Comparison of 85Kr and 3H Apparent Ground‐Water Ages for Source Water Vulnerability in the Collyer River Catchment,Maine1

Abstract: Apparent ground‐water ages as determined by the noble gas isotope ⁸⁵Kr and the water isotope ³H are compared. Refined gas extraction methodology at the wellhead permits efficient collection of Kr for ⁸⁵Kr isotope enrichment. ⁸⁵Kr isochrones elucidate areas of much younger ground‐water ages than ³H. Declining ³H activities in the catchment prevent its correlation with the youngest measured ⁸⁵Kr ages. Source water for most drinking water supplies in the Collyer River catchment is recharged within 40 years BP (2004). Mean‐age (τ) transport modeling suggests uncertainty of ground‐water ages is greatest in the central basin area.     

Characterizing Storm Hydrograph Rise and Fall Dynamics With Stream Stage Data1

Abstract: Storm‐flow transients (i.e., hydrograph rise and fall dynamics) may represent an important aspect of understanding streamflow dynamics. However, little is known about how temporal resolution of transient data and climate variability may color these potential indicators of hydrologic pattern or condition. Warm‐season stream stage and rainfall were monitored continuously (5 min) during the 2002 water year in eight tributaries of the Little Miami River (Ohio), which drain 17‐58 km² catchments. Rise rates generated using 5‐min data were different than those generated with mean daily data [calculated with the Indicators of Hydrologic Alteration (IHA) software], though fall rates were similar for fine and coarse temporal data. This result suggests that data with low temporal resolution may not be adequate to fully represent the dynamics of storm rise rates. Conversely, fall rates based on daily stage data (via IHA) were similar to those based on the 5‐min data, and so daily mean data may be appropriate for characterizing fall rates. We next analyzed the possible correlations between rainfall variability and storm‐flow stage dynamics. We derived rise and recession rates from storm stage hydrographs by assuming exponential rise and decay of a runoff peak. We found that raw rise rates (R_raw) were correlated with both the maximum rainfall rate and the time to the centroid of a rain event. We subsequently removed the trend based on these rainfall characteristics, which yielded new representations of rise rates abbreviated as R_rate and R_tcent, respectively, and that had lower variability than the uncorrected (raw) data. Fall rates were found to be independent of rainfall characteristics. Due to the predominant influence of stream hydrology upon aquatic biota and nutrient fluxes, our work suggests that these stage data analysis protocols can refine or otherwise reduce variability in these indices by accounting for relevant factors such as rainfall forcing. These protocols for derivation of transient indices should be tested for their potential to improve correlations between stream hydrology and temporally aligned biotic data and dissolved nutrient fluxes in streams.     

Responding to a policy mandate to collaborate: structuring collaboration in the collaborative forest landscape restoration program

The Collaborative Forest Landscape Restoration Program (CFLRP) aims to expand the pace and scale of forest restoration on national forests in the United States. The program requires candidate projects to develop landscape-scale forest restoration proposals through a collaborative process and continue to collaborate throughout planning, implementation, and monitoring. Our comparative case analysis of the initial selected projects examines how existing collaborative groups draw on past experience of collaboration and the requirements of a new mandate to shape collaborative structures as they undertake CFLRP work. While mandating collaboration appears contrary to what is often defined as an informal and emergent process, mandates can encourage stakeholder engagement and renew commitment to overcome past conflict. Our findings also suggest that a collaborative mandate can lead to increased attention and scrutiny, prompting adjustments to collaborative process and structure. As such, mandating collaboration creates dynamic tensions between past experience and new requirements for collaborative practice.     

Optimal Reorganization of NASA Earth Science Data for Enhanced Accessibility and Usability for the Hydrology Community

A long‐standing “Digital Divide” in data representation exists between the preferred way of data access by the hydrology community and the common way of data archival by earth science data centers. Typically, in hydrology, earth surface features are expressed as discrete spatial objects (e.g., watersheds), and time‐varying data are contained in associated time series. Data in earth science archives, although stored as discrete values (of satellite swath pixels or geographical grids), represent continuous spatial fields, one file per time step. This Divide has been an obstacle, specifically, between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. and NASA earth science data systems. In essence, the way data are archived is conceptually orthogonal to the desired method of access. Our recent work has shown an optimal method of bridging the Divide, by enabling operational access to long‐time series (e.g., 36 years of hourly data) of selected NASA datasets. These time series, which we have termed “data rods,” are pre‐generated or generated on‐the‐fly. This optimal solution was arrived at after extensive investigations of various approaches, including one based on “data curtains.” The on‐the‐fly generation of data rods uses “data cubes,” NASA Giovanni, and parallel processing. The optimal reorganization of NASA earth science data has significantly enhanced the access to and use of the data for the hydrology user community.     

Assessment of a regulatory model's performance relative to large spatial heterogeneity in observed ozone in Houston, Texas

In Houston, some of the highest measured 8-hr ozone (O3) peaks are characterized by sudden increases in observed concentrations of at least 40 ppb in 1 hr or 60 ppb in 2 hr. Measurements show that these large hourly changes appear at only a few monitors and span a narrow geographic area, suggesting a spatially heterogeneous field of O3 concentrations. This study assessed whether a regulatory air quality model (AQM) can simulate this observed behavior. The AQM did not reproduce the magnitude or location of some of the highest observed hourly O3 changes, and it also failed to capture the limited spatial extent. On days with measured large hourly changes in O3 concentrations, the AQM predicted high O3 over large regions of Houston, resulting in overpredictions at several monitors. This analysis shows that the model can make high O3, but on these days the predicted spatial field suggests that the model had a different cause. Some observed large hourly changes in O3 concentrations have been linked to random releases of industrial volatile organic compounds (VOCs). In the AQM emission inventory, there are several emission events when an industrial point source increases VOC emissions in excess of 10,000 mol/hr. One instance increased predicted downwind O3 concentrations up to 25 ppb. These results show that the modeling system is responsive to a large VOC release, but the timing and location of the release, and meteorological conditions, are critical requirements. Attainment of the O3 standard requires the use of observational data and AQM predictions. If the large observed hourly changes are indicative of a separate cause of high O3, then the model may not include that cause, which might result in regulators enacting control strategies that could be ineffective.     

Optimal temporal scale for the correlation of AOD and ground measurements of PM2.5 in a real-time air quality estimation system

Aerosol optical depth (AOD), an indirect estimate of particulate matter using satellite observations, has shown great promise in improving estimates of PM_2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5 μm) surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM_2.5 in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) an approach that integrates satellite measurements with ground measurements in the estimates of pollutants and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect, identifying the optimal temporal scale to correlate AOD with PM_2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale: within the last 30 days, displays the best model performance in a southern multi-state area centered in Mississippi using 2004 and 2005 data sets.     

Nitrogen limited biobarriers remove atrazine from contaminated water: laboratory studies

Atrazine is one of the most frequently used herbicides. This usage coupled with its mobility and recalcitrant nature in deeper soils and aquifers makes it a frequently encountered groundwater contaminant. We formed biobarriers in sand filled columns by coating the sand with soybean oil; after which, we inoculated the barriers with a consortium of atrazine-degrading microorganisms and evaluated the ability of the barriers to remove atrazine from a simulated groundwater containing 1 mg L(-1) atrazine. The soybean oil provided a carbon rich and nitrogen poor substrate to the microbial consortium. Under these nitrogen-limiting conditions it was hypothesized that bacteria capable of using atrazine as a source of nitrogen would remove atrazine from the flowing water. Our hypothesis proved correct and the biobarriers were effective at removing atrazine when the nitrogen content of the influent water was low. Levels of atrazine in the biobarrier effluents declined with time and by the 24th week of the study no detectable atrazine was present (limit of detection<0.005 mg L(-1)). Larger amounts of atrazine were also removed by the biobarriers; when biobarriers were fed 16.3 mg L(-1) atrazine 97% was degraded. When nitrate (5 mg L(-1) N), an alternate source of nitrogen, was added to the influent water the atrazine removal efficiency of the barriers was reduced by almost 60%. This result supports the hypothesis that atrazine was degraded as a source of nitrogen. Poisoning of the biobarriers with mercury chloride resulted in an immediate and large increase in the amount of atrazine in the barrier effluents confirming that biological activity and not abiotic factors were responsible for most of the atrazine degradation. The presence of hydroxyatrazine in the barrier effluents indicated that dehalogenation was one of the pathways of atrazine degradation. Permeable barriers might be formed in-situ by the injection of innocuous vegetable oil emulsions into an aquifer or sandy soil and used to remove atrazine from a contaminated groundwater or to protect groundwater from an atrazine spill.     

Essential and non-essential element concentrations in two sleeper shark species collected in arctic waters

A number of elements/metals have increased in arctic biota and are of concern due to their potential toxicity. Most studies on elements in the Arctic have focused on marine mammals and seabirds, but concentrations in the Greenland shark (Somniosus microcephalus) and Pacific sleeper shark (Somniosus pacificus), the only two shark species known to regularly inhabit arctic waters, have never been reported. To address this data gap, concentrations and patterns of 25 elements were analyzed in liver of Greenland sharks collected about Cumberland Sound (n=24) and Pacific sleeper sharks collected about Prince William Sound (n=14). Several non-essential elements differed between species/locations, which could suggest geographical exposure differences or ecological (e.g., diet) differences between the species. Certain essential elements also differed between the two sleeper sharks, which may indicate different physiological requirements between these closely related shark species, although information on such relationships are lacking for sharks and fish.