Nitrate-nitrogen losses through subsurface drainage under various agricultural land covers

Nitrate-nitrogen (NO?-N) loading to surface water bodies from subsurface drainage is an environmental concern in the midwestern United States. The objective of this study was to investigate the effect of various land covers on NO?-N loss through subsurface drainage. Land-cover treatments included (i) conventional corn ( L.) (C) and soybean [ (L.) Merr.] (S); (ii) winter rye ( L.) cover crop before corn (rC) and before soybean (rS); (iii) kura clover ( M. Bieb.) as a living mulch for corn (kC); and (iv) perennial forage of orchardgrass ( L.) mixed with clovers (PF). In spring, total N uptake by aboveground biomass of rye in rC, rye in rS, kura clover in kC, and grasses in PF were 14.2, 31.8, 87.0, and 46.3 kg N ha, respectively. Effect of land covers on subsurface drainage was not significant. The NO?-N loss was significantly lower for kC and PF than C and S treatments (p < 0.05); rye cover crop did not reduce NO?-N loss, but NO?-N concentration was significantly reduced in rC during March to June and in rS during July to November (p < 0.05). Moreover, the increase of soil NO?-N from early to late spring in rS was significantly lower than the S treatment (p < 0.05). This study suggests that kC and PF are effective in reducing NO?-N loss, but these systems could lead to concerns relative to grain yield loss and change in farming practices. Management strategies for kC need further study to achieve reasonable corn yield. The effectiveness of rye cover crop on NO-N loss reduction needs further investigation under conditions of different N rates, wider weather patterns, and fall tillage.     

Assessment of the overall resource consumption of germanium wafer production for high concentration photovoltaics

The overall resource requirements for the production of germanium wafers for III–V multi-junction solar cells applied in concentrator photovoltaics have been assessed based on up to date process information. By employing the cumulative energy demand (CED) method and the cumulative exergy extraction from the natural environment (CEENE) method the following resources have been included in the assessment: fossil resources, nuclear resources, renewable resources, land resources, atmospheric resources, metal resources, mineral resources and water resources. The CED has been determined as 216 MJ and the CEENE has been determined as 258 MJ_ex. In addition partial energy and exergy payback times have been calculated for the base case, which entails the installation of the high concentration photovoltaics (HCPVs) in the Southwestern USA, resulting in payback times of around 4 days for the germanium wafer production. Due to applying concentration technology the germanium wafer accounts for only 3% of the overall resource consumption of an HCPV system. A scenario analysis on the electricity input to the wafer production and on the country of installation of the HCPV has been performed, showing the importance of these factors on the cumulative resource consumption of the wafer production and the partial payback times.     

The Shallow‐Water Component of the Chesapeake Bay Environmental Model Package

The shallow‐water component of the Chesapeake Bay Environmental Model Package emphasizes the regions of the system inside the 2‐m depth contour. The model of these regions is unified with the system‐wide model but places emphasis on locally significant components and processes, notably submerged aquatic vegetation (SAV), sediment resuspension, and their interaction with light attenuation (Ke). The SAV model is found to be most suited for computing the equilibrium distribution of perennial species. Addition of plant structure and propagation are recommended to improve representation of observed trends in SAV area. Two approaches are taken to examining shallow‐water Ke. The first compares observed and computed differences between deep‐ and shallow‐water Ke. No consistent difference in observations is noted. In the preponderance of regions examined, computed shallow‐water Ke exceeds computed deep‐water Ke. The second approach directly compares Ke measured in shallow water with modeled results. Model values are primarily lower than observed, in contrast to results in deep water where model values exceed observed. The shortfall in computed Ke mirrors a similar shortfall in computed suspended solids. Improved model representation of Ke requires process‐based investigations into suspended solids dynamics as well as increased model resolution in shallow‐water regions.     

ASSESSMENT OF METHODS FOR MEASURING EMBEDDEDNESS: APPLICATION TO SEDIMENTATION IN FLOW REGULATED STREAMS1

Abstract: Five commonly used methods for measuring embeddedness the — degree to which fine particles surround coarse substrate on the surface of the streambed — are assessed and used to evaluate the sedimentation pattern resulting from impoundment on tributaries of the Connecticut River. Results show that the U.S. Environmental Protection Agency (USEPA) method best reflects the sediment regime on these rivers. On the Ompompanoosuc River, regulated by a run-of-the-river/flood control dam, embeddedness increases significantly directly downstream of the dam. On the unregulated White River, no downstream trends in embeddedness are observed. The USEPA results on the Ompompanoosuc River reflect the movement of a local decrease in embeddedness, interpreted as a moving region of scour, with a calculated transport rate of approximately 5 to 25 m/day. Observed transport rates are similar to previously measured sediment transport rates and consistent with results from a multifraction sediment transport model. Application of the USEPA method to an additional regulated tributary demonstrates the effects of dam management on embeddedness. Flow regulation with high sediment trapping efficiency results in a decrease in embeddedness downstream of the dam. Results provide insight into the utility of available methods for evaluating the effects of management practice on streambed composition.     

Incorporating green-area user groups in urban ecosystem management

We analyze the role of urban green areas managed by local user groups in their potential for supporting biodiversity and ecosystem services in growing city-regions, with focus on allotment areas, domestic gardens, and golf courses. Using Stockholm, Sweden, as an example cityregion, we compile GIS data of its spatial characteristics and relate these data to GIS data for protected areas and "green wedges" prioritized in biodiversity conservation. Results reveal that the three land uses cover 18% of the studied land area of metropolitan Stockholm, which corresponds to more than twice the land set aside as protected areas. We review the literature to identify ecosystem functions and services provided by the three green areas and discuss their potential in urban ecosystem management. We conclude that the incorporation of locally managed lands, and their stewards and institutions, into comanagement designs holds potential for improving conditions for urban biodiversity, reducing transaction costs in ecosystem management, and realizing local Agenda 21.     

Revisiting a statistical shortcoming when fitting the Langmuir model to sorption data

The Langmuir model is commonly used for describing the sorption behavior of reactive solutes to surfaces and is often fit to sorption data using nonlinear least squares regression. An important assumption of least squares regression is that the predictor variable is error free. In the case of sorption data, this assumption is not valid, and therefore the potential for parameter bias exists. Although alternative regression methods exist that either explicitly account for error in the predictor variable (Model II regression) or minimize the error in the predictor variable, these methods are not commonly used. Therefore, this paper more fully explores the differences in fitted parameters and model fits between these different data fitting methods by fitting P sorption data collected on 26 different soil samples using three different regression methods. For a majority of soils tested in this study, the differences in model fits between the three regression methods were not statistically significant. Statistical differences were observed in over a third of the soils, however, suggesting that errors in the predictor variable may be large enough to produce biased parameter estimates. These results suggest that multiple regression methods should be used when fitting the Langmuir model to sorption data to better assess the potential impact of error on model fits.     

In situ push-pull method to determine ground water denitrification in riparian zones

To quantify ground water denitrification in discrete locations of riparian aquifers, we modified and evaluated an in situ method based on conservative tracers and 15N-enriched nitrate. Ground water was "pushed" (i.e., injected) into a mini-piezometer and then "pulled" (i.e., extracted) from the same mini-piezometer after an incubation period. This push-pull method was applied in replicate mini-piezometers at two Rhode Island riparian sites, one fresh water and one brackish water. Conservative tracer pretests were conducted to determine incubation periods, ranging from 5 to 120 h, to optimize recovery of introduced plumes. For nitrate push-pull tests, we used two conservative tracers, sulfur hexafluoride and bromide, to provide insight into plume recovery. The two conservative tracers behaved similarly. The dosing solutions were amended with 15N-enriched nitrate that enabled us to quantify the mass of denitrification gases generated during the incubation period. The in situ push-pull method detected substantial denitrification rates at a site where we had previously observed high denitrification rates. At our brackish site, we found high rates of ground water denitrification in marsh locations and minimal denitrification in soils fringing the marsh. The push-pull method can provide useful insights into spatial and temporal patterns of denitrification in riparian zones. The method is robust and results are not seriously affected by dilution or degassing from ground water to soil air. In conjunction with measurements of ground water flow-paths, this method holds promise for evaluating the influence of site and management factors on the ground water nitrate removal capacity of riparian zones.