THE POTENTIAL FOR REMOTE SENSING OF LOESS SOILS SUSPENDED IN SURFACE WATERS1

ABSTRACT: The potential for detecting the concentration and type of soils suspended in surface water through remote sensing techniques was investigated by studying the spectral reflectance of two types of soils in suspension. In a large tank filled with 7510 liters of water, 20 levels of suspended sediment (soil) concentration (SSC), ranging from 50 to 1000 mg/l were prepared. A high resolution spectroradiometer was used to measure the reflectance at each SSC level. The reflectance spectra of two contrasting soils were distinct in the visible and near infrared (NIR) portions of the electromagnetic spectrum. The wavelength range between 580–690 nm (visible) was found to be optimal for indicating the type of soil, whereas, the wavelength range between 714–880 (NIR) was found to be appropriate for estimating the concentration of sediment suspended in surface waters.     

Nitrate removal in a riparian wetland of the Appalachian Valley and Ridge physiographic province

Riparian zones within the Appalachian Valley and Ridge physiographic province are often characterized by localized variability in soil moisture and organic carbon content, as well as variability in the distribution of soils formed from alluvial and colluvial processes. These sources of variability may significantly influence denitrification rates. This investigation studied the attenuation of nitrate (NO3- -N) as wastewater effluent flowed through the shallow ground water of a forested headwater riparian zone within the Appalachian Valley and Ridge physiographic province. Ground water flow and NO3- -N measurements indicated that NO3- -N discharged to the riparian zone preferentially flowed through the A and B horizons of depressional wetlands located in relic meander scars, with NO3- -N decreasing from > 12 to < 0.5 mg L(-1). Denitrification enzyme activity (DEA) attributable to riparian zone location, soil horizon, and NO3- -N amendments was also determined. Mean DEA in saturated soils attained values as high as 210 microg N kg(-1) h(-1), and was significantly higher than in unsaturated soils, regardless of horizon (p < 0.001). Denitrification enzyme activity in the shallow A horizon of wetland soils was significantly higher (p < 0.001) than in deeper soils. Significant stimulation of DEA (p = 0.027) by N03- -N amendments occurred only in the meander scar soils receiving low NO3- -N (<3.6 mg L(-1)) concentrations. Significant denitrification of high NO3- -N ground water can occur in riparian wetland soils, but DEA is dependent upon localized differences in the degree of soil saturation and organic carbon content.     

Effects of Light Zenith Angle Variation on Spectral Responses of a Water Body’s Environmental Quality

The effect of light source zenith angle (θ_z) variation on the spectral reflectance measurement from sediment-laden water was studied in the laboratory using a spectroradiometer. Light source zenith angle in addition to sediment characteristics and concentration play a dominant role in affecting the reflectance characteristics of a suspension. With an increase in θ_z values, an increase in spectral reflectance is observed. The spectral reflectance characteristics of a water body also increase with the sediment concentration for all soil types and at all wavelengths. Empirical relationships between the spectral reflectance, suspended sediment concentration, and the light source zenith angle have been developed. Such a remote sensing technique for monitoring the concentration of the suspended sediment and their characteristics is a useful tool for economical estimation of a large water body’s quality related parameters vis-a-vis its environmental quality.Retd. Professor of Environmental Engineering & Pollution Control, Presently Residing at Makkhan Kutir, Bhargava Lane, Devpura, Haridwar-249401, India.Former Ph.D. student.     

Near- and mid-infrared diffuse reflectance spectroscopy for measuring soil metal content

Rapid and nondestructive methods such as diffuse reflectance infrared spectroscopy provide potentially useful alternatives to time-consuming chemical methods of soil metal analysis. To assess the utility of near-infrared reflectance spectroscopy (NIRS) and diffuse mid-infrared reflectance spectroscopy (DRIFTS) for soil metal determination, 70 soil samples from the metal mining region of Tarnowskie Gory (Upper Silesia, Poland) were analyzed by both chemical and spectroscopic methods. Soils represented a wide range of pH (4.0-8.0), total carbon (5.1-73.2 g kg(-1)), and textural classes (from sand to silty clay loam). Soils had various contents of metals (14-4500 mg kg(-1) for Zn, 18-6530 mg kg(-1) for Pb, and 0.17-34 mg kg(-1) for Cd), ranging from natural background levels to high contents indicative of industrial contamination in the region. Soil samples were scanned at the wavelengths from 400 to 2498 nm (near-infrared region) and from 2500 to 25000 nm (mid-infrared region). Calibrations were developed using the one-out validation procedure under partial least squares (PLS) regression. Mid-infrared spectroscopy markedly outperformed NIRS. Iron, Cd, Cu, Ni, and Zn were successfully predicted using DRIFTS. The coefficients of determination (R(2)) between actual and predicted contents were 0.97, 0.94, 0.80, 0.99, and 0.96 for those metals, respectively. Only Pb content was predicted poorly. Calibrations using NIRS were less accurate. Root mean squared deviation (RMSD) values were from 1.27 (Pb) to 3.3 (Ni) times higher for NIRS than for DRIFTS. Results indicate that DRIFTS may be useful for accurate predictions of metals if samples originate from one region.     

FORESTED WETLANDS IN EASTERN CONNECTICUT: THEIR TRANSITION ZONES AND DELINEATION1

ABSTRACT: The delineation of inland wetlands requires close field examination of the biological and physical gradients (transition zones) between wetlands and bordering uplands. As part of a study on the detection and delineation of inland wetlands in eastern Connecticut by remote sensing techniques, this effort was designed to investigate vegetation distribution and composition and selected physical and chemical properties of the soils of wetland to upland transition zones in deciduous wetland forests. Field research was conducted during the growing season of 1975 within a test area consisting of the 45 mi² Town of Mansfield, Connecticut. Changes in vegetation composition and structure, soil pH, and soil water content were determined along line transects extended over wetland to upland transition zones. Differences in soil pH occurred along the transects but were of such magnitude that they probably have little impact on plant distribution. There were significant changes in soil water content along the wetland to upland gradients. Discriminant analysis applied to statistical “index of abundance” data describing vegetation distribution among the various zones (wetland, transition, upland) showed which plant species best distinguish wetlands from uplands. Of the criteria studied, vegetation composition and distribution, soil water content, and relief are the most useful criteria for delineating deciduous wetland forests.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Hyperspectral reflectance response of freshwater macrophytes to salinity in a brackish subtropical marsh

Coastal freshwater wetlands are threatened by increased salinity due to relative sea level rise and reduced freshwater inputs. Remote radiometric measurement of freshwater marsh canopies to detect small shifts in water column salinity would be useful for assessing salinity encroachment. We measured leaf hyperspectral (300-1100 nm) reflectance of freshwater macrophytes (cattail, Typha latifolia and sea oxeye, Borrichia frutescens) in a field study in a subtropical brackish (2.5-4.5 parts per thousand salinity, per thousand) marsh to determine salinity effects on visible and near-infrared spectral band reflectance and to identify reflectance indices sensitive to small (1 per thousand) changes in wetland salinity. For sea oxeye, floating-position water band index [fWBI = R(900)/minimum(R(930) - R(980)), where R(lambda) = reflectance at band lambda], normalized difference vegetation index [NDVI = (R(774) - R(681))/(R(774) + R(681))], and a proposed wetland salinity reflectance ratio (WSRR = R(990)/R(933)) were sensitive to salinity with R2 of 40, 35, and 65%, respectively (p < 0.01). For cattail, NDVI and photochemical reflectance index [PRI = (R(531) - R(570))/(R(570) + R(531))] were sensitive to salinity with R2 of 29 and 33%, respectively (p 相似文献   

A spatially explicit investigation of phosphorus sorption and related soil properties in two riparian wetlands

Soils of riparian wetlands are highly effective at phosphorus (P) sorption. However, these soils exhibit extreme spatial variability across riparian zones. We used a spatially explicit sampling design in two riparian wetlands in North Carolina to better understand the relationships among P sorption, soil properties, and spatial variability. Our objectives were to quantify patterns of spatial variability of P sorption and related soil properties, and to determine which soil properties best explained the variability in P sorption after accounting for the effects of spatial autocorrelation. We measured bulk density, moisture, pH, soil organic matter (SOM), texture (percent clay, silt, and sand), oxalate-extractable aluminum (Al(ox)), iron (Fe(ox)), and the phosphorus sorption index (PSI). Due to differences in texture, Al(ox), and Fe(ox), the two sites had substantially different mean PSIs. At each site, we found considerable differences in the spatial variability of soil properties. For example, semivariance analysis and kriging illustrated that soil properties at Site 1 varied at smaller scales than those at Site 2. At both sites, after accounting for the effects of spatial autocorrelation and all other soil properties, we determined that Al(ox) had the highest Mantel correlation with PSI. We believe this geostatistic and Mantel approach is robust and could serve as a model for research on other biogeochemical processes such as denitrification.     

Carbon storage by urban soils in the United States

We used data available from the literature and measurements from Baltimore, Maryland, to (i) assess inter-city variability of soil organic carbon (SOC) pools (1-m depth) of six cities (Atlanta, Baltimore, Boston, Chicago, Oakland, and Syracuse); (ii) calculate the net effect of urban land-use conversion on SOC pools for the same cities; (iii) use the National Land Cover Database to extrapolate total SOC pools for each of the lower 48 U.S. states; and (iv) compare these totals with aboveground totals of carbon storage by trees. Residential soils in Baltimore had SOC densities that were approximately 20 to 34% less than Moscow or Chicago. By contrast, park soils in Baltimore had more than double the SOC density of Hong Kong. Of the six cities, Atlanta and Chicago had the highest and lowest SOC densities per total area, respectively (7.83 and 5.49 kg m(-2)). On a pervious area basis, the SOC densities increased between 8.32 (Oakland) and 10.82 (Atlanta) kg m(-2). In the northeastern United States, Boston and Syracuse had 1.6-fold less SOC post- than in pre-urban development stage. By contrast, cities located in warmer and/or drier climates had slightly higher SOC pools post- than in pre-urban development stage (4 and 6% for Oakland and Chicago, respectively). For the state analysis, aboveground estimates of C density varied from a low of 0.3 (WY) to a high of 5.1 (GA) kg m(-2), while belowground estimates varied from 4.6 (NV) to 12.7 (NH) kg m(-2). The ratio of aboveground to belowground estimates of C storage varied widely with an overall ratio of 2.8. Our results suggest that urban soils have the potential to sequester large amounts of SOC, especially in residential areas where management inputs and the lack of annual soil disturbances create conditions for net increases in SOC. In addition, our analysis suggests the importance of regional variations of land-use and land-cover distributions, especially wetlands, in estimating urban SOC pools.     

Aerospace wetland monitoring by hyperspectral imaging sensors: a case study in the coastal zone of San Rossore Natural Park

The San Rossore Natural Park, located on the Tuscany (Italy) coast, has been utilized over the last 10 years for many remote sensing campaigns devoted to coastal zone monitoring. A wet area is located in the south-west part of the Natural Park and it is characterized by a system of ponds and dunes formed by sediment deposition occurring at the Arno River estuary. The considerable amount of collected data has permitted us to investigate the evolution of wetland spreading and land coverage as well as to retrieve relevant biogeochemical parameters, e.g. green biomass, from remote sensing images and products. This analysis has proved that the monitoring of coastal wetlands, characterized by shallow waters, moor and dunes, demands dedicated aerospace sensors with high spatial and spectral resolution. The outcomes of the processing of images gathered during several remote sensing campaigns by airborne and spaceborne hyperspectral sensors are presented and discussed. A particular effort has been devoted to sensor response calibration and data validation due to the complex heterogeneity of the observed natural surfaces.     

Temporal and spatial development of surface soil conditions at two created riverine marshes

The amount of time it takes for created wetlands to develop soils comparable to natural wetlands is relatively unknown. Surface soil changes over time were evaluated in two created wetlands (approximately 1 ha each) at the Olentangy River Wetland Research Park in Columbus, Ohio. The two wetlands were constructed in 1993 to be identical in size and geomorphology, and maintained to have the same hydrology. The only initial difference between the wetlands was that one was planted with native macrophytes while the other was not. In May 2004, soil samples were collected (10 yr and 2 mo after the wetlands were flooded) and compared to samples collected in 1993 (after the wetlands were excavated but before flooding) and 1995 (18 mo after the wetlands were flooded). In all three years, soils were split into surface (0-8 cm) and subsurface (8-16 cm) depths and analyzed for soil organic matter, total C, total P, available P, exchangeable cations, and pH. Soils in the two wetlands have changed substantially through sedimentation and organic accretion. Between 1993 and 1995, soils were most influenced by the deposition of senescent macroalgae, the mobilization of soluble nutrients, and the precipitation of CaCO(3). Between 1995 and 2004, soil parameters were influenced more by the deposition of organic matter from colonized macrophyte communities. Mean percent organic matter at the surface increased from 5.3 +/- 0.1% in 1993, 6.1 +/- 0.2% in 1995, to 9.5 +/- 0.2% in 2004. Mean total P increased from 493 +/- 18 microg g(-1) in 1993, 600 +/- 23 microg g(-1) in 1995, to 724 +/- 20 microg g(-1) in 2004. Spatial analyses of percent organic matter (a commonly used indicator of hydric soil condition) at both wetlands in 1993, 1995, and 2004 showed that soil conditions have become increasingly more variable. High spatial structure (autocorrelation) between data points was detected in 1993 and 2004, with data in 2004 exhibiting a much higher overall variance and narrower range of spatial structure than in 1993.     

Evaluation of the European Space Agency Climate Change Initiative Soil Moisture Product over China Using Variance Reduction Factor

In this study, we evaluated the European Space Agency Climate Change Initiative soil moisture product v02.1 (ESA CCI SM v02.1) using in situ observations collected at 547 stations in China from 1991 to 2013. A conventional validation was first conducted, and the triple collocation errors of ESA CCI SM and the European Centre for Medium Range Weather Forecasting reanalysis data were approximately 0.053 and 0.050 m³/m³, respectively. To obtain more reliable validation results, the average soil moisture of the in situ observations per ESA CCI SM pixel was also used as the validation sites. Variance reduction factor (VRF) was adopted to quantify the accuracy of the soil moisture validation sites, and the average VRF was estimated at 4.88%. The validation results were enhanced by excluding validation sites with VRF errors greater than 5% from the statistical analysis. Although the ESA CCI SM underestimated the in situ observations with a Bias of 0.05 m³/m³, a moderately high correlation coefficient of 0.44 and a relatively small unbiased root‐mean‐square difference of 0.05 m³/m³ were observed. This study provides information on the utilization of ESA CCI SM for ecological protection, climate change, and hydrological forecasting. It also suggests the adoption of VRF for future error corrections of satellite‐based products.     

Connectivity of Streams and Wetlands to Downstream Waters: An Integrated Systems Framework

Interest in connectivity has increased in the aquatic sciences, partly because of its relevance to the Clean Water Act. This paper has two objectives: (1) provide a framework to understand hydrological, chemical, and biological connectivity, focusing on how headwater streams and wetlands connect to and contribute to rivers; and (2) briefly review methods to quantify hydrological and chemical connectivity. Streams and wetlands affect river structure and function by altering material and biological fluxes to the river; this depends on two factors: (1) functions within streams and wetlands that affect material fluxes; and (2) connectivity (or isolation) from streams and wetlands to rivers that allows (or prevents) material transport between systems. Connectivity can be described in terms of frequency, magnitude, duration, timing, and rate of change. It results from physical characteristics of a system, e.g., climate, soils, geology, topography, and the spatial distribution of aquatic components. Biological connectivity is also affected by traits and behavior of the biota. Connectivity can be altered by human impacts, often in complex ways. Because of variability in these factors, connectivity is not constant but varies over time and space. Connectivity can be quantified with field‐based methods, modeling, and remote sensing. Further studies using these methods are needed to classify and quantify connectivity of aquatic ecosystems and to understand how impacts affect connectivity.     

Quantitative assessment of tidal wetlands using remote sensing

Effective management of tidal wetlands requires periodic data on the boundaries, extent, and condition of the wetlands. In many states, wetlands are defined wholly, or in combination with other criteria, by the presence of particular emergent halophytic plants. Many important characteristics of the wetlands ecosystem are related directly to the production of emergent plant material or may be inferred from knowledge of the distribution of emergent plant species. Remote-sensing techniques have been applied to mapping of the distribution of wetland vegetation but not to quantitative evaluation of the condition of that vegetation.Recent research in the tidal wetlands of Delaware and elsewhere has shown that spectral canopy reflectance properties can be quantitatively related to the emergent green biomass ofSpartina alterniflora (salt marsh cord grass) throughout the peak growing season (April through September, in Delaware). Periodic measurements of this parameter could be applied to calculations of net aerial primary productivity for large areas ofS. alterniflora marsh in which conventional harvest techniques may be prohibitively time consuming. The method is species specific and, therefore, requires accurate discrimination ofS. alterniflora from other vegetation types. Observed seasonal changes in species spectral signatures are shown to have potential for improving multispectral categorization of tidal wetland vegetation types.     

SOIL EROSION AND SEDIMENT YIELD PREDICTION ACCURACY USING WEPP1

ABSTRACT: The objectives of this paper are to discuss expectations for the Water Erosion Prediction Project (WEPP) accuracy, to review published studies related to WEPP goodness of fit, and to evaluate these in the context of expectations for WEPP's goodness of fit. WEPP model erosion predictions have been compared in numerous studies to observed values for soil loss and sediment delivery from cropland plots, forest roads, irrigated lands and small watersheds. A number of different techniques for evaluating WEPP have been used, including one recently developed where the ability of WEPP to accurately predict soil erosion can be compared to the accuracy of replicated plots to predict soil erosion. In one study involving 1,594 years of data from runoff plots, WEPP performed similarly to the Universal Soil Loss Erosion (USLE) technology, indicating that WEPP has met the criteria of results being “at least as good with respect to observed data and known relationships as those from the USLE,” particularly when the USLE technology was developed using relationships derived from that data set, and using soil erodibility values measured on those plots using data sets from the same period of record. In many cases, WEPP performed as well as could be expected, based on comparisons with the variability in replicate data sets. One major finding has been that soil erodibility values calculated using the technology in WEPP for rainfall conditions may not be suitable for furrow irrigated conditions. WEPP was found to represent the major storms that account for high percentages of soil loss quite well—a single storm application that the USLE technology is unsuitable for—and WEPP has performed well for disturbed forests and forest roads. WEPP has been able to reflect the extremes of soil loss, being quite responsive to the wide differences in cropping, tillage, and other forms of management, one of the requirements for WEPP validation. WEPP was also found to perform well on a wide range of small watersheds, an area where USLE technology cannot be used.     

Does Including Soil Moisture Observations Improve Operational Streamflow Forecasts in Snow‐Dominated Watersheds?

Changing climate and growing water demand are increasing the need for robust streamflow forecasts. Historically, operational streamflow forecasts made by the Natural Resources Conservation Service have relied on precipitation and snow water equivalent observations from Snow Telemetry (SNOTEL) sites. We investigate whether also including SNOTEL soil moisture observations improve April‐July streamflow volume forecast accuracy at 0, 1, 2, and 3‐month lead times at 12 watersheds in Utah and California. We found statistically significant improvement in 0 and 3‐month lead time accuracy in 8 of 12 watersheds and 10 of 12 watersheds for 1 and 2‐month lead times. Surprisingly, these improvements were insensitive to soil moisture metrics derived from soil physical properties. Forecasts were made with volumetric water content (VWC) averaged from October 1 to the forecast date. By including VWC at the 0‐month lead time the forecasts explained 7.3% more variability and increased the streamflow volume accuracy by 8.4% on average compared to standard forecasts that already explained an average 77% of the variability. At 1 to 3‐month lead times, the inclusion of soil moisture explained 12.3‐26.3% more variability than the standard forecast on average. Our findings indicate including soil moisture observations increased statistical streamflow forecast accuracy and thus, could potentially improve water supply reliability in regions affected by changing snowpacks.     

Soil quality at a national scale in New Zealand

New Zealand is a signatory to international conventions on environmental performance, and soil quality information is needed for reporting both at a national and regional level. Soil quality was measured at 222 sites in five regions of New Zealand (12 soil orders and 9 land-use categories). Topsoil (0-100 mm) properties measured were total carbon and nitrogen, potentially mineralizable N, pH, Olsen P, cation exchange capacity, bulk density, total porosity, macroporosity, and total available and readily available water. Our objectives were to gauge the representativeness of the sample, determine the contribution from land use or soil order to variability, rationalize the data set, and identify concerns for long-term sustainable land use. Soil and land use combinations were both under- or overrepresented in the data set compared with national distribution. Soil order and land-use categories explained 55 to 76% of the variance in soil properties. Total C contents of pastures were comparable with indigenous forest soils, but pastures were less acidic and with higher N and P contents. Plantation forests had characteristics similar to indigenous forests on comparable soils. Cropland soils comprised <1% of the national land cover and generally had high inorganic fertility and low organic matter, with evidence of compaction. Seven characteristics (total C, total N, mineralizable N, pH, Olsen P, bulk density, and macroporosity) explained 87% of the total variability. The findings are being used by monitoring agencies to raise awareness about soil quality in the wider community, set land management guidelines, and develop policies.     

Phytoremediation of polycyclic aromatic hydrocarbons in manufactured gas plant-impacted soil

Contamination of soil by hazardous substances poses a significant threat to human, environmental, and ecological health. Cleanup of the contaminants using destructive, invasive technologies has proven to be expensive and more importantly, often damaging to the natural resource properties of the soil, sediment, or aquifer. Phytoremediation is defined as the cleanup of contaminated sites using plants. There has been evidence of enhanced polycyclic aromatic hydrocarbons (PAHs) degradation in rhizosphere soils for a limited number of plants. However, research focusing on the degradation of PAHs in the rhizosphere of trees is lacking. The objective of this study was to assess the potential use of trees to enhance degradation of PAHs located in manufactured gas plant-impacted soils. In greenhouse studies with intact soil cores, acenaphthene, anthracene, fluoranthene, naphthalene, and phenanthrene decreased significantly (p < 0.05) in green ash (Fraxinus pennsylvanica Marshall) and hybrid poplar (Populus deltoides x P. nigra DN 34) phytoremediation treatments when compared to the unplanted soil control. Increases in PAH microbial degraders in rhizosphere soil were observed when compared to unvegetated soil controls. In addition, the rate of degradation or biotransformation of PAHs was greatest for soils with black willow (Salix nigra Marshall), followed by poplar, ash, and the unvegetated controls. These results support the hypothesis that a variety of plants can enhance the degradation of target PAHs in soil.     

Weathering of lead bullets and their environmental effects at outdoor shooting ranges

Lead contamination at shooting range soils is of great environmental concern. This study focused on weathering of lead bullets and its effect on the environment at five outdoor shooting ranges in Florida, USA. Soil, plant, and water samples were collected from the ranges and analyzed for total Pb and/or toxicity characteristic leaching procedure (TCLP) Pb. Selected bullet and berm soil samples were mineralogically analyzed with X-ray diffraction and scanning electron microscopy. Hydrocerussite [Pb3(CO3)2(OH)2] was found in both the weathered crusts and berm soils in the shooting ranges with alkaline soil pH. For those shooting ranges with acidic soil pH, hydrocerussite, cerussite (PbCO3), and small amount of massicot (PbO) were predominantly present in the weathered crusts, but no lead carbonate mineral was found in the soils. However, hydroxypyromorphite [(Pb10(PO4)6(OH)2] was formed in a P-rich acidic soil, indicating that hydroxypyromorphite can be a stable mineral in P-rich shooting range soil. Total Pb and TCLP Pb in the soils from all five shooting ranges were significantly elevated with the highest total Pb concentration of 1.27 to 4.84% (w/w) in berm soils. Lead concentrations in most sampled soils exceeded the USEPA's critical level of 400 mg Pb kg(-1) soil. Lead was not detected in subsurface soils in most ranges except for one, where elevated Pb up to 522 mg kg(-1) was observed in the subsurface, possibly due to enhanced solubilization of organic Pb complexes at alkaline soil pH. Elevated total Pb concentrations in bermudagrass [Cynodon dactylon (L.) Pers.] (up to 806 mg kg(-1) in the aboveground parts) and in surface water (up to 289 microg L(-1)) were observed in some ranges. Ranges with high P content or high cation exchange capacity showed lower Pb mobility. Our research clearly demonstrates the importance of properly managing shooting ranges to minimize adverse effects of Pb on the environment.     

Using remote sensing technique to study soil sedimentation flow

Soils will behave differently when used for agriculture, forestry, and other purposes and must be managed differently. The difference is most evident in the Inverbrackie Creek catchment area in South Australia where the study reported in this article was conducted and where the soils are used extensively for grazing and dairy farming. This catchment covers an area of 8.38 km², comprising an undulating upland plain with irregularly high hills and broad interfluves. Previous information-gathering methods used to model the catchment's hydrologic activity have been derived from the downstream pluviographic point-source technique. The model input samples obtained by this technique are not truly representative of the catchment. The potential for using remote sensing color infrared imagery to delineate the areas contributing to soil sediment flow is demonstrated as a better alternative to obtaining representative samples to model this activity. This article reports on part of the work supported by the University Research Grant, University of Adelaide.