Distribution and Trophic Importance of Anthropogenic Nitrogen in Narragansett Bay: An Assessment Using Stable Isotopes

Narragansett Bay has been heavily influenced by human activities for more than 200 years. In recent decades, it has been one of the more intensively fertilized estuaries in the USA, with most of the anthropogenic nutrient load originating from sewage treatment plants (STP). This will soon change as tertiary treatment upgrades reduce nitrogen (N) loads by about one third or more during the summer. Before these reductions take place, we sought to characterize the sewage N signature in primary (macroalgae) and secondary (the hard clam, Mercenaria mercenaria) producers in the bay using stable isotopes of N (δ¹⁵N) and carbon (δ¹³C). The δ¹⁵N signatures of the macroalgae show a clear gradient of approximately 4‰ from north to south, i.e., high to low point source loading. There is also evidence of a west to east gradient of heavy to light values of δ¹⁵N in the bay consistent with circulation patterns and residual flows. The Providence River Estuary, just north of Narragansett Bay proper, receives 85% of STP inputs to Narragansett Bay, and lower δ¹⁵N values in macroalgae there reflected preferential uptake of ¹⁴N in this heavily fertilized area. Differences in pH from N stimulated photosynthesis and related shifts in predominance of dissolved C species may control the observed δ¹³C signatures. Unlike the macroalgae, the clams were remarkably uniform in both δ¹⁵N (13.2 ± 0.54‰ SD) and δ¹³C (−16.76 ± 0.61‰ SD) throughout the bay, and the δ¹⁵N values were 2–5‰ heavier than in clams collected outside the bay. We suggest that this remarkable uniformity reflects a food source of anthropogenically heavy phytoplankton formed in the upper bay and supported by sewage derived N. We estimate that approximately half of the N in the clams throughout Narragansett Bay may be from anthropogenic sources.     

Properties of the clouds of Venus,as inferred from airborne observations of its near-infrared reflectivity spectrum

We have measured the shape and absolute value of Venus' reflectivity spectrum in the 1.2-to 4.0-μm spectral region with a circular variable filter wheel spectrometer having a spectral resolution of 1.5%. The instrument package was mounted on the 91-cm telescope of NASA Ames Kuiper Airborne Observatory, and the measurements were obtained at an altitude of about 41,000 feet, when Venus had a phase angle of 86°. Comparing these spectra with synthetic spectra generated with a multiple-scattering computer code, we infer a number of properties of the Venus clouds. We obtain strong confirmatory evidence that the clouds are made of a water solution of sulfuric acid in their top unit optical depth and find that the clouds are made of this material down to an optical depth of at least 25. In addition, we determine that the acid concentration is 84 ± 2% H_2SO4 by weight in the top unit optical depth, that the total optical depth of the clouds is 37.5 ± 12.5, and that the cross-sectional weighted mean particle radius lies between 0.5 and 1.4 μm in the top unit optical depth of the clouds. These results have been combined with a recent determination of the location of the clouds' bottom boundary [Marov et al., Cosmic Res.14, 637–642 (1976)] to infer additional properties about Venus' atmosphere. We find that the average volume mixing ratio of H₂SO₄ and H₂O contained in the cloud material both equal approximately 2× 10^?6. Employing vapor pressure arguments, we show that the acid concentration equals 84 ± 6% at the cloud bottom and that the water vapor mixing ratio beneath the clouds lies between 6 × 10^?4 and 10^?2.     

Is there a superior conceptual groundwater model structure for baseflow simulation?

Previous work has shown that streamflow response during baseflow conditions is a function of storage, but also that this functional relationship varies among seasons and catchments. Traditionally, hydrological models incorporate conceptual groundwater models consisting of linear or non‐linear storage–outflow functions. Identification of the right model structure and model parameterization however is challenging. The aim of this paper is to systematically test different model structures in a set of catchments where different aquifer types govern baseflow generation processes. Nine different two‐parameter conceptual groundwater models are applied with multi‐objective calibration to transform two different groundwater recharge series derived from a soil‐atmosphere‐vegetation transfer model into baseflow separated from streamflow data. The relative performance differences of the model structures allow to systematically improve the understanding of baseflow generation processes and to identify most appropriate model structures for different aquifer types. We found more versatile and more aquifer‐specific optimal model structures and elucidate the role of interflow, flow paths, recharge regimes and partially contributing storages. Aquifer‐specific recommendations of storage models were found for fractured and karstic aquifers, whereas large storage capacities blur the identification of superior model structures for complex and porous aquifers. A model performance matrix is presented, which highlights the joint effects of different recharge inputs, calibration criteria, model structures and aquifer types. The matrix is a guidance to improve groundwater model structures towards their representation of the dominant baseflow generation processes of specific aquifer types. Copyright © 2014 John Wiley & Sons, Ltd.     

Exploration of remotely sensed forest structure and ultrasonic range sensor metrics to improve empirical snow models

Current methods to estimate snow accumulation and ablation at the plot and watershed levels can be improved as new technologies offer alternative approaches to more accurately monitor snow dynamics and their drivers. Here we conduct a meta‐analysis of snow and vegetation data collected in British Columbia to explore the relationships between a wide range of forest structure variables – obtained from Light Detection and Ranging (LiDAR), hemispherical photography (HP) and Landsat Thematic Mapper – and several indicators of snow accumulation and ablation estimated from manual snow surveys and ultrasonic range sensors. By merging and standardizing all the ground plot information available in the study area, we demonstrate how LiDAR‐derived forest cover above 0.5 m was the variable explaining the highest percentage of absolute peak snow water equivalent (SWE) (33%), while HP‐derived leaf area index and gap fraction (45° angle of view) were the best potential predictors of snow ablation rate (explaining 57% of variance). This study reveals how continuous SWE data from ultrasonic sensors are fundamental to obtain statistically significant relationships between snow indicators and structural metrics by increasing mean r² by 20% when compared to manual surveys. The relationships between vegetation and spectral indices from Landsat and snow indicators, not explored before, were almost as high as those shown by LiDAR or HP and thus point towards a new line of research with important practical implications. While the use of different data sources from two snow seasons prevented us from developing models with predictive capacity, a large sample size helped to identify outliers that weakened the relationships and suggest improvements for future research. A concise overview of the limitations of this and previous studies is provided along with propositions to consistently improve experimental designs to take advantage of remote sensing technologies, and better represent spatial and temporal variations of snow. Copyright © 2013 John Wiley & Sons, Ltd.     

Socioeconomic vulnerability and electric power restoration timelines in Florida: the case of Hurricane Irma

Large-scale damage to the power infrastructure from hurricanes and high-wind events can have devastating ripple effects on infrastructure, the broader economy, households, communities, and regions. Using Hurricane Irma’s impact on Florida as a case study, we examined: (1) differences in electric power outages and restoration rates between urban and rural counties; (2) the duration of electric power outages in counties exposed to tropical storm force winds versus hurricane Category 1 force winds; and (3) the relationship between the duration of power outage and socioeconomic vulnerability. We used power outage data for the period September 9, 2017–September 29, 2017. At the peak of the power outages following Hurricane Irma, over 36% of all accounts in Florida were without electricity. We found that the rural counties, predominantly served by rural electric cooperatives and municipally owned utilities, experienced longer power outages and much slower and uneven restoration times. Results of three spatial lag models show that large percentages of customers served by rural electric cooperatives and municipally owned utilities were a strong predictor of the duration of extended power outages. There was also a strong positive association across all three models between power outage duration and urban/rural county designation. Finally, there is positive spatial dependence between power outages and several social vulnerability indicators. Three socioeconomic variables found to be statistically significant highlight three different aspects of vulnerability to power outages: minority groups, population with sensory, physical and mental disability, and economic vulnerability expressed as unemployment rate. The findings from our study have broader planning and policy relevance beyond our case study area, and highlight the need for additional research to deepen our understanding of how power restoration after hurricanes contributes to and is impacted by the socioeconomic vulnerabilities of communities.     

A comparison of two avalanche-models with exemplary avalanches of Tyrol and Switzerland and the effects to hazard zoning

For the purposes of a thesis at the Institute of avalanche and torrent control at the university of agriculture in Vienna a comparison of two avalanche-models, a hydraulic one from Voellmy/Salm/Gubler and a statistical one from Laatsch/Zenke/Dankerl with exemplary exactly known avalanches of Tyrol and Switzerland was started in 1993. The result of this work was that both models failed by the calculation of avalanches with high recurrence intervals (over 300 years). For the calculation of avalanches with recurrence intervals under 300 years the results of both models are regular. The conclusion is that a combination of two models i.e. a hydraulic one improved by statistical calculations will be the best.     

Incentives for field hydrology and data sharing: collaboration and compensation: reply to “A need for incentivizing field hydrology,especially in an era of open data”*

ABSTRACT

We thank Allen and Berghuijs for continuing the discussion on field hydrology and data sharing and discuss two incentives to promote data collection and sharing in hydrological sciences: a collaborative attitude and additional funding to make data publicly available.     

Linking geomorphology and hydrodynamics: a case study from Península Valdés, Patagonia, Argentina

A case study is presented to assess the relevance of geomorphology in hydrogeological phenomena in an arid coastal area in the Argentinean extra-Andean Patagonia (Península Valdés) with an average rainfall of 232 mm/year and a soil moisture deficit of about 472 mm/year. Various geomorphic units were identified by interpreting Landsat 7 satellite images processed with ER Mapper software and then surveyed in the field, as well as by geological characterization. The hydrodynamic analysis was based on a survey of 89 wells, the construction of equipotential maps, and the interpretation of pumping-test results by a non-equilibrium method. The hydrochemical characterization was based on chemical tests analyzed with the Easy_Quim 6.0 application. The combination of geomorphological, geological, hydrodynamic and hydrochemical elements allowed the definition of hydromorphological units that are typical of recharge, circulation and discharge areas, the latter both for coastal and inland areas in wetlands (salt pans) with elevations to ?40 m relative to sea level. These units and the criteria used for their definition allow immediate recognition of hydrogeological phenomena in arid regions such as the extra-Andean Patagonia, with low information density but with near-optimal satellite imaging of landforms due to the lack of vegetation cover.     

Spatial and Temporal Variability of Benthic Oxygen Demand and Nutrient Regeneration in an Anthropogenically Impacted New England Estuary

Strong benthic–pelagic coupling is an important characteristic of shallow coastal marine ecosystems. Building upon a rich history of benthic metabolism data, we measured oxygen uptake and nutrient fluxes across the sediment–water interface along a gradient of water column primary production in Narragansett Bay, RI (USA). Despite the strong gradients seen in water column production, sediment oxygen demand (SOD) and benthic nutrient fluxes did not exhibit a clear spatial pattern. Some of our sites had been studied in the 1970s and 1980s and thus allowed historical comparison. At these sites, we found that SOD and benthic fluxes have not changed uniformly throughout Narragansett Bay. In the uppermost portion of the bay, the Providence River Estuary, we observed a significant decrease in dissolved inorganic phosphorus fluxes which we attribute to management interventions. At another upper bay site, we observed significant declines in SOD and dissolved inorganic nitrogen fluxes which may be linked to climate-induced decreases in water column primary production and shifts in bloom phenology. In the 1970s, benthic nutrient regeneration supplied 50% to over 200% of the N and P needed to support primary production by phytoplankton. Summer nutrient regeneration in the Providence River Estuary and Upper bay now may only supply some 5–30% of the N and 3–20% of the P phytoplankton demand.