Advanced Scanning Microwave Mission on the NASA's Earth Observing System Aqua satellite (AMSR-E). AMSR-E failed in late 2011, but its legacy is continued by AMSR2, launched in 2012 on the JAXA Global Change Observation Mission-Water (GCOM-W) mission. AMSR is a multi-frequency dual-polarization instrument, where the lowest two frequencies (C- and X-band) were used for soil moisture retrieval. Theoretical research and small-/field-scale airborne campaigns, however, have demonstrated that soil moisture would be best monitored using L-band-based observations. This consequently led to the development and launch of the first L-band-based mission-the ESA's Soil Moisture Ocean Salinity (SMOS) mission (2009). In early 2015 NASA launched the second L-band-based mission, the Soil Moisture Active Passive (SMAP). These satellite-based soil moisture products have been demonstrated to be invaluable sources of information for mapping water stress areas, crop monitoring and yield forecasting. Thus, a number of agricultural agencies routinely utilize and rely on global soil moisture products for improving their decision making activities, determining global crop production and crop prices, identifying food restricted areas, etc. The basic premise of applying soil moisture observations for vegetation monitoring is that the change in soil moisture conditions will precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop condition change. Here this relationship was evaluated across multiple microwave frequencies by examining the lag rank cross-correlation coefficient between the soil moisture observations and the Normalized Difference Vegetation Index (NDVI). A main goal of our analysis is to evaluate and inter-compare the value of the different soil moisture products derived using L-band (SMOS) versus C-/X-band (AMSR2) observations. The soil moisture products analyzed here were derived using the Land Parameter Retrieval Model.

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

PubMed

Qiu, Guo Yu; Zhao, Ming

2010-03-01

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

The Texas Water Observatory: Utilizing Advanced Observing System Design for Understanding Water Resources Sustainability Across Climatic and Geologic Gradients of Texas

NASA Astrophysics Data System (ADS)

Mohanty, B.; Moore, G. W.; Miller, G. R.; Quiring, S. M.; Everett, M. E.; Morgan, C.

2015-12-01

The Texas Water Observatory (TWO) is a new distributed network of field observatories for better understanding of the hydrologic flow in the critical zone (encompassing groundwater, soil water, surface water, and atmospheric water) at various space and time scales. Core sites in the network will begin in Brazos River corridor and expand from there westward. Using many advanced observational platforms and real-time / near-real time sensors, this observatory will monitor high frequency data of water stores and fluxes, critical for understanding and modeling the in the state of Texas and Southern USA. Once implemented, TWO will be positioned to support high-impact water science that is highly relevant to societal needs and serve as a regional resource for better understanding and/or managing agriculture, water resources, ecosystems, biodiversity, disasters, health, energy, and weather/climate. TWO infrastructure will span land uses (cultivation agriculture, range/pasture, forest), landforms (low-relief erosional uplands to depositional lowlands), and across climatic and geologic gradients of Texas to investigate the sensitivity and resilience of fertile soils and the ecosystems they support. Besides developing a network of field water observatory infrastructure/capacity for accounting water flow and storage, TWO will facilitate developing a new generation interdisciplinary water professionals (from various TAMU Colleges) with better understanding and skills for attending to future water challenges of the region. This holistic growth will have great impact on TAMU research enterprise related to water resources, leading to higher federal and state level competitiveness for funding and establishing a center of excellence in the region

Determining the spatial variability of wetland soil bulk density, organic matter, and the conversion factor between organic matter and organic carbon across coastal Louisiana, U.S.A.

USGS Publications Warehouse

Wang, Hongqing; Piazza, Sarai C.; Sharp, Leigh A.; Stagg, Camille L.; Couvillion, Brady R.; Steyer, Gregory D.; McGinnis, Thomas E.

2016-01-01

Soil bulk density (BD), soil organic matter (SOM) content, and a conversion factor between SOM and soil organic carbon (SOC) are often used in estimating SOC sequestration and storage. Spatial variability in BD, SOM, and the SOM–SOC conversion factor affects the ability to accurately estimate SOC sequestration, storage, and the benefits (e.g., land building area and vertical accretion) associated with wetland restoration efforts, such as marsh creation and sediment diversions. There are, however, only a few studies that have examined large-scale spatial variability in BD, SOM, and SOM–SOC conversion factors in coastal wetlands. In this study, soil cores, distributed across the entire coastal Louisiana (approximately 14,667 km2) were used to examine the regional-scale spatial variability in BD, SOM, and the SOM–SOC conversion factor. Soil cores for BD and SOM analyses were collected during 2006–09 from 331 spatially well-distributed sites in the Coastwide Reference Monitoring System network. Soil cores for the SOM–SOC conversion factor analysis were collected from 15 sites across coastal Louisiana during 2006–07. Results of a split-plot analysis of variance with incomplete block design indicated that BD and SOM varied significantly at a landscape level, defined by both hydrologic basins and vegetation types. Vertically, BD and SOM varied significantly among different vegetation types. The SOM–SOC conversion factor also varied significantly at the landscape level. This study provides critical information for the assessment of the role of coastal wetlands in large regional carbon budgets and the estimation of carbon credits from coastal restoration.

An assessment of the risk of element contamination of urban and industrial areas using Taraxacum sect. Ruderalia as a bioindicator.

PubMed

Fröhlichová, Alena; Száková, Jiřina; Najmanová, Jana; Tlustoš, Pavel

2018-02-19

Central Bohemia (Czech Republic) has highly developed industry and a dense rail network. Here, we aimed to determine the content of risk elements in dandelion plants (Taraxacum sect. Ruderalia) growing near train stations, industrial enterprises, and in the city parks of 16 cities in the Central Bohemian region. The highest element contents in the soils were found in industrial areas affected by the historical mining and smelting activities; contemporary industry showed no substantial effect on the soil element contents. The median values of element contents (As, Be, Cd, Co, Cr, Cu, Ni, Pb, and Zn) at the railway station sites were the highest among the monitored sites, where the differences between park and station sites were significant for Be, Co, and Zn. Although the intensity of the traffic at the individual stations differed, we found that long-term regular traffic enhanced the element contents in the soils and, subsequently, in the plants. For Cd, Co, Cr, Cu, Pb, V, and Zn, the highest median element contents were found in plant roots, regardless of the sampling site. For Cd and Zn, the contents in leaves were higher than in the inflorescences, and the opposite pattern was recorded for Co and Cu. As and Be were distributed equally among the plant parts. Among the sampling sites, the As, Be, Cd, Zn, and Pb contents in the plant roots tended to have higher median values at the station sites, confirming the results of our soil analyses. We detected a fairly good correlation between soil and plant content for cadmium, regardless of the sampling site, soil element content, or analyzed part of the plant. Thus, we propose that dandelion is a suitable bioindicator of cadmium pollution of soil.

High-Resolution Monitoring of Soil Water Dynamics in a Vegetated Hillslope by Active Distributed Temperature Sensing

NASA Astrophysics Data System (ADS)

Ciocca, F.; Krause, S.; Blaen, P.; Hannah, D. M.; Chalari, A.; Mondanos, M.; Abesser, C.

2016-12-01

Water and thermal conditions in the shallow vadose zone can be very complex and dynamic across a range of spatiotemporal scales. The efficient analysis of such dynamics requires technologies capable of precise and high-resolution monitoring of soil temperature and moisture across multiple scales. Optical fibre distributed temperature sensors (DTS) allows for precise temperature measurements at high spatio-temporal resolution, over several kilometres of optical fibre cable. In addition to passive temperature monitoring, hybrid optical cables with embedded metal conductors can be electrically heated and allow for distributed heat pulses. Such Active-DTS technique involves the analysis of temperatures during both heating and cooling phases of an optical fibre cable buried in the soil in order to provide distributed soil moisture estimates. In summer 2015, three loops of a 500m hybrid-optical cable have been deployed at 10cm, 25cm and 40cm depths along a hillslope with juvenile forest. Active-DTS surveys have been conducted with the aim to: (i) monitor the post-installation soil settling around the cable; (ii) analyse different heating strategies (intensity, duration) of the cable; (iii) establish a method for inferring soil moisture from Active-DTS results and validate with independent soil moisture readings from point probes; (iv) monitor the soil moisture response to short forcing events such as storms and artificial irrigation. Results from the surveys will be presented, and first assumptions on how the obtained soil water dynamics can be associated to specific triggers such as precipitation, evapotranspiration, soil inclination, will be discussed. This research is part of the British National Environmental Research Council (NERC) funded Distributed intelligent Heat Pulse System (DiHPS) project and is realised in the context of the Free Air Carbon Enrichment (FACE) experiment, in collaboration with the Birmingham Institute of Forest Research (BIFoR).

Improving Alpine Streamflow Simulations by Incorporation of Evapotranspiration and Soil Moisture Data

NASA Astrophysics Data System (ADS)

Tobin, K. J.; Bennett, M. E.

2017-12-01

Over the last decade autocalibration routines have become commonplace in watershed modeling. This approach is most often used to simulate a streamflow at a basin's outlet. In alpine settings spring/early summer snowmelt is by far the dominant signal in this system. Therefore, there is great potential for a modeled watershed to underperform during other times of the year. This tendency has been noted in many prior studies. In this work, the Soil and Water Assessment Tool (SWAT) model was autocalibrated with the SUFI-2 routine. Two mountainous watersheds from Idaho and Utah were examined. In this study, the basins were calibrated on a monthly satellite based on the MODIS 16A2 product. The gridded MODIS product was ideally suited to derive an estimate of ET on a subbasin basis. Soil moisture data was derived from extrapolation of in situ sites from the SNOwpack TELemetry (SNOTEL) network. Previous work has indicated that in situ soil moisture can be applied to derive an estimate at a significant distance (>30 km) away from the in situ site. Optimized ET and soil moisture parameter values were then applied to streamflow simulations. Preliminary results indicate improved streamflow performance both during calibration (2005-2011) and validation (2012-2014) periods. Streamflow performance was monitored with not only standard objective metrics (bias and Nash Sutcliffe coefficients) but also improved baseflow accuracy, demonstrating the utility of this approach in improving watershed modeling fidelity outside the main snowmelt season.

Landslides risk mitigation along lifelines

NASA Astrophysics Data System (ADS)

Capparelli, G.; Versace, P.; Artese, G.; Costanzo, S.; Corsonello, P.; Di Massa, G.; Mendicino, G.; Maletta, D.; Leone, S.; Muto, F.; Senatore, A.; Troncone, A.; Conte, E.; Galletta, D.

2012-04-01

The paper describes an integrated, innovative and efficient solution to manage risk issues associated to landslides interfering with infrastructures. The research project was submitted for financial support in the framework of the Multi -regional Operational Programme 2007-13: Research and Competitiveness funded by the Ministry of Research (MIUR) and co-funded by the European Regional Development Fund. The project is aimed to developing and demonstrating an integrated system of monitoring, early warning and mitigation of landslides risk. The final goal is to timely identify potentially dangerous landslides, and to activate all needed impact mitigation measures, including the information delivery. The essential components of the system include monitoring arrays, telecommunication networks and scenario simulation models, assisted by a data acquisition and processing centre, and a traffic control centres. Upon integration, the system will be experimentally validated and demonstrated over ca. 200 km of three highway sections, crossing the regions of Campania, Basilicata, Calabria and Sicily. Progress in the state of art is represented by the developments in the field of environmental monitoring and in the mathematical modeling of landslides and by the development of services for traffic management. The approach to the problem corresponds to a "systemic logics" where each developed component foresees different interchangeable technological solutions to maximize the operational flexibility. The final system may be configured as a simple to complex structure, including different configurations to deal with different scenarios. Specifically, six different monitoring systems will be realized: three "point" systems, made up of a network of locally measuring sensors, and three "area" systems to remotely measure the displacements of large areas. Each network will be fully integrated and connected to a unique data transmission system. Standardized and shared procedures for the identification of risk scenarios will be developed, concerning the surveys to be carried out, the procedures for each type of on-site testing and guidelines and dynamic templates for presentations of results, such as highway risk maps e.g. The setting up of data acquisition and processing centre and traffic control centre are the core of the integrated system. The DAC (data acquisition center, newly designed) will acquire and process data varying in intensity, dimensions, characteristics and information content. The Traffic Control Center (TCC) is meant to integrate the scientific and the management aspects of hydrological risk monitoring and early warning. The overall system is expected to benefit of the development of new, advanced mathematical models on landslide triggers and propagation. Triggering models will be empirical or hydrological, represented by simple empirical relationships, obtained by linking the antecedent rainfall and the landslide time occurrence, and complete models identified through more complex expressions that take into account different components as the specific site conditions, the mechanical, hydraulic and physical properties of soils and slopes, the local seepage conditions and their contribution to soil strength. The industrial partners of the University of Calabria are Autostrade Tech, Strago and TD Group, with the Universities of Firenze and Catania acting research Partners.

Design of a ground-water-quality monitoring network for the Salinas River basin, California

USGS Publications Warehouse

Showalter, P.K.; Akers, J.P.; Swain, L.A.

1984-01-01

A regional ground-water quality monitoring network for the entire Salinas River drainage basin was designed to meet the needs of the California State Water Resources Control Board. The project included phase 1--identifying monitoring networks that exist in the region; phase 2--collecting information about the wells in each network; and phase 3--studying the factors--such as geology, land use, hydrology, and geohydrology--that influence the ground-water quality, and designing a regional network. This report is the major product of phase 3. Based on the authors ' understanding of the ground-water-quality monitoring system and input from local offices, an ideal network was designed. The proposed network includes 317 wells and 8 stream-gaging stations. Because limited funds are available to implement the monitoring network, the proposed network is designed to correspond to the ideal network insofar as practicable, and is composed mainly of 214 wells that are already being monitored by a local agency. In areas where network wells are not available, arrangements will be made to add wells to local networks. The data collected by this network will be used to assess the ground-water quality of the entire Salinas River drainage basin. After 2 years of data are collected, the network will be evaluated to test whether it is meeting the network objectives. Subsequent network evaluations will be done very 5 years. (USGS)

A near real time scenario at regional scale for the hydrogeological risk

NASA Astrophysics Data System (ADS)

Ponziani, F.; Stelluti, M.; Zauri, R.; Berni, N.; Brocca, L.; Moramarco, T.; Salciarini, D.; Tamagnini, C.

2012-04-01

The early warning systems dedicated to landslides and floods represent the Umbria Region Civil Protection Service new generation tools for hydraulic and hydrogeological risk reduction. Following past analyses performed by the Functional Centre (part of the civil protection service dedicated to the monitoring and the evaluation of natural hazards) on the relationship between saturated soil conditions and rainfall thresholds, we have developed an automated early warning system for the landslide risk, called LANDWARN, which generates daily and 72h forecast risk matrix with a dense mesh of 100 x 100m, throughout the region. The system is based on: (a) the 20 days -observed and 72h -predicted rainfall, provided by the local meteorological network and the Local scale Meteorological Model COSMO ME, (b) the assessment of the saturation of soils by: daily extraction of ASCAT satellite data, data from a network of 16 TDR sensors, and a water balance model (developed by the Research Institute for Geo-Hydrological Protection, CNR, Perugia, Italy) that allows for the prediction of a saturation index for each point of the analysis grid up to a window of 72 h, (c) a Web-GIS platform that combines the data grids of calculated hazard indicators with layers of landslide susceptibility and vulnerability of the territory, in order to produce dynamic risk scenarios. The system is still under development and it's implemented at different scales: the entire region, and a set of known high-risk landslides in Umbria. The system is monitored and regularly reviewed through the back analysis of landslide reports for which the activation date is available. Up to now, the development of the system involves: a) the improvement of the reliability assessment of the condition of soil saturation, a key parameter which is used to dynamically adjust the values of rainfall thresholds used for the declaration of levels of landslide hazard. For this purpose, a procedure was created for the ASCAT satellite data daily download, used for the derivation of a soil water content index (SWI): these data are compared with instrumental ones from the TDR stations and the results of the water balance model that evaluates the contributions of water infiltration, percolation, evapotranspiration, etc. using physically based parameters obtained through a long process of characterization of soil and rock types, for each grid point; b) The assessment of the contribution due to the melting of the snow; c) the physically based - coupling model slope stability analysis, GIS-based, developed by the Department of Civil and Environmental Engineering, University of Perugia, with the aim to introduce also the actual mechanical and physical characteristics of slopes in the analysis. As result of the system, is the daily creation of near real-time and 24, 48, 72h forecast risk scenarios, that, under the intention of the Department of Civil Protection Service, will be used by the Functional Centre for the institutional tasks of hydrogeological risk evaluation and management, but also by local Administrations involved in the monitoring and assessment of landslide risk, in order to receive feedback on the effectiveness of the scenarios produced.

Soil-related geohazard assessments for maintaining the UK's minor road network

NASA Astrophysics Data System (ADS)

Pritchard, Oliver; Hallett, Stephen; Farewell, Timothy

2015-04-01

The minor road network of the UK (United Kingdom) encompasses 98% of the overall road network. In recent years the UK's roads have been deteriorating, currently rated 26th in the world and considered at risk and declining by the Institution of Civil Engineers (ICE). Many factors contribute to the degradation and ultimately, to the failure of particular road sections. However, several UK local authorities have identified that during drought conditions, road sections founded upon clay soils which are susceptible to volumetric shrinkage and swelling undergo significant deterioration compared to those sections on non-susceptible soils. Droughts in East Anglia recently resulted in estimated damages of £26 million, leading several local authorities to apply to Central Government for emergency funding. The minor or evolved road network is most at risk due to them having often little, if any, structural foundations. This paper addresses the use of soil-related geohazard assessments and GIS (Geographical Information Systems) in helping to provide a soil-informed maintenance strategy for the asset management of the important (both socially and commercially) local road network of the UK. Furthermore, to establish future subsidence risk, UKCP09 climate projections have been used to model the likely potential soil moisture deficit (PSMD) for baseline (1961-1990), 2030 (2020-2049) and 2050 (2040-2069) scenarios. The incorporation of probabilistic PSMD data into clay-related subsidence models has allowed an assessment of potential subsidence risk, with a range of uncertainties, for these scenarios. Intersection of road networks with future projections of subsidence risk has enabled metrics of potential vulnerability to be established. This will aid prioritisation of areas which require further maintenance to make them more climate resilient, avoiding emergency funding situations. Subsequently, this approach can then be extrapolated to the entire UK minor road network, on a local authority level, to provide a series of regional risk assessments. Case studies are drawn from the UK administrative counties of Lincolnshire and Worcestershire. Data from observed road assessments, obtained from the respective local authorities have been analysed and intersected with clay-related subsidence risk. Lincolnshire County Council have already implemented this research to prioritise approximately £600,000 of road maintenance fund to their minor road network. Further appreciation of the spatial distribution and understanding of soil-related hazards has also led Lincolnshire County Council to trial new resurfacing strategies; these new techniques helping to reduce carbon outputs in the form of materials and transport. A reduction in the amount of potential hazardous (bituminous) waste to landfill is also being achieved through re-inclusion of waste material back into the road foundation where areas are particularly prone to soil shrinkage. Our research shows that soil-related geohazard assessments have a part to play in the asset management of the UK's local highways network. The study supports the ICE's recommendation for a regime which moves towards planned, preventative maintenance and achieving Defra's (Department for Environment, Food and Rural Affairs) aim of a climate resilient UK infrastructure. The methodology introduced here also has applicability to other countries, where appropriate soils and infrastructure data are available.

American River Hydrologic Observatory

NASA Astrophysics Data System (ADS)

Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2016-12-01

We have set up fourteen large wireless sensor networks to measure hydrologic parameters over physiographical representative regions of the snow-dominated portion of the river basin. This is perhaps the largest wireless sensor network in the world. Each network covers about a 1 km2 area and consists of about 45 elements. We measure snow depth, temperature humidity soil moisture and temperature, and solar radiation in real time at ten locations per site, as opposed to the traditional once-a-month snow course. As part of the multi-PI SSCZO, we have installed a 62-node wireless sensor network to measure snow depth, temperature humidity soil moisture and temperature, and solar radiation in real time. This network has been operating for approximately six years. We are now installing four large wireless sensor networks to measure snow depth, temperature humidity soil moisture and temperature, and solar radiation in East Branch of the North Fork of the Feather River, CA. The presentation will discuss the planning and operation of the networks as well as some unique results. It will also present information about the networking hardware designed for these installations, which has resulted in a start-up, Metronome Systems.

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

NASA Technical Reports Server (NTRS)

Smith, James A.

1992-01-01

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

Four soil orders on a Vermont mountaintop-one-third of the world`s soil orders in a 2500-square-meter research plot

Treesearch

Thomas R. Villars; Scott W. Bailey; Donald S. Ross

2015-01-01

As part of the Vermont Long-Term Soil Monitoring Project, five 50 x 50 m plots were established on protected forestland across Vermont. In 2002, ten randomly selected subplots at each monitoring plot were sampled. The 10 pedons sampled at the high-elevation spruce-fir “Forehead” plot on Mount Mansfield were found to include soils of four taxonomic Orders: Entisols,...

Progress and lessons learned from water-quality monitoring networks

USGS Publications Warehouse

Myers, Donna N.; Ludtke, Amy S.

2017-01-01

Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

Geostatistics-based groundwater-level monitoring network design and its application to the Upper Floridan aquifer, USA.

PubMed

Bhat, Shirish; Motz, Louis H; Pathak, Chandra; Kuebler, Laura

2015-01-01

A geostatistical method was applied to optimize an existing groundwater-level monitoring network in the Upper Floridan aquifer for the South Florida Water Management District in the southeastern United States. Analyses were performed to determine suitable numbers and locations of monitoring wells that will provide equivalent or better quality groundwater-level data compared to an existing monitoring network. Ambient, unadjusted groundwater heads were expressed as salinity-adjusted heads based on the density of freshwater, well screen elevations, and temperature-dependent saline groundwater density. The optimization of the numbers and locations of monitoring wells is based on a pre-defined groundwater-level prediction error. The newly developed network combines an existing network with the addition of new wells that will result in a spatial distribution of groundwater monitoring wells that better defines the regional potentiometric surface of the Upper Floridan aquifer in the study area. The network yields groundwater-level predictions that differ significantly from those produced using the existing network. The newly designed network will reduce the mean prediction standard error by 43% compared to the existing network. The adoption of a hexagonal grid network for the South Florida Water Management District is recommended to achieve both a uniform level of information about groundwater levels and the minimum required accuracy. It is customary to install more monitoring wells for observing groundwater levels and groundwater quality as groundwater development progresses. However, budget constraints often force water managers to implement cost-effective monitoring networks. In this regard, this study provides guidelines to water managers concerned with groundwater planning and monitoring.

Preliminary assessment of the state of CO2 soil degassing on the flanks of Gede volcano (West Java, Indonesia)

NASA Astrophysics Data System (ADS)

Kunrat, S. L.; Schwandner, F. M.

2013-12-01

Gede Volcano (West Java) is part of an andesitic stratovolcano complex consisting of Pangrango in the north-west and Gede in the south-east. The last recorded eruptive activity was a phreatic subvolcanian ash eruption in 1957. Current activity is characterized by episodic swarms at 2-4 km depth, and low-temperature (~160°C) crater degassing in two distinct summit crater fumarolic areas. Hot springs occur in the saddle between the Gede and Pangrango edifice, as well as on the NE flank base. The most recent eruptive events produced pyroclastic material, their flow deposits concentrate toward the NE. A collaborative effort between the Center for Volcanology and Geological Hazard Mitigation (CVGHM), Geological Agency and the Earth Observatory of Singapore (EOS) is since 2010 aimed at upgrading the geophysical and geochemical monitoring network at Gede Volcano. To support the monitoring instrumentation upgrades under way, surveys of soil CO2 degassing have been performed on the flanks of Gede, in circular and radial traverses.The goal was to establish a spatial distribution of flank CO2 fluxes, and to allow smart siting for continuous gas monitoring stations. Crater fluxes were not surveyed, as its low-temperature hydrothermal system is likely prone to large hydraulic changes in this tropical environment, resulting in variable permeability effects that might mask signals from deeper reservoir or conduit degassing. The high precipitation intensity in the mountains of tropical Java pose challenges to this method, since soil gas permeability is largely controlled by soil moisture content. Simultaneous soil moisture measurements were undertaken. The soil CO2 surveys were carried out using a LI-8100A campaign flux chamber instrument (LICOR Biosciences, Lincoln, Nebraska). This instrument has a very precise and highly stable sensor and an atmospheric pressure equilibrator, making it highly sensitive to low fluxes. It is the far superior choice for higher precision low-flux flank surveys in tropical environments. The mean flank fluxes measured were 19.8 g/m2/day in 2011, 11.7 g/m2/day in 2012 and 7.6 g/m2/day in early 2013. The mean flank flux for all the surveys is 17.9 g/m2/day. Statistical analysis of the data set reveals at least three distinct flux populations. Results from 2011, 2012 and 2013 indicate that flank fluxes were as high as 112.5g/m2/day, suggesting recent intrusive activity. The spatial distribution of fluxes indicates a strong focus on the NE sector. This finding appears concurrent with an area previously documented as continuously subsiding and filled with recent pyroclastic deposits (Philiboisan et al.2011, G3 Vol.12(11), Fig.15). The surveys also permit selection and validation of sites for continuous CO2 monitoring stations, representing medium and low flank flux populations.

Thermal Conductivity Prediction of Soil in Complex Plant Soil System using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Wardani, A. K.; Purqon, A.

2016-08-01

Thermal conductivity is one of thermal properties of soil in seed germination and plants growth. Different soil types have different thermal conductivity. One of soft-computing promising method to predict thermal conductivity of soil types is Artificial Neural Network (ANN). In this study, we estimate the thermal conductivity of soil prediction in a soil-plant complex systems using ANN. With a feed-forward multilayer trained with back-propagation with 4, 10 and 1 on the input, hidden and output layers respectively. Our input are heating time, temperature and thermal resistance with thermal conductivity of soil as a target. ANN prediction demonstrates a good agreement with Mean Squared Error-testing (MSEte) of 9.56 x 10-7 for soils with green beans and those of bare soils is 7.00 × 10-7 respectively Green beans grow only on black-clay soil with a thermal conductivity of 0.7 W/m K with a sufficient water content. Our results demonstrate that temperature, moisture content, colour, texture and structure of soil are greatly affect to the thermal conductivity of soil in seed germination and plant growth. In future, it is potentially applied to estimate more complex compositions of plant-soil systems.

Optical Network Virtualisation Using Multitechnology Monitoring and SDN-Enabled Optical Transceiver

NASA Astrophysics Data System (ADS)

Ou, Yanni; Davis, Matthew; Aguado, Alejandro; Meng, Fanchao; Nejabati, Reza; Simeonidou, Dimitra

2018-05-01

We introduce the real-time multi-technology transport layer monitoring to facilitate the coordinated virtualisation of optical and Ethernet networks supported by optical virtualise-able transceivers (V-BVT). A monitoring and network resource configuration scheme is proposed to include the hardware monitoring in both Ethernet and Optical layers. The scheme depicts the data and control interactions among multiple network layers under the software defined network (SDN) background, as well as the application that analyses the monitored data obtained from the database. We also present a re-configuration algorithm to adaptively modify the composition of virtual optical networks based on two criteria. The proposed monitoring scheme is experimentally demonstrated with OpenFlow (OF) extensions for a holistic (re-)configuration across both layers in Ethernet switches and V-BVTs.

Availability Issues in Wireless Visual Sensor Networks

PubMed Central

Costa, Daniel G.; Silva, Ivanovitch; Guedes, Luiz Affonso; Vasques, Francisco; Portugal, Paulo

2014-01-01

Wireless visual sensor networks have been considered for a large set of monitoring applications related with surveillance, tracking and multipurpose visual monitoring. When sensors are deployed over a monitored field, permanent faults may happen during the network lifetime, reducing the monitoring quality or rendering parts or the entire network unavailable. In a different way from scalar sensor networks, camera-enabled sensors collect information following a directional sensing model, which changes the notions of vicinity and redundancy. Moreover, visual source nodes may have different relevancies for the applications, according to the monitoring requirements and cameras' poses. In this paper we discuss the most relevant availability issues related to wireless visual sensor networks, addressing availability evaluation and enhancement. Such discussions are valuable when designing, deploying and managing wireless visual sensor networks, bringing significant contributions to these networks. PMID:24526301

FutureGen 2.0 Monitoring Program: An Overview of the Monitoring Approach and Technologies Selected for Implementation

DOE PAGES

Vermeul, Vince R.; Strickland, Chris E.; Thorne, Paul D.; ...

2014-12-31

The FutureGen 2.0 Project will design and build a first-of-its-kind, near-zero emissions coal-fueled power plant with carbon capture and storage (CCS). To assess storage site performance and meet the regulatory requirements of the Class VI Underground Injection Control (UIC) Program for CO2 Geologic Sequestration, the FutureGen 2.0 project will implement a suite of monitoring technologies designed to 1) evaluate CO2 mass balance and 2) detect any unforeseen loss in CO2 containment. The monitoring program will include direct monitoring of the injection stream and reservoir, and early-leak-detection monitoring directly above the primary confining zone. It will also implement an adaptive monitoringmore » strategy whereby monitoring results are continually evaluated and the monitoring network is modified as required, including the option to drill additional wells in out-years. Wells will be monitored for changes in CO2 concentration and formation pressure, and other geochemical/isotopic signatures that provide indication of CO2 or brine leakage. Indirect geophysical monitoring technologies that were selected for implementation include passive seismic, integrated surface deformation, time-lapse gravity, and pulsed neutron capture logging. Near-surface monitoring approaches that have been initiated include surficial aquifer and surface- water monitoring, soil-gas monitoring, atmospheric monitoring, and hyperspectral data acquisition for assessment of vegetation conditions. Initially, only the collection of baseline data sets is planned; the need for additional near- surface monitoring will be continually evaluated throughout the design and operational phases of the project, and selected approaches may be reinstituted if conditions warrant. Given the current conceptual understanding of the subsurface environment, early and appreciable impacts to near-surface environments are not expected.« less

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2014-01-01

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2013; this array is part of the Global Terrestrial Network for Permafrost, (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. This array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2016-03-04

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2014; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. The array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2015

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2017-02-06

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2015; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. The array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve: Alaska and the Arctic National Wildlife Refuge, 1998-2011

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2014-01-01

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2011; this array is part of the Global Terrestrial Network for Permafrost, (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methodology. This array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature and soil moisture, snow depth, rainfall, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

Air temperature, wind speed, and wind direction in the National Petroleum Reserve—Alaska and the Arctic National Wildlife Refuge, 1998–2011

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2013-01-01

This report provides air temperature, wind speed, and wind direction data collected on Federal lands in Arctic Alaska over the period August 1998 to July 2011 by the U.S. Department of the Interior's climate monitoring array, part of the Global Terrestrial Network for Permafrost. In addition to presenting data, this report also describes monitoring, data collection, and quality control methodology. This array of 16 monitoring stations spans 68.5°N to 70.5°N and 142.5°W to 161°W, an area of roughly 150,000 square kilometers. Climate summaries are presented along with provisional quality-controlled data. Data collection is ongoing and includes several additional climate variables to be released in subsequent reports, including ground temperature and soil moisture, snow depth, rainfall, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

Effective contaminant detection networks in uncertain groundwater flow fields.

PubMed

Hudak, P F

2001-01-01

A mass transport simulation model tested seven contaminant detection-monitoring networks under a 40 degrees range of groundwater flow directions. Each monitoring network contained five wells located 40 m from a rectangular landfill. The 40-m distance (lag) was measured in different directions, depending upon the strategy used to design a particular monitoring network. Lagging the wells parallel to the central flow path was more effective than alternative design strategies. Other strategies allowed higher percentages of leaks to migrate between monitoring wells. Results of this study suggest that centrally lagged groundwater monitoring networks perform most effectively in uncertain groundwater-flow fields.

Functional units and lead topologies: a hierarchical framework for observing and modeling the interplay of structures, storage dynamics and integral mass and energy flows in lower mesoscale catchments

NASA Astrophysics Data System (ADS)

Zehe, Erwin; Jackisch, Conrad; Blume, Theresa; Haßler, Sibylle; Allroggen, Niklas; Tronicke, Jens

2013-04-01

The CAOS Research Unit recently proposed a hierarchical classification scheme to subdivide a catchment into what we vaguely name classes of functional entities that puts the gradients driving mass and energy flows and their controls on top of the hierarchy and the arrangement of landscape attributes controlling flow resistances along these driving gradients (for instance soil types and apparent preferential pathways) at the second level. We name these functional entities lead topology classes, to highlight that they are characterized by a spatially ordered arrangement of landscape elements along a superordinate driving gradient. Our idea is that these lead topology classes have a distinct way how their structural and textural architecture controls the interplay of storage dynamics and integral response behavior that is typical for all members of a class, but is dissimilar between different classes. This implies that we might gain exemplary understanding of the typical dynamic behavior of the class, when thoroughly studying a few class members. We propose that the main integral catchment functions mass export and drainage, mass redistribution and storage, energy exchange with the atmosphere, as well as energy redistribution and storage - result from spatially organized interactions of processes within lead topologies that operate at different scale levels and partly dominate during different conditions. We distinguish: 1) Lead topologies controlling the land surface energy balance during radiation driven conditions at the plot/pedon scale level. In this case energy fluxes dominate and deplete a vertical temperature gradient that is build up by depleting a gradient in radiation fluxes. Water is a facilitator in this concert due to the high specific heat of vaporization. Slow vertical water fluxes in soil dominate, which are driven by vertical gradients in atmospheric water potential, chemical potential in the plant and in soil hydraulic potentials. 2) Lead topologies controlling fast drainage and generation stream flow during rainfall events at the hillslope scale level: Fast vertical and lateral mass fluxes dominate. They are driven by vertical and lateral gradients in pressure heads which build up by depleting the kinetic energy/velocity gradient of rainfall when it hits the ground or of vertical subsurface flows that "hit" a layer of low permeability. 3) Lead topologies controlling slow drainage and its supply, and thus creating memory at the catchment scale level: These are the groundwater system and the stream including the riparian zone. Permanent lateral water flows dominate that are driven by permanently active lateral gradients in pressure heads. Event scale stream flow generation and energy exchange with the atmospheric boundary layer are organized by the first two types of lead topologies, and their dominance changes with prevailing type of boundary conditions. We furthermore propose that lead topologies at the plot and the hillslope scale levels can be further subdivided into least functional entities we name call classes of elementary functional units. These classes of elementary functional units co-evolved being exposed to similar superordinate vertical gradients in a self-reinforcing manner. Being located either at the hilltop (sediment source area), midslope (sediment transport area) or hillfoot/riparian zone (sediment deposit area) they experienced similar weathering processes (past water, energy and nutrient flows), causing formation of similar soil texture in different horizons. This implies, depending on hillslope position and aspect, formation of distinct niches (with respect to water, nutrient and sun light availability) and thus "similar filters" to select distinct natural communities of animal and vegetation species. This in turn implies similarity with respect to formation of biotic flow networks (ant-, worm-, mole- and whole burrow systems, as well as root systems), which feeds back on vertical and lateral water/mass and thermal energy flows and so on. The idea is that members of EFU classes interact within lead topologies along a hierarchy of driving potential gradients and that these interactions are mediated by a hierarchy of connected flow networks like macropores, root networks or lateral pipe systems. We hypothesize that members of a functional unit class are similar with respect to the time invariant controls of the vertical gradients (soil hydraulic potentials, soil temperature, plant water potential) and the flow resistances in vertical direction (plant and soil albedo, soil hydraulic and thermal conductivity, vertical macropore networks). This implies that members of an EFU class behave functionally similar at least with respect to vertical flows of water and heat: we may gain exemplary understanding of the typical dynamic behavior of the class, by thoroughly studying a few class members. In the following we will thus use the term "elementary functional units, EFUs" and "elementary functional unit class, EFU class" as synonyms. We propose that a thorough understanding of the behavior of a few representatives of the most important EFU classes and of their interactions within a hierarchy of lead topology classes is sufficient for understanding and distributed modeling of event scale stream flow production under rainfall driven conditions and energy exchange with the atmosphere under radiation driven conditions. Good and not surprising news is that lead topologies controlling stream flow contribution, are an interconnected, ordered arrangement of the lead topologies that control energy exchange. We suggests that a combination of the related model approaches which simplified but physical based approaches to simulate dynamics in the saturated zone, riparian zone and the river network results in a structurally more adequate model framework for catchments of organized complexity. The feasibility of this concept is currently tested in the Attert catchment by setting up pseudo replica of field experiments and a distributed monitoring network in several members of first guess EFUs and superordinate lead topology classes. We combine geophysical and soil physical survey, artificial tracer tests and analysis of stable isotopes and ecological survey with distributed sensor clusters that permanently monitor meteorological variables, soil moisture and matric potential, piezometric heads etc. Within the proposed study we will present first results especially from the sensor clusters and geophysical survey. By using geostatistical methods we will work out to which extend members within a candidate EFU class are similar with respect to subsurface structures like depth to bedrock and soil properties as well as with respect to soil moisture/storage dynamics. Secondly, we will work out whether structurally similar hillslopes produce a similar event scale stream flow contribution, which of course is dependent on the degree of similarity of a) the rainfall forcing they receive and b) of their wetness state. To this end we will perform virtual experiments with the physically based model CATFLOW by perturbing behavioral model structures. These have been shown to portray system behavior and its architecture in a sense that they reproduce distributed observations of soil moisture and subsurface storm flow and represent the observed structural and textural signatures of soils, flow networks and vegetation.

Subsurface Hydrologic Processes Revealed by Time-lapse GPR in Two Contrasting Soils in the Shale Hills CZO

NASA Astrophysics Data System (ADS)

Guo, L.; Lin, H.; Nyquist, J.; Toran, L.; Mount, G.

2017-12-01

Linking subsurface structures to their functions in determining hydrologic processes, such as soil moisture dynamics, subsurface flow patterns, and discharge behaviours, is a key to understanding and modelling hydrological systems. Geophysical techniques provide a non-invasive approach to investigate this form-function dualism of subsurface hydrology at the field scale, because they are effective in visualizing subsurface structure and monitoring the distribution of water. In this study, we used time-lapse ground-penetrating radar (GPR) to compare the hydrologic responses of two contrasting soils in the Shale Hills Critical Zone Observatory. By integrating time-lapse GPR with artificial water injection, we observed distinct flow patterns in the two soils: 1) in the deep Rushtown soil (over 1.5 m depth to bedrock) located in a concave hillslope, a lateral preferential flow network extending as far as 2 m downslope was identified above a less permeable layer and via a series of connected macropores; whereas 2) in the shallow Weikert soil ( 0.3 m depth to saprock) located in a planar hillslope, vertical infiltration into the permeable fractured shale dominated the flow field, while the development of lateral preferential flow along the hillslope was restrained. At the Weikert soil site, the addition of brilliant blue dye to the water injection followed by in situ excavation supported GPR interpretation that only limited lateral preferential flow formed along the soil-saprock interface. Moreover, seasonally repeated GPR surveys indicated different patterns of profile moisture distribution in the two soils that in comparison with the dry season, a dense layer within the BC horizon in the deep Rushtown soil prevented vertical infiltration in the wet season, leading to the accumulation of soil moisture above this layer; whereas, in the shallow Weikert soil, water infiltrated into saprock in wet seasons, building up water storage within the fractured bedrock (i.e., the rock moisture). Results of this study demonstrated the strong interplay between soil structures and subsurface hydrologic behaviors, and time-lapse GPR is an effective method to establish such a relationship under the field conditions.

Clustering and Flow Conservation Monitoring Tool for Software Defined Networks.

PubMed

Puente Fernández, Jesús Antonio; García Villalba, Luis Javier; Kim, Tai-Hoon

2018-04-03

Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.

Electrical Resistivity Tomography Monitoring of Soil Remediation for a Garbage Dump

NASA Astrophysics Data System (ADS)

shi, X.; Luo, Z.; Zhang, Y.; Fu, Q.; Xu, Z.

2011-12-01

Electrical resistivity tomography (ERT) survey was firstly used to investigate the distribution of contaminated soil in a garbage dump area, Wuhan city, China. The result shows that sulfated soil resistivity is about 4 to 7 ohm-m, which is relatively lower than normal soil resistivity of about 15 to 25 ohm-m. The distribution of contaminated soil was delineated using ERT images. Then, ERT survey was carried out in this area for monitoring of remediation of contaminated soil and groundwater. Werner measurements with 60 electrodes of 1 m spacing were taken during the 9-well oxygen injection and nutrition liquid injection period. The difference of apparent resistivity between before gas injection and after gas injection was used to delineate the channel of gas and the trace of gas migration in the porous garbage dump. The electrical resitivity changes between before and after nutrition liquid injection were used to analyze the liquid migration and distribution. The dynamic procedures of gas and water migration are outlined. The results suggest that ERT is a powerful technique for monitoring of soil remediation.

Research on horizontal displacement monitoring of deep soil based on a distributed optical fibre sensor

NASA Astrophysics Data System (ADS)

Huang, Xiaodi; Wang, Yuan; Sun, Yangyang; Zhang, Qinghua; Zhang, Zhenglin; You, Zewei; Ma, Yuan

2018-01-01

The traditional measurement method for the horizontal displacement of deep soil usually uses an inclinometer for piecewise measurement and then generates an artificial reading, which takes a long time and often contains errors; in addition, the anti-jamming and long-term stability of the inclinometer is poor. In this paper, a technique for monitoring horizontal displacement based on distributed optical fibres is introduced. The relationship between the strain and the deflection was described by a theoretical model, and the strain distribution of the inclinometer tube was measured by the cables laid on its surface so that the deflection of the inclinometer tube could be calculated by the difference algorithm and regarded as the horizontal displacement of deep soil. The horizontal displacement monitoring technology of deep soil based on distributed optical fibre sensors developed in this paper not only overcame the shortcomings of traditional inclinometer technology to realize automatic real-time monitoring but also allowed for distributed measurement. The experiment was similar to the expected engineering situations, and the deflection calculated from the strain was compared with an inclinometer. The results demonstrated that the relative error between the distributed optical fibre sensors and the inclinometer was less than 8.0%, and the results also verified both the feasibility of using distributed optical fibre to monitor the horizontal displacement of soil as well as the rationality of the theoretical model and difference algorithm. The application of distributed optical fibre in monitoring the horizontal displacement of deep soil in the engineering of foundation pits and slopes can more accurately evaluate the safety of engineering during construction.

Neural networks using broadband spectral discriminators reduces illumination required for broccoli identification in weedy fields

NASA Astrophysics Data System (ADS)

Hahn, Federico

1996-03-01

Statistical discriminative analysis and neural networks were used to prove that crop/weed/soil discrimination by optical reflectance was feasible. The wavelengths selected as inputs on those neural networks were ten nanometers width, reducing the total collected radiation for the sensor. Spectral data collected from several farms having different weed populations were introduced to discriminant analysis. The best discriminant wavelengths were used to build a wavelength histogram which selected the three best spectral broadbands for broccoli/weed/soil discrimination. The broadbands were analyzed using a new single broadband discriminator index named the discriminative integration index, DII, and the DII values obtained were used to train a neural network. This paper introduces the index concept, its results and its use for minimizing artificial lightning requirements with broadband spectral measurements for broccoli/weed/soil discrimination.

Correction of temperature and bulk electrical conductivity effects on soil water content measurements using ECH2O EC-5, TE and 5TE sensors

NASA Astrophysics Data System (ADS)

Rosenbaum, Ulrike; Huisman, Sander; Vrba, Jan; Vereecken, Harry; Bogena, Heye

2010-05-01

For a monitoring of dynamic spatiotemporal soil moisture patterns at the catchment scale, automated and continuously measuring systems that provide spatial coverage and high temporal resolution are needed. Promising techniques like wireless sensor networks (e.g. SoilNet) have to integrate low-cost electromagnetic soil water content sensors [1], [2]. However, the measurement accuracy of such sensors is often deteriorated by effects of temperature and soil bulk electrical conductivity. The objective of this study is to derive and validate correction functions for such temperature and electrical conductivity effects for the ECH2O EC-5, TE and 5TE sensors. We used dielectric liquids with known dielectric properties for two different laboratory experiments. In the first experiment, the temperature of eight reference liquids with permittivity ranging from 7 to 42 was varied from 5 to 40°C. All sensor types showed an underestimation of permittivity for low temperatures and an overestimation for high temperatures. In the second experiment, the conductivity of the reference liquids was increased by adding NaCl. The highest deviations occurred for high permittivity and electrical conductivity between ~0.8 and 1.5 dS/m (underestimation from 8 to 16 permittivity units depending on sensor type). For higher electrical conductivity (2.5 dS/m), the permittivity was overestimated (10 permittivity units for the EC-5 and 7 for the 5TE sensor). Based on these measurements on reference liquids, we derived empirical correction functions that are able to correct thermal and conductivity effects on measured sensor response. These correction functions were validated using three soil samples (coarse sand, silty clay loam and bentonite). For the temperature correction function, the results corresponded better with theoretical predictions after correction for temperature effects on the sensor circuitry. It was also shown that the application of the conductivity correction functions improved the accuracy of the soil water content predictions considerably. References: [1] Bogena, H.R., J.A. Huisman, C. Oberdörster, H. Vereecken (2007): Evaluation of a low-cost soil water content sensor for wireless network applications. Journal of Hydrology: 344, 32- 42. [2] Rosenbaum, U., Huisman, J.A., Weuthen, A., Vereecken, H. and Bogena, H.R. (2010): Quantification of sensor-to-sensor variability of the ECH2O EC-5, TE and 5TE sensors in dielectric liquids. Accepted for publication in VZJ (09/2009).

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

PubMed

Albaradeyia, Issa; Hani, Azzedine; Shahrour, Isam

2011-09-01

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

Remote sensing of soybean stress as an indicator of chemical concentration of biosolid amended surface soils

NASA Astrophysics Data System (ADS)

Sridhar, B. B. Maruthi; Vincent, Robert K.; Roberts, Sheila J.; Czajkowski, Kevin

2011-08-01

The accumulation of heavy metals in the biosolid amended soils and the risk of their uptake into different plant parts is a topic of great concern. This study examines the accumulation of several heavy metals and nutrients in soybeans grown on biosolid applied soils and the use of remote sensing to monitor the metal uptake and plant stress. Field and greenhouse studies were conducted with soybeans grown on soils applied with biosolids at varying rates. The plant growth was monitored using Landsat TM imagery and handheld spectroradiometer in field and greenhouse studies, respectively. Soil and plant samples were collected and then analyzed for several elemental concentrations. The chemical concentrations in soils and roots increased significantly with increase in applied biosolid concentrations. Copper (Cu) and Molybdenum (Mo) accumulated significantly in the shoots of the metal-treated plants. Our spectral and Landsat TM image analysis revealed that the Normalized Difference Vegetative Index (NDVI) can be used to distinguish the metal stressed plants. The NDVI showed significant negative correlation with increase in soil Cu concentrations followed by other elements. This study suggests the use of remote sensing to monitor soybean stress patterns and thus indirectly assess soil chemical characteristics.

Electrical resistivity tomography as monitoring tool for unsaturated zone transport: an example of preferential transport of deicing chemicals.

PubMed

Wehrer, Markus; Lissner, Heidi; Bloem, Esther; French, Helen; Totsche, Kai Uwe

2014-01-01

Non-invasive spatially resolved monitoring techniques may hold the key to observe heterogeneous flow and transport behavior of contaminants in soils. In this study, time-lapse electrical resistivity tomography (ERT) was employed during an infiltration experiment with deicing chemical in a small field lysimeter. Deicing chemicals like potassium formate, which frequently impact soils on airport sites, were infiltrated during snow melt. Chemical composition of seepage water and the electrical response was recorded over the spring period 2010. Time-lapse electrical resistivity tomographs are able to show the infiltration of the melt water loaded with ionic constituents of deicing chemicals and their degradation product hydrogen carbonate. The tomographs indicate early breakthrough behavior in parts of the profile. Groundtruthing with pore fluid conductivity and water content variations shows disagreement between expected and observed bulk conductivity. This was attributed to the different sampling volume of traditional methods and ERT due to a considerable fraction of immobile water in the soil. The results show that ERT can be used as a soil monitoring tool on airport sites if assisted by common soil monitoring techniques.

Ecohydrological drought monitoring and prediction using a land data assimilation system

NASA Astrophysics Data System (ADS)

Sawada, Y.; Koike, T.

2017-12-01

Despite the importance of the ecological and agricultural aspects of severe droughts, few drought monitor and prediction systems can forecast the deficit of vegetation growth. To address this issue, we have developed a land data assimilation system (LDAS) which can simultaneously simulate soil moisture and vegetation dynamics. By assimilating satellite-observed passive microwave brightness temperature, which is sensitive to both surface soil moisture and vegetation water content, we can significantly improve the skill of a land surface model to simulate surface soil moisture, root zone soil moisture, and leaf area index (LAI). We run this LDAS to generate a global ecohydrological land surface reanalysis product. In this presentation, we will demonstrate how useful this new reanalysis product is to monitor and analyze the historical mega-droughts. In addition, using the analyses of soil moistures and LAI as initial conditions, we can forecast the ecological and hydrological conditions in the middle of droughts. We will present our recent effort to develop a near real time ecohydrological drought monitoring and prediction system in Africa by combining the LDAS and the atmospheric seasonal prediction.

Environmental conditions affecting concentrations of He, CO2, O2 and N2 in soil gases

USGS Publications Warehouse

Hinkle, Margaret E.

1994-01-01

The measurement of concentrations of volatile species in soil gases has potential for use in geochemical exploration for concealed ore deposits and for monitoring of subsurface contaminants. However, the interpretation of anomalies in surficial gases can be difficult because soil-gas concentrations are dependent on both meteorological and environmental conditions.For this study, concentrations of He, CO2, O2 and N2 and meteorological conditions were monitored for 10–14 months at eight nonmineralized sites in both humid and dry environments. Gases were collected at 0.6–0.7-m depth at seven sites. At one site, gases were collected from 0.3-, 0.6-, 1.2-, and 2.0-m depths; diurnal monitoring studies were conducted at this site also. Rain and snowfall, soil and air temperatures, barometric pressure, and relative humidity were monitored at all the sites. The sand, silt and clay content, and the organic carbon content of surficial soil were measured at each site.Meteorological conditions generally affected He and CO2 concentrations in the same way at all the sites; however, these effects were modified by local environmental conditions. Both seasonal and diurnal concentration changes occurred. The most important seasonal concentration changes were related to rain and snowfall and soil and air temperatures. Seasonal changes tended to be larger then the diurnal changes, but both could be related to the same processes. Local conditions of soil type and organic content affected the amount of pore space and moisture present in the soil and therefore the soil-gas concentrations.

ASSESSING THE COMPARABILITY OF AMMONIUM, NITRATE AND SULFATE CONCENTRATIONS MEASURED BY THREE AIR QUALITY MONITORING NETWORKS

EPA Science Inventory

Airborne fine particulate matter across the United States is monitored by different networks, the three prevalent ones presently being the Clean Air Status and Trend Network (CASTNet), the Interagency Monitoring of PROtected Visual Environment Network (IMPROVE) and the Speciati...

USGS Tracks Acid Rain

USGS Publications Warehouse

Gordon, John D.; Nilles, Mark A.; Schroder, LeRoy J.

1995-01-01

The U.S. Geological Survey (USGS) has been actively studying acid rain for the past 15 years. When scientists learned that acid rain could harm fish, fear of damage to our natural environment from acid rain concerned the American public. Research by USGS scientists and other groups began to show that the processes resulting in acid rain are very complex. Scientists were puzzled by the fact that in some cases it was difficult to demonstrate that the pollution from automobiles and factories was causing streams or lakes to become more acidic. Further experiments showed how the natural ability of many soils to neutralize acids would reduce the effects of acid rain in some locations--at least as long as the neutralizing ability lasted (Young, 1991). The USGS has played a key role in establishing and maintaining the only nationwide network of acid rain monitoring stations. This program is called the National Atmospheric Deposition Program/National Trends Network (NADP/NTN). Each week, at approximately 220 NADP/NTN sites across the country, rain and snow samples are collected for analysis. NADP/NTN site in Montana. The USGS supports about 72 of these sites. The information gained from monitoring the chemistry of our nation's rain and snow is important for testing the results of pollution control laws on acid rain.

Groundwater recharge from point to catchment scale

NASA Astrophysics Data System (ADS)

Leterme, Bertrand; Di Ciacca, Antoine; Laloy, Eric; Jacques, Diederik

2016-04-01

Accurate estimation of groundwater recharge is a challenging task as only a few devices (if any) can measure it directly. In this study, we discuss how groundwater recharge can be calculated at different temporal and spatial scales in the Kleine Nete catchment (Belgium). A small monitoring network is being installed, that is aimed to monitor the changes in dominant processes and to address data availability as one goes from the point to the catchment scale. At the point scale, groundwater recharge is estimated using inversion of soil moisture and/or water potential data and stable isotope concentrations (Koeniger et al. 2015). At the plot scale, it is proposed to monitor the discharge of a small drainage ditch in order to calculate the field groundwater recharge. Electrical conductivity measurements are necessary to separate shallow from deeper groundwater contribution to the ditch discharge (see Di Ciacca et al. poster in session HS8.3.4). At this scale, two or three-dimensional process-based vadose zone models will be used to model subsurface flow. At the catchment scale though, using a mechanistic, process-based model to estimate groundwater recharge is debatable (because of, e.g., the presence of numerous drainage ditches, mixed land use pixels, etc.). We therefore investigate to which extent various types of surrogate models can be used to make the necessary upscaling from the plot scale to the scale of the whole Kleine Nete catchment. Ref. Koeniger P, Gaj M, Beyer M, Himmelsbach T (2015) Review on soil water isotope based groundwater recharge estimations. Hydrological Processes, DOI: 10.1002/hyp.10775

Dynamic monitoring of horizontal gene transfer in soil

NASA Astrophysics Data System (ADS)

Cheng, H. Y.; Masiello, C. A.; Silberg, J. J.; Bennett, G. N.

2015-12-01

Soil microbial gene expression underlies microbial behaviors (phenotypes) central to many aspects of C, N, and H2O cycling. However, continuous monitoring of microbial gene expression in soils is challenging because genetically-encoded reporter proteins widely used in the lab are difficult to deploy in soil matrices: for example, green fluorescent protein cannot be easily visualized in soils, even in the lab. To address this problem we have developed a reporter protein that releases small volatile gases. Here, we applied this gas reporter in a proof-of-concept soil experiment, monitoring horizontal gene transfer, a microbial activity that alters microbial genotypes and phenotypes. Horizontal gene transfer is central to bacterial evolution and adaptation and is relevant to problems such as the spread of antibiotic resistance, increasing metal tolerance in superfund sites, and bioremediation capability of bacterial consortia. This process is likely to be impacted by a number of matrix properties not well-represented in the petri dish, such as microscale variations in water, nutrients, and O2, making petri-dish experiments a poor proxy for environmental processes. We built a conjugation system using synthetic biology to demonstrate the use of gas-reporting biosensors in safe, lab-based biogeochemistry experiments, and here we report the use of these sensors to monitor horizontal gene transfer in soils. Our system is based on the F-plasmid conjugation in Escherichia coli. We have found that the gas signal reports on the number of cells that acquire F-plasmids (transconjugants) in a loamy Alfisol collected from Kellogg Biological Station. We will report how a gas signal generated by transconjugants varies with the number of F-plasmid donor and acceptor cells seeded in a soil, soil moisture, and soil O2 levels.

Towards Integrating Soil Quality Monitoring Targets as Measures of Soil Natural Capital Stocks with the Provision of Ecosystem Services

NASA Astrophysics Data System (ADS)

Taylor, M. D.; Mackay, A. D.; Dominati, E.; Hill, R. B.

2012-04-01

This paper presents the process used to review soil quality monitoring in New Zealand to better align indicators and indicator target ranges with critical values of change in soil function. Since its inception in New Zealand 15 year ago, soil quality monitoring has become an important state of the environment reporting tool for Regional Councils. This tool assists councils to track the condition of soils resources, assess the impact of different land management practices, and provide timely warning of emerging issues to allow early intervention and avoid irreversible loss of natural capital stocks. Critical to the effectiveness of soil quality monitoring is setting relevant, validated thresholds or target ranges. Provisional Target Ranges were set in 2003 using expert knowledge available and data on production responses. Little information was available at that time for setting targets for soil natural capital stocks other than those for food production. The intention was to revise these provisional ranges as further information became available and extend target ranges to cover the regulating and cultural services provided by soils. A recently developed ecosystems service framework was used to explore the feasibility of linking soil natural capital stocks measured by the current suite of soil quality indicators to the provision of ecosystem services by soils. Importantly the new approach builds on and utilises the time series data sets collected by current suite of soil quality indicators, adding value to the current effort, and has the potential to set targets ranges based on the economic and environmental outcomes required for a given farm, catchment or region. It is now timely to develop a further group of environmental indicators for measuring specific soil issues. As with the soil quality indicators, these environmental indicators would be aligned with the provision of ecosystem services. The toolbox envisaged is a set of indicators for specific soil issues with appropriate targets tied to ecosystem services and changes in critical soil function. Such indicators would be used for specific purposes for limited periods, rather than long-term, continuous monitoring. Some examples will be presented. An important step needed to successfully initiate and complete the review was assigning national oversight. Reigniting scientific interest (which had declined with the cessation of funding in 2003) and documentation of the process were other important steps. We had to extend the recently developed ecosystem service approach to accommodate the catchment scale. This required additional attributes in the framework and recognition that some of the proxies will change with scale as will the techniques to value the services. The framework was originally developed for use at the farm scale. Macroporosity, one of the two indicators used to monitor the physical condition of the soil, was used to illustrate how the ecosystem service framework could be used to link a change in the physical condition of the soil with the provision of services. The sum of the dollar values of selected soil ecosystem services were used to inform the state of soil natural capital stocks. This estimate provides a new insight into the value of the soil quality indicators and existing target ranges. Doing so will enable targets to be more closely aligned and integrated with the provision of a range of ecosystem services, going far beyond food production.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

GPR monitoring for non-uniform infiltration through a high permeable gravel layer in the test sand box

NASA Astrophysics Data System (ADS)

Kuroda, Seiichiro; Ishii, Nobuyuki; Morii, Toshihiro

2017-04-01

Recently capillary barriers have been known as a method to protect subsurface regions against infiltration from soil surface. It has essentially non-uniform structure of permeability or soil physical property. To identify the function of the capillary barrier, the site-characterization technique for non-uniform soil moisture distribution and infiltration process is needed. We built a sand box in which a thin high-permeable gravel layer was embedded and conducted a infiltration test, including non-uniform flow of soil water induced by capillary barrier effects. We monitored this process by various types of GPR measurements, including time-lapsed soundings with multi-frequency antenna and transmission measurements like one using cross-borehole radar. Finally we will discuss the applicability of GPR for monitoring the phenomena around the capillary barrier of soil. This work has partially supported by JSPS Grant-in-aid Scientific Research program, No.16H02580.

Prediction of relative and absolute permeabilities for gas and water from soil water retention curves using a pore-scale network model

NASA Astrophysics Data System (ADS)

Fischer, Ulrich; Celia, Michael A.

1999-04-01

Functional relationships for unsaturated flow in soils, including those between capillary pressure, saturation, and relative permeabilities, are often described using analytical models based on the bundle-of-tubes concept. These models are often limited by, for example, inherent difficulties in prediction of absolute permeabilities, and in incorporation of a discontinuous nonwetting phase. To overcome these difficulties, an alternative approach may be formulated using pore-scale network models. In this approach, the pore space of the network model is adjusted to match retention data, and absolute and relative permeabilities are then calculated. A new approach that allows more general assignments of pore sizes within the network model provides for greater flexibility to match measured data. This additional flexibility is especially important for simultaneous modeling of main imbibition and drainage branches. Through comparisons between the network model results, analytical model results, and measured data for a variety of both undisturbed and repacked soils, the network model is seen to match capillary pressure-saturation data nearly as well as the analytical model, to predict water phase relative permeabilities equally well, and to predict gas phase relative permeabilities significantly better than the analytical model. The network model also provides very good estimates for intrinsic permeability and thus for absolute permeabilities. Both the network model and the analytical model lost accuracy in predicting relative water permeabilities for soils characterized by a van Genuchten exponent n≲3. Overall, the computational results indicate that reliable predictions of both relative and absolute permeabilities are obtained with the network model when the model matches the capillary pressure-saturation data well. The results also indicate that measured imbibition data are crucial to good predictions of the complete hysteresis loop.

Monitoring restoration impacts to endemic plant communities in soil inclusions of arid environments

USGS Publications Warehouse

Louhaichi, Mounir; Pyke, David A.; Shaff, Scott E.; Johnson, Douglas E.

2013-01-01

Soil inclusions are small patches of soil with different properties than the surrounding, dominant soil. In arid areas of western North America, soil inclusions called slickspot soils are saltier than adjacent soil and support different types of native vegetation. Traditional sagebrush restoration efforts, such as using drills to plant seeds or herbicides to control invasive vegetation, may damage sensitive slickspot soil and supporting vegetation. USGS scientists David Pyke and Scott Shaff and collaborators monitored slickspot size and cover of endangered slickspot peppergrass for two years to see if they were affected by the application of the herbicide glyphosate or by a minimum-till drill in the Snake River Plain, ID. The researchers examined the use of aerial photographs versus on-the-ground measurements and concluded that slickspot sizes were not affected by these treatments. Remote sensing using aerial photographs proved a useful method for mapping slickspot soils.

Climate change and soil salinity: The case of coastal Bangladesh.

PubMed

Dasgupta, Susmita; Hossain, Md Moqbul; Huq, Mainul; Wheeler, David

2015-12-01

This paper estimates location-specific soil salinity in coastal Bangladesh for 2050. The analysis was conducted in two stages: First, changes in soil salinity for the period 2001-2009 were assessed using information recorded at 41 soil monitoring stations by the Soil Research Development Institute. Using these data, a spatial econometric model was estimated linking soil salinity with the salinity of nearby rivers, land elevation, temperature, and rainfall. Second, future soil salinity for 69 coastal sub-districts was projected from climate-induced changes in river salinity and projections of rainfall and temperature based on time trends for 20 Bangladesh Meteorological Department weather stations in the coastal region. The findings indicate that climate change poses a major soil salinization risk in coastal Bangladesh. Across 41 monitoring stations, the annual median projected change in soil salinity is 39 % by 2050. Above the median, 25 % of all stations have projected changes of 51 % or higher.

Validation of in situ networks via field sampling: case study in the South Fork Experimental Watershed

USDA-ARS?s Scientific Manuscript database

The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Therefore, these stations are located along field boundaries or in non-representative sites with regards to so...

Assimilation of spatially sparse in situ soil moisture networks into a continuous model domain

USDA-ARS?s Scientific Manuscript database

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 ...

National monitoring study in Denmark finds increased and critical levels of copper and zinc in arable soils fertilized with pig slurry.

PubMed

Jensen, John; Larsen, Martin Mørk; Bak, Jesper

2016-07-01

The increasing consumption of copper and zinc in modern farming is linked to their documented benefit as growth promoting agents and usefulness for controlling diarrhoea. Copper and zinc are inert and non-degradable in the slurry and the environment and thereby introducing new challenges and concern. Therefore, a follow-up to pervious national soil monitoring programs on heavy metals was initiated in 2014 with special focus on the historical trends in soil concentrations of copper and zinc in Danish arable soils. Hereby it is possible to analyse trends for a 28 year period. Data shows that: 1) Amendment of soils with pig slurry has led to a significant increase in soil concentrations of copper and zinc, especially in the latest monitoring period from 1998 to 2014; 2) Predicted no-effect concentrations for soil dwelling species published by the European Union is exceeded for zinc in 45% of all soil samples, with the highest proportion on sandy soils; 3) The current use of zinc and copper in pig production may lead to leaching of metals, especially zinc, from fields fertilized with pig slurry in concentrations that may pose a risk to aquatic species. Copyright © 2016 Elsevier Ltd. All rights reserved.

Soil

USDA-ARS?s Scientific Manuscript database

Soil is a diverse natural material characterized by solid, liquid, and gas phases that impart unique chemical, physical, and biological properties. Soil provides many key functions, including supporting plant growth and providing environmental remediation. Monitoring key soil properties and processe...

The San Niccolo' experimental area for studying the hydrology of coastal Mediterranean peatlands

NASA Astrophysics Data System (ADS)

Rossetto, Rudy; Barbagli, Alessio; Sabbatini, Tiziana; Silvestri, Nicola; Bonari, Enrico

2015-04-01

Starting from 1930, a large part of the Massaciuccoli Lake coastal area (Tuscany, Italy) has been drained for agricultural purposes by a complex network of artificial drains and pumping stations. In the drained areas, peat soils, with values of organic matter up to 50% in some cases, are largely present (Pistocchi et al., 2012). As a consequence of the human impact, environmental problems arose in the last 50 years: i. the eutrophication status of the Massaciuccoli lake caused by nutrient enrichment (N, P) in surface- and ground-water (Rossetto et al., 2010a); ii. the subsidence (2-3 m in 70 years) of the lake bordering areas due to soil compaction and mineralization (Rossetto et al., 2010b). As a potential solution to improve water quality and to decrease soil organic matter mineralization, a rewetted pilot experimental area of 15 ha with phyto-treatment functionalities has been set up. This pilot, adequately instrumented, now constitutes an open field lab to conduct research on the hydrology of coastal Mediterranean peatlands. Site investigation was performed and data on stratigraphy (from top on average: 1/2 m thick peat layer, 1/3 m organic matter-rich silt, 1/3 m stiff blue-gray clay, up to 30 m thick sand layer) and water (ground- and surface-water) quantity and quality were gathered and related to both local and regional groundwater flows. The inferred hydrological conceptual model revealed the pilot is set in a regional discharge area and the ground-water dependent nature of the agro-ecosystem, with mixing of waters with different origins. The site has been divided in three different phyto-treatment systems: a constructed wetland system, internally and externally banked in order to force water flow to a convoluted pattern where Phragmites australis L. and Thypha angustifolia L. constitute the sparse natural vegetation; a vegetation filter system based on the plantation of seven different no-food crops managed according to a periodic cutting and biomass harvesting (eg: Populus spp., Salix spp., Arundo donax L., Miscanthus x giganteus ). The system is crossed by a dense network of ditches supplying water to the crops through lateral infiltration and partial submersion; a wetland system consisting in a flooded area where the re-colonization of spontaneous vegetation takes place. The designed monitoring system includes sensors in surface- and ground-water. The ground-water monitoring system consists of a set of 15 piezometer clusters. At each cluster three piezometers (3 inch diameter, screened in the last 30 cm) are set at about 3 m, 2 m and 1 m depth to allow multilevel monitoring and sampling so to investigate a large part of the aquifer and the relationships between the surface-water and ground-water systems. An unsaturated pilot monitoring station has been designed and it will be set in operation to gain information on infiltration and/or exfiltration processes and evapotranspiration. Ten sensors for continuously monitoring groundwater head, temperature and electrical conductivity are in operation. Surface water are monitored by means of six gauging stations where sensors are recording at least head, temperature and electrical conductivity. At four of them continuous sampling takes place with a composite daily sample made up of four samples, each gathered every six hours. A complete hydrological monitoring protocol has been set in place starting by meteorological data aquisition. As well as continuous monitoring with in-situ sensors and composite sampling with automatic samplers, discrete monitoring on monthly basis takes place. Main physico/chemical parameters (temperature, pH, dissolved oxygen, electrical conductivity and redox potential) are routinely monitored. The experimental area is in operation since December 2013. Acknowledgements The authors wish to thank the Consorzio 1 - Toscana Nord for technical support. References Pistocchi C., Silvestri N., Rossetto R., Sabbatini T., Guidi M., Baneschi I., Bonari E. & Trevisan D. (2012) - A simple model to assess nitrogen and phosphorus contamination in ungauged surface drainage networks: application to the Massaciuccoli Lake Catchment, Italy. Journal of Environmental Quality 41, 544-53. Rossetto,R., Basile, P., Cavallaro, E., Menichetti,S., Pistocchi, C., Sabbatini, T., Silvestri, N. & Bonari, E. (2010a) - Phosphorous presence in groundwater from peat oxidation: preliminary results from the Lake Massaciuccoli area (Italy). International Groundwater Symposium I.A.H.R. Valencia (Spain). Rossetto R., Basile P., Cannavò S., Pistocchi C., Sabbatini T., Silvestri N. & Bonari E. (2010b) - Surface water and groundwater monitoring and numerical modeling of the southern sector of the Massaciuccoli Lake basin (Italy). Rendiconti Online Società Geologica Italiana 11, 189-190.

Soil properties discriminating Araucaria forests with different disturbance levels.

PubMed

Bertini, Simone Cristina Braga; Azevedo, Lucas Carvalho Basilio; Stromberger, Mary E; Cardoso, Elke Jurandy Bran Nogueira

2015-04-01

Soil biological, chemical, and physical properties can be important for monitoring soil quality under one of the most spectacular vegetation formation on Atlantic Forest Biome, the Araucaria Forest. Our aim was to identify a set of soil variables capable of discriminating between disturbed, reforested, and native Araucaria forest soils such that these variables could be used to monitor forest recovery and maintenance. Soil samples were collected at dry and rainy season under the three forest types in two state parks at São Paulo State, Brazil. Soil biological, chemical, and physical properties were evaluated to verify their potential to differentiate the forest types, and discriminant analysis was performed to identify the variables that most contribute to the differentiation. Most of physical and chemical variables were sensitive to forest disturbance level, but few biological variables were significantly different when comparing native, reforested, and disturbed forests. Despite more than 20 years following reforestation, the reforested soils were chemically and biologically distinct from native and disturbed forest soils, mainly because of the greater acidity and Al3+ content of reforested soil. Disturbed soils, in contrast, were coarser in texture and contained greater concentrations of extractable P. Although biological properties are generally highly sensitive to disturbance and amelioration efforts, the most important soil variables to discriminate forest types in both seasons included Al3+, Mg2+, P, and sand, and only one microbial attribute: the NO2- oxidizers. Therefore, these five variables were the best candidates, of the variables we employed, for monitoring Araucaria forest disturbance and recovery.

Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

USGS Publications Warehouse

Harden, Jennifer W.; Hugelius, Gustaf; Ahlström, Anders; Blankinship, Joseph C.; Bond-Lamberty, Ben; Lawrence, Corey; Loisel, Julie; Malhotra, Avni; Jackson, Robert B.; Ogle, Stephen M.; Phillips, Claire; Ryals, Rebecca; Todd-Brown, Katherine; Vargas, Rodrigo; Vergara, Sintana E.; Cotrufo, M. Francesca; Keiluweit, Marco; Heckman, Katherine; Crow, Susan E.; Silver, Whendee L.; DeLonge, Marcia; Nave, Lucas E.

2018-01-01

Soil organic matter (SOM) supports the Earth's ability to sustain terrestrial ecosystems, provide food and fiber, and retains the largest pool of actively cycling carbon. Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerable to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of SOM and SOC and their management for sustained production and climate regulation.

Common mycorrhizal networks and their effect on the bargaining power of the fungal partner in the arbuscular mycorrhizal symbiosis.

PubMed

Bücking, Heike; Mensah, Jerry A; Fellbaum, Carl R

2016-01-01

Arbuscular mycorrhizal (AM) fungi form mutualistic interactions with the majority of land plants, including some of the most important crop species. The fungus takes up nutrients from the soil, and transfers these nutrients to the mycorrhizal interface in the root, where these nutrients are exchanged against carbon from the host. AM fungi form extensive hyphal networks in the soil and connect with their network multiple host plants. These common mycorrhizal networks (CMNs) play a critical role in the long-distance transport of nutrients through soil ecosystems and allow the exchange of signals between the interconnected plants. CMNs affect the survival, fitness, and competitiveness of the fungal and plant species that interact via these networks, but how the resource transport within these CMNs is controlled is largely unknown. We discuss the significance of CMNs for plant communities and for the bargaining power of the fungal partner in the AM symbiosis.

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

USDA-ARS?s Scientific Manuscript database

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

Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring

PubMed Central

Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

2016-01-01

Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and k-connectivity WSN deployment for monitoring crop growth information of farmland on a large scale and to ensure the accuracy of the monitored data, a new WSN deployment method using a genetic algorithm (GA) is here proposed. The fitness function of GA was constructed based on the following WSN deployment criteria: (1) nodes must be located in the corresponding plots; (2) WSN must have k-connectivity; (3) WSN must have no communication silos; (4) the minimum distance between node and plot boundary must be greater than a specific value to prevent each node from being affected by the farmland edge effect. The deployment experiments were performed on natural farmland and on irregular farmland divided based on spatial differences of soil nutrients. Results showed that both WSNs gave full coverage, there were no communication silos, and the minimum connectivity of nodes was equal to k. The deployment was tested for different values of k and transmission distance (d) to the node. The results showed that, when d was set to 200 m, as k increased from 2 to 4 the minimum connectivity of nodes increases and is equal to k. When k was set to 2, the average connectivity of all nodes increased in a linear manner with the increase of d from 140 m to 250 m, and the minimum connectivity does not change. PMID:27941704

A pilot study of the Earthquake Precursors in the Southwest Peloponnes, Greece

NASA Astrophysics Data System (ADS)

Velez, A. P.; Tsinganos, K.; Karastathis, V. K.; Kafatos, M.; Ouzounov, D.; Papadopoulos, G. A.; Tselentis, A.; Eleftheriou, G.; Mouzakiotis, E.; Gika, F.; Aspiotis, T.; Liakopoulos, S.; Voulgaris, N.

2016-12-01

A seismic array of the most contemporary technology has been recently installed in the area of Southwest Peloponnese, Greece, an area well known for its high seismic activity. The tectonic regime of the Hellenic arc was the reason for many lethal earthquakes with considerable damage to the broader area of East Mediterranean sea. The seismic array is based on nine 32-bit stations with broadband borehole seismometers. The seismogenic region, monitored by the array, is offshore. At this place the earthquake location suffers by poor azimuthal coverage and the stations of the national seismic network are very distant to this area. Therefore, the existing network cannot effectively monitor the microseismicity. The new array achieved a detailed monitoring of the small events dropping considerably the magnitude of completeness. The detectability of the microearthquakes has been drastically improved permitting so the statistical assessment of earthquake sequences in the area. In parallel the monitored seismicity is directly related with Radon measurement in the soil, taken at three stations in the area.. Radon measurements are performed indirectly by means γ-ray spectrometry of its radioactive progenies 214Pb and 214Bi (emitted at 351 keV and 609 keV, respectively). NaI(Tl) detectors have been installed at 1 m depth, at sites in vicinity of faults providing continuous real time data. Local meteorological records for atmospheric corrections are also continuously recorded. According to the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model atmospheric thermal anomalies observed before strong events can be attributed to increased radon concentration. This is also supported by the statistical analysis of AVHRR/NOAA-18 satellite thermal infrared (TIR) daily records. A combined study of precursor's signals is expected to provide a reliable assessment of their ability on short-term forecasting.

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Huffman, George J.; Pierce, Harold

2008-01-01

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

Transregional Collaborative Research Centre 32: Patterns in Soil-Vegetation-Atmosphere-Systems

NASA Astrophysics Data System (ADS)

Simmer, C.; Thiele-Eich, I.

2015-12-01

The Collaborative Research Centre TR32 has the goal to perform pattern-based prediction of states and fluxes of water, CO2 and energy in terrestrial systems across scales. For this, the TR32 set up the following three elements during the past nine years: measurement techniques that allow us to characterize and monitor the spatiotemporal dynamics and evolution of system properties across scales, a cross-scale, multi-compartment terrestrial system modeling approach that includes all relevant processes using the terrestrial model platform TerrSysMP and state variable assimilation and parameter estimation methods. We will present examples of how the TR32 utilizes these three elements to improve our understanding of the water cycle. The available soil moisture monitoring network consisting of e.g. cosmic-ray sensors or an in situ NMR slim-line logging tool has been helpful in understanding the interactions of plant growth and soil moisture dynamics. New algorithms derive soil moisture from satellite based SAR systems, which showed potential for the derivation of surface roughness and vegetation information. For surface precipitation, a radar composite using observations from two dual-polarized X-band Doppler radars provides nearly 100% coverage of the Rur catchment. To also be able to include other precipitation observations which occur at different temporal and spatial resolutions, such as rain gauges, a high resolution space-time precipitation model is being developed. Commercial microwave links used for cell phone communication have also been experimented with to improve polarimetric quantitative precipitation estimation. In addition, uncertainty plays a major role with respect to the central goal of the TR32 and is taken into account in various ways. For example, model uncertainty in the Rur catchment results in large parts from anthropogenic activities such as e.g. drainage patterns in fields, the control of the Rur discharge, groundwater pumping, storage lakes, etc. Other approaches to quantify uncertainty include sensitivity experiments to evaluate the effects of parameter lumping.

Statistical approaches used to assess and redesign surface water-quality-monitoring networks.

PubMed

Khalil, B; Ouarda, T B M J

2009-11-01

An up-to-date review of the statistical approaches utilized for the assessment and redesign of surface water quality monitoring (WQM) networks is presented. The main technical aspects of network design are covered in four sections, addressing monitoring objectives, water quality variables, sampling frequency and spatial distribution of sampling locations. This paper discusses various monitoring objectives and related procedures used for the assessment and redesign of long-term surface WQM networks. The appropriateness of each approach for the design, contraction or expansion of monitoring networks is also discussed. For each statistical approach, its advantages and disadvantages are examined from a network design perspective. Possible methods to overcome disadvantages and deficiencies in the statistical approaches that are currently in use are recommended.

Effects of non-native earthworms on on below- and aboveground processes in the Mid-Atlantic region

NASA Astrophysics Data System (ADS)

Szlavecz, K. A.; McCormick, M. K.; Xia, L.; Pitz, S.; O'Neill, J.; Bernard, M.; Chang, C.; Whigham, D. F.

2011-12-01

Many biotic and abiotic disturbances have shaped the structure of the deciduous forests in the Mid-Atlantic region. One major anthropogenic factor is land use history. Agricultural practices in the past undoubtedly facilitated non-native earthworm colonization and establishment. Today most secondary forests are dominated by European lumbricid earthworms, although native species also occur in some habitats. To investigate how earthworm community composition and abundance affect belowground processes and tree seedling growth we set up a field manipulation experiment at the Smithsonian Environmental Research Center in Edgewater, MD. A total of 66 experimental plots were set up in successional (70 yrs) and mature (150 yrs) Tulip-poplar-Oak associations. We manipulated earthworm abundance and leaf litter input, and planted seedlings of Tulip poplar, Red maple, Red oak, and American beech. The experiment lasted for two years during which we regularly monitored density, biomass and species composition of earthworm assemblages and measured soil respiration. Soil moisture, temperature and air temperature were also continuously monitored using a wireless sensor network. At harvest, soil bulk density, pH, N pools, C:N ratio, potential N-mineralization rates, and enzyme activity were determined. We used quantitative PCR to assess the community composition of soil fungi. We also determined the extent of mycorrhizal colonization and biomass of roots, shoots and leaves. We conducted likelihood ratio tests for random and fixed effects based on mixed model analyses of variance. Differences between soil depths and among sites and plots accounted for a large portion of the variation in many soil properties. Litter quality affected soil pH and N mineralization. Earthworm densities affected bulk density, inorganic N content, and N mineralization. Both mycorrhizal groups were more abundant in mature than in successional forests. Both ectomycorrhizal (ECM) and arbuscular (AM) fungi were less abundant in the earthworm removal plots. There was a significant positive earthworm effect on the rate and thermal sensitivity of soil respiration. Soil respiration was consistently higher in plots with tulip poplar litter than those with beech litter, indicating a strong influence of plant residue quality. However, the differences were smaller in the second year than in the first one indicating an adaptation of the soil system. Oak and beech seedlings were smaller in high density earthworm plots, while the reverse was true for maple and tulip poplar seedlings. Non-native earthworms affect below- and aboveground processes, however, these effects depend on forest type and land use history. The earthworm effects also appear to be dynamic, as witnessed by a recent invasion of an Asian earthworm species in one of our forest stands.

Evaluation of soil erosion risk using Analytic Network Process and GIS: a case study from Spanish mountain olive plantations.

PubMed

Nekhay, Olexandr; Arriaza, Manuel; Boerboom, Luc

2009-07-01

The study presents an approach that combined objective information such as sampling or experimental data with subjective information such as expert opinions. This combined approach was based on the Analytic Network Process method. It was applied to evaluate soil erosion risk and overcomes one of the drawbacks of USLE/RUSLE soil erosion models, namely that they do not consider interactions among soil erosion factors. Another advantage of this method is that it can be used if there are insufficient experimental data. The lack of experimental data can be compensated for through the use of expert evaluations. As an example of the proposed approach, the risk of soil erosion was evaluated in olive groves in Southern Spain, showing the potential of the ANP method for modelling a complex physical process like soil erosion.

The influences of changing weather patterns and land management on runoff biogeochemistry in a snowmelt dominated agricultural region

NASA Astrophysics Data System (ADS)

Wilson, H. F.; Elliott, J. A.; Glenn, A. J.

2017-12-01

Runoff generation and the associated export of nitrogen, phosphorus, and organic carbon on the Northern Great Plains have historically been dominated by snowmelt runoff. In this region the transport of elements primarily occurs in dissolved rather than particulate forms, so cropland management practices designed to reduce particulate losses tend to be ineffective in reducing nutrient runoff. Over the last decade a higher frequency of high volume and intensity rainfall has been observed, leading to rainfall runoff and downstream flooding. To evaluate interactions between tillage, crop residue management, fertilization practices, weather, and runoff biogeochemistry a network of 18 single field scale watersheds (2-6 ha.) has been established in Manitoba, Canada over a range of fertilization (no input to high input) and tillage (zero tillage to frequent tillage). Soils in this network are typical of cropland in the region with clay or clay loam textures, but soil phosphorus differs greatly depending on input practices (3 to 25 mg kg-1 sodium bicarbonate extractable P). Monitoring of runoff chemistry and hydrology at these sites was initiated in 2013 and over the course of 5 years high volume snowmelt runoff from deep snowpack (125mm snow water equivalent), low volume snowmelt from shallow snowpack (25mm snow water equivalent) and extreme rainfall runoff events in spring have all been observed. Event based analyses of the drivers of runoff chemistry indicate that spring fertilization practices (depth, amount, and timing) influence concentrations of N and P in runoff during large rainfall runoff events, but for snowmelt runoff the near surface soil chemistry, tillage, and crop residue management are of greater importance. Management recommendations that might be suggested to reduce nutrient export and downstream eutrophication in the region differ for snowmelt and rainfall, but are not mutually exclusive.

Development of Compact, Modular Lunar Heat Flow Probes

NASA Technical Reports Server (NTRS)

Nagihara, S.; Zacny, K.; Hedlund, M.; Taylor, P. T.

2014-01-01

Geothermal heat flow measurements are a high priority for the future lunar geophysical network missions recommended by the latest Decadal Survey and previously the International Lunar Network. Because the lander for such a mission will be relatively small, the heat flow instrumentation must be a low-mass and low-power system. The instrument needs to measure both thermal gradient and thermal conductivity of the regolith penetrated. It also needs to be capable of excavating a deep enough hole (approx. 3 m) to avoid the effect of potential long-term changes of the surface thermal environment. The recently developed pneumatic excavation system can largely meet the low-power, low-mass, and the depth requirements. The system utilizes a stem which winds out of a pneumatically driven reel and pushes its conical tip into the regolith. Simultaneously, gas jets, emitted from the cone tip, loosen and blow away the soil. The thermal sensors consist of resistance temperature detectors (RTDs) embedded on the stem and an insitu thermal conductivity probe attached to the cone tip. The thermal conductivity probe consists of a short 'needle' (2.4-mm diam. and 15- to 20-mm length) that contains a platinum RTD wrapped in a coil of heater wire. During a deployment, when the penetrating cone reaches a desired depth, it stops blowing gas, and the stem pushes the needle into the yet-to-be excavated, undisturbed bottom soil. Then, it begins heating and monitors the temperature. Thermal conductivity of the soil can determined from the rate of temperature increase with time. When the measurement is complete, the system resumes excavation until it reaches the next targeted depth.