WATER QUALITY IMPROVEMENT PROGRAM EFFECTIVENESS FOR CARBONATE AQUIFERS IN GRAZED LAND WATERSHEDS1

ABSTRACT: Water quality indicators of two agriculturally impacted karst areas in southeastern West Virginia were studied to determine the water quality effects of grazing agriculture and water quality trends following initiation of water quality improvement programs. Both areas are tributaries of the Greenbrier River and received funding for best management practices under the President's Initiative for Water Quality and then under the Environmental Quality Incentives Program (EQIP). After 11 years of study there was little evidence to suggest that water quality improved in one area. Three and a half years of study in the other area showed little evidence of consistent water quality improvement under EQIP. Lack of consistent water quality improvement at the catchment scale does not imply that the voluntary programs were failures. Increased livestock numbers as a result of successful changes in forage management practices may have overridden water quality improvements achieved through best management practices. Practices that target well defined contributing areas significantly impacting aquifer water quality might be one way to improve water quality at catchment scales in karst basins. For example, a significant decrease in fecal coliform concentrations was observed in subterranean drainage from one targeted sinkhole after dairy cattle were permanently excluded from the sinkhole.     

SUMMER LOW FLOWS IN NEW ENGLAND DURING THE 20TH CENTURY1

ABSTRACT: High springtime river flows came earlier by one to two weeks in large parts of northern New England during the 20th Century. In this study it was hypothesized that late spring/early summer recessional flows and late summer/early fall low flows could also be occurring earlier. This could result in a longer period of low flow recession and a decrease in the magnitude of low flows. To test this hypothesis, variations over time in the magnitude and timing of low flows were analyzed. To help understand the relation between low flows and climatic variables in New England, low flows were correlated with air temperatures and precipitation. Analysis of data from 23 rural, unregulated rivers across New England indicated little evidence of consistent changes in the timing or magnitude of late summer/early fall low flows during the 20th Century. The interannual variability in the timing and magnitude of the low flows in northern New England was explained much more by the interannual variability in precipitation than by the interannual variability of air temperatures. The highest correlation between the magnitude of the low flows and air temperatures was with May through November temperatures (r =?0.37, p= 0.0017), while the highest correlation with precipitation was with July through August precipitation (r = 0.67, p > 0.0001).     

MODELING THE DISTRIBUTION OF DIFFUSE NITROGEN SOURCES AND SINKS IN THE NEUSE RIVER BASIN OF NORTH CAROLINA,USA1

This study quantified nonpoint source nitrogen (NPS‐N) sources and sinks across the 14,582 km² Neuse River Basin (NRB) located in North Carolina, to provide tabular data summaries and graphic overlay products to support the development of management approaches to best achieve established N reduction goals. First, a remote sensor derived, land cover classification was performed to support modeling needs. Modeling efforts included the development of a mass balance model to quantify potential N sources and sinks, followed by a precipitation event driven hydrologic model to effectively transport excess N across the landscape to individual stream reaches to support subsequent labeling of transported N values corresponding to source origin. Results indicated that agricultural land contributed 55 percent of the total annual NPS‐N loadings, followed by forested land at 23 percent (background), and urban areas at 21 percent. Average annual N source contributions were quantified for agricultural (1.4 kg/ha), urban (1.2 kg/ha), and forested cover types (0.5 kg/ha). Nonpoint source‐N contributions were greatest during the winter (40 percent), followed by spring (32 percent), summer (28 percent), and fall (0.3 percent). Seasonal total N loadings shifted from urban dominated and forest dominated sources during the winter, to agricultural sources in the spring and summer. A quantitative assessment of the significant NRB land use activities indicated that high (greater than 70 percent impervious) and medium (greater than 35 percent impervious) density urban development were the greatest contributors of NPS‐N on a unit area basis (1.9 and 1.6 kg/ha/yr, respectively), followed by row crops and pasture/hay cover types (1.4 kg/ha/yr).     

BASE FLOW RECESSION RATES,LOW FLOWS,AND HYDROLOGIC FEATURES OF SMALL WATERSHEDS IN PENNSYLVANIA,USA1

This paper examines the relationships between measurable watershed hydrologic features, base flow recession rates, and the Q_7,10 low flow statistic (the annual minimum seven‐day average streamflow occurring once every 10 years on average). Base flow recession constants were determined by analyzing hydrograph recession data from 24 small (>130 km²), unregulated watersheds across five major physiographic provinces of Pennsylvania, providing a highly variable dataset. Geomorphic, hydrogeologic, and land use parameters were determined for each watershed. The base flow recession constant was found to be most strongly correlated to drainage density, geologic index, and ruggedness number (watershed slope); however, these three parameters are intercorrelated. Multiple regression models were developed for predicting the recession rate, and it was found that only two parameters, drainage density and hydrologic soil group, were required to obtain good estimates of the recession constant. Equations were also developed to relate the recession rates to Q_7,10 per unit area, and to the Q_7,10/Q₅₀ ratio. Using these equations, estimates of base flow recession rates, Q_7,10, and streamflow reduction under drought conditions can be made for small, ungaged basins across a wide range of physiography.     

Erratum to: Accumulation of Cr,Cd, Pb,Cu, and Zn by plants in tanning sludge storage sites: opportunities for contamination bioindication and phytoremediation

Environmental Science and Pollution Research -     

Pollutant concentration profile reconstruction using digital soft sensors for biodegradation and exposure assessment in the presence of model uncertainty

A new approach to the problem of environmental hazard assessment and monitoring for pollutant biodegradation reaction systems in the presence of uncertainty is proposed using soft sensor-based pollutant concentration dynamic profile reconstruction techniques. In particular, a robust reduced-order soft sensor is proposed that can be digitally implemented in the presence of inherent complexity and the inevitable model uncertainty. The proposed method explicitly incorporates all the available information associated with a process model characterized by varying degrees of uncertainty, as well as available sensor measurements of certain physicochemical quantities. Based on the above information, a reduced-order soft sensor is designed enabling the reliable reconstruction of pollutant concentration profiles in complex biodegradation systems that can not be always achieved due to physical and/or technical limitations associated with current sensor technology. The option of using the aforementioned approach to compute toxic load and persistence indexes on the basis of the reconstructed concentration profiles is also pursued. Finally, the performance of the proposed method is evaluated in two illustrative environmental hazard assessment case studies.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

Population Structure of Sable in the Baikal Mountain Land: Analysis of Genetic and Phenotypic Traits

Russian Journal of Ecology - The genetic and phenotypic structure (according to the fur color) of 14 sable samples from the Baikal mountain land (BML) has been studied by analyzing 257 animals for...     

Suicide by crashing into a heavy vehicle: Focus on professional drivers using in-depth crash data

Objective: Road traffic suicides typically involve a passenger car driver crashing his or her vehicle into a heavy vehicle, because death is almost certain due to the large mass difference between these vehicles. For the same reason, heavy-vehicle drivers typically suffer minor injuries, if any, and have thus received little attention in the research literature. In this study, we focused on heavy-vehicle drivers who were involved as the second party in road suicides in Finland.

Methods: We analyzed 138 road suicides (2011–2016) involving a passenger car crashing into a heavy vehicle. We used in-depth road crash investigation data from the Finnish Crash Data Institute.

Results: The results showed that all but 2 crashes were head-on collisions. Almost 30% of truck drivers were injured, but only a few suffered serious injuries. More than a quarter reported sick leave following their crash. Injury insurance compensation to heavy-vehicle drivers was just above €9,000 on average. Material damage to heavy vehicles was significant, with average insurance compensation paid being €70,500. Three out of 4 truck drivers reported that drivers committing suicide acted abruptly and left them little opportunity for preventive action.

Conclusions: Suicides by crashing into heavy vehicles can have an impact on drivers’ well-being; however, it is difficult to see how heavy-vehicle drivers could avoid a suicide attempt involving their vehicle.