Christopher J. Post

Measurement and modeling of the transpiration of a temperate red maple container nursery

This study was designed to estimate transpiration in a container nursery under both irrigated and water stressed conditions using a biologically based canopy model. The model, MAESTRA, was parameterized with a suite of physiological measurements and an explicit response function for soil moisture deficit was incorporated. The model was validated against transpiration measurements monitored by the stem heat balance method in both irrigated and non-irrigated plots. Distinct disconnects between estimated and measured values were found at high soil moisture deficits. The data justify the incorporation of a soil moisture component to simulate transpiration of plants with root zones in limited soil volumes. The agreement between measured and modelled canopy transpiration separated at a soil moisture deficit of 0.85 or greater, however, estimates of daily transpiration simulated by the model were in agreement with sap-flow measurements when water was not limiting. The data indicate that cuticular conductance at soil moisture deficits ≤0.85 may explain the separation in model estimates and actual plant water loss.

Comparison of Soil Organic Carbon Recovery by Walkley-Black and Dry Combustion Methods in the Russian Chernozem

This study compared soil organic carbon (SOC) recovery in the Russian Chernozem (a fine-silty, mixed, frigid Pachic Hapludoll) under four management regimes (native grassland, yearly-cut/grazed hay, continuous cropping, and continuously plowed fallow) and different depths by Walkley-Black and two dry combustion methods. The Walkley-Black method was different from both dry combustion methods and required a correction factor of 1.63 in all management regimes.

An Integrated WebGIS Framework for Volunteered Geographic Information and Social Media in Soil and Water Conservation

Volunteered geographic information and social networking in a WebGIS has the potential to increase public participation in soil and water conservation, promote environmental awareness and change, and provide timely data that may be otherwise unavailable to policymakers in soil and water conservation management. The objectives of this study were: (1) to develop a framework for combining current technologies, computing advances, data sources, and social media; and (2) develop and test an online web mapping interface. The mapping interface integrates Microsoft Silverlight, Bing Maps, ArcGIS Server, Google Picasa Web Albums Data API, RSS, Google Analytics, and Facebook to create a rich user experience. The website allows the public to upload photos and attributes of their own subdivisions or sites they have identified and explore other submissions. The website was made available to the public in early February 2011 at http://www.AbandonedDevelopments.com and evaluated for its potential long-term success in a pilot study.

The South Carolina Digital Watershed: End-to-End Support for Real-Time Management of Water Resources

Water resources are under unprecedented strain. The combined effects of population growth, climate change, and rural industrialization have led to greater demand for an increasingly scarce resource. Ensuring that communities have adequate access to water—an essential requirement for community health and prosperity—requires finegrained management policies based on real-time in situ data, both environmental and hydrological. To address this requirement at the state level, we have developed the South Carolina Digital Watershed, an end-to-end system for monitoring water resources. In this paper, we describe the design and implementation of the core system components: (i) in situ sensing hardware, (ii) collection and uplink facilities, (iii) data streaming middleware, and (iv) back-end repository and presentation services. We conclude by discussing key organizational and technical challenges encountered during the development process.

Towards Ontology-based Data Quality Inference in Large-Scale Sensor Networks

This paper presents an ontology-based approach for data quality inference on streaming observation data originating from large-scale sensor networks. We evaluate this approach in the context of an existing river basin monitoring program called the Intelligent River®. Our current methods for data quality evaluation are compared with the ontology-based inference methods described in this paper. We present an architecture that incorporates semantic inference into a publish/subscribe messaging middleware, allowing data quality inference to occur on real-time data streams. Our preliminary benchmark results indicate delays of 100ms for basic data quality checks based on an existing semantic web software framework. We demonstrate how these results can be maintained under increasing sensor data traffic rates by allowing inference software agents to work in parallel. These results indicate that data quality inference using the semantic sensor network paradigm is viable solution for data intensive, large-scale sensor networks.

The Intelligent River©: Implementation of Sensor Web Enablement technologies across three tiers of system architecture: Fabric, middleware, and application

Population growth, energy demand, and climate change are placing an unprecedented strain on water resources, requiring a fundamental shift in how these resources are managed. More precisely, resource management programs must embrace a new paradigm, one with realtime environmental monitoring at its core. The Intelligent River© is an environmental and hydrological observation system engineered to support research and management of water resources at watershed scales. The system architecture is comprised of three primary tiers: (i) a field-deployed sensor fabric and uplink infrastructure, (ii) real-time data streaming middleware, and (iii) repository, presentation, and web services. Sensor Web Enablement (SWE) adoption decisions revolve around balancing efficiency concerns and implementation time with capability and standards compliance. In this context, our team has examined, applied, and evaluated SWE technologies to enable data archival, access, and discovery. We have found varying levels of success with SWE adoption across the three tiers. At the fabric layer, platform configurability and ease-of-integration have been important engineering drivers. SensorML arose as a natural candidate solution; however, its resource requirements are largely incompatible with our target hardware platforms. At the middleware layer, recent efforts have focused on the use of SensorML and a metadata catalog to perform metadata annotation. This solution appends SensorML elements onto incoming observations, supporting data processing and semantic resolution. During early development of middleware technologies, we linked sensor platforms with web services using the transactional profile of the Sensor Observation Service (SOS) to perform data insertion and retrieval queries. At the application level, SOS is used to support data discovery and access, and Sensor Alert Service (SAS) is used to provide near-real time notifications of sensor status and QA/QC failures. In this paper, we report on our experiences, both positive and negative, and outline potential solutions to some of the most important obstacles we have encountered.

Impacts of Land Disturbance on Aquatic Ecosystem Health: Quantifying the Cascade of Events

ABSTRACT The impacts of land disturbance on streams have been studied extensively, but a quantitative mechanism of stream degradation is still lacking. Small changes in land use result in changes in physical and chemical characteristics in the stream, which significantly alter biotic integrity. The objective of this study was to quantify the mechanisms of aquatic ecosystem degradation in streams impacted by watershed urbanization. By quantifying the development level and the changes in the physical parameters of receiving streams, the effects of land use change can be illustrated in a conceptual model and evaluated using a traditional ecological risk assessment framework. Three 1st-order streams draining catchments undergoing varying stages of land development were examined in the upper Piedmont physiographic province of South Carolina, USA. A disturbance index was developed to quantify the changes in land use on a monthly basis. This normalized disturbance index (NDI) was quantitatively linked to an increase in the percentage of impervious cover, stormwater runoff, storm-event total suspended solid (TSS) concentrations, and the North Carolina biotic index (NCBI). The NDI was inversely related to a decline in habitat, median bed-sediment particle size, and benthic index of biotic integrity (BIBI). Unlike the percentage of impervious cover, the NDI facilitated the development of strategies for multiple scales of regulation. Predictive multivariate regressions were developed for storm-event TSS concentrations, the BIBI, and the NCBI. These regressions can be used to develop improved regulations for the effects of development and can lead to better implementation of best management practices, improved monitoring of land use change, and more sustainable development.

Spectral Measurements of Alfalfa/Grass Fields Related to Forage Properties and Species Composition

ABSTRACT The relationship between plant canopy reflectance and plant nutritive value has not been extensively investigated. The goal of this study was to relate spectral canopy reflectance to plant nutritive value and species composition. Multiple grass/alfalfa fields were analyzed using a field spectrometer, and then species composition, forage nutritive quality, and plant biomass were determined. Derivative analyses of spectra as well as narrow-band vegetation indices were used to examine the relationship between canopy reflectance and plant biophysical properties. Derivative analysis found a high correlation between high-order derivatives at multiple wavelengths and some plant properties, which include species composition and neutral detergent fiber (NDF). Wavelengths in the red region and between the red and near-infrared region of the spectrum showed the highest correlation in the derivative analysis. Analysis of whole canopy reflectance using spectroscopy may provide a quick, nondestructive method to determine plant characteristics.

Stable carbon and oxygen isotopes of soil carbonates at depth in the Russian Chernozem under different land use

Limited information is available about stable carbon and oxygen composition of soil carbonates at depth in the Russian Chernozem under different land use. This study was conducted to determine the stable isotope geochemistry of disseminated carbonates in the Russian Chernozem, one of the typical soils in grasslands. Three sites were sampled: a native grassland field (not cultivated for at least 300 years), an adjacent 50-year continuous fallow field in the V.V. Alekhin Central-Chernozem Biosphere State Reserve in the Kursk region of Russia, and a continuously cropped field in the Experimental Station of the Kursk Institute of Agronomy and Soil Erosion Control. All sampled soils were classified as fine-silty, mixed, frigid Pachic Hapludolls. The stable carbon isotope composition of carbonates varied with depth and land use: in the native grassland field &dgr;13C was in the range of −6.1−(−7.7)‰; in the continuous fallow &dgr;13C was in the range of −5.7−(−9.8)‰ Pee Dee Belemnite (PDB); and in a continuously cropped field &dgr;13C was in the range of −5.1−(−10.2)‰ PDB. The stable oxygen isotope composition of carbonates also varied with depth and land use: in the native grassland field &dgr;18O was in the range of −6.9−(−9.4)‰; in the continuous fallow &dgr;18O was in the range of −6.2−(−10.7)‰; and in a continuously cropped field &dgr;18O was in the range of −7.0−(−9.4)‰. More research is needed to investigate the effect of cultivation on stable isotope signatures of pedogenic carbonates.

Examining the impacts of changing land use on biological integrity in streams using Geographical Information Systems and statistical modeling

Land-use activities and land cover of a watershed influence chemical and physical properties of streams which may impact the biota of the aquatic ecosystem. This study was designed to investigate the impacts of the conversion of forests to urbanized land, including construction and development impacts of land use conversion on water quality and biological integrity of streams. Land use and land cover changes, habitat conditions, water quality, and sediment loadings were studied in eleven subwatersheds of the Reedy River Watershed in the South Carolina Piedmont Ecoregion. Physical and chemical datasets and land use data were used as inputs to build a multivariate model using stepwise multiple regression to predict two instream biological dependant metrics, including Biotic Index, Final Bioclassification, and two biotic metrics that measure richness and species composition. Univariate statistical analysis among 25 environmental variables and biological indices indicated that watersheds of stable land use differed significantly from watersheds undergoing conversion of forest to urban land uses. Significant correlations were observed between land use and particle size distribution, land use and in-stream physical parameters, and land use and in-stream chemical variables. Multivariate statistical analysis indicated that the principle environmental factors correlated with biological responses were conductivity, land use, and substrate distribution. Significant correlations between Biotic Index, Final Bioclassification, and compositional measures were found with conductivity, suggesting that conductivity may be a good indicator of land use changes and thus a good predictor of biotic indices in these subwatersheds.