Spatial analysis of future climate risk to stormwater infrastructure.

Climate change is expected to result in more intense precipitation events that will affect the performance and design requirements of stormwater infrastructure. Such changes will vary spatially, and climate models provide a range of estimates of the effects on events of different intensities and recurrence. Infrastructure performance should be evaluated against the expected range of events, not just rare extremes. We present a national-scale, spatially detailed screening assessment of the potential effects of climatic change on precipitation, stormwater runoff, and associated design requirements. This is accomplished through adjustment relative to multiple future climate scenarios of precipitation intensity-duration-frequency analyses presented in NOAA Atlas 14, which are commonly used in infrastructure design. Future precipitation results are estimated for each Atlas 14 station (these currently omit the Pacific Northwest). Results are interpolated using a geographically conditioned regression kriging approach to provide information about potential climate change impacts in a format more directly useful to local stormwater managers. The intensity of 24-h events with 2-year or greater recurrence is likely to increase in most areas of the United States leading to increased runoff and potential need for increased storage volumes. Changes in more frequent events (e.g., the 90th percentile event) commonly used in design of green infrastructure are relatively less.

A coupled hydrodynamic (HEC-RAS 2D) and water quality model (WASP) for simulating flood-induced soil, sediment, and contaminant transport.

Increased intensity and frequency of floods raise concerns about the release and transport of contaminated soil and sediment to and from rivers and streams. To model these processes during flooding events, we developed an External Coupler in Python to link the Hydrologic Engineering Center-River Analysis System (HEC-RAS) 2D hydrodynamic model to the Water Quality Analysis Simulation Program (WASP). Accurate data transfer from a hydrodynamic model to a water quality model is critical. Our test results showed the External Coupler successfully linked HEC-RAS and WASP and addressed technical challenges in aggregating flow data and conserving mass during the flood event. We ran the coupled models for a 100-year flood event to calculate flood-induced transport of sediment-associated arsenic in Woodbridge Creek, NJ. Change in surface sediment and arsenic at the end of 48-h flood simulation ranged from a net loss of 13.5 cm to a net gain of 11.6 cm, and 16.2 to 2.9 mg/kg, respectively, per model segment, which demonstrates the capability of the coupled model for simulating sediment and contaminant transport in flood.

Applying landscape metrics and structural equation modeling to predict the effect of urban green space on air pollution and respiratory mortality in Tehran.

Green space and its spatial formation are important elements of public welfare in urban environments and green ecosystems in big cities largely contribute to the mental and physical health of citizens. Tehran is Iran's biggest and most polluted city and air pollution in this city causes loss of human lives due to respiratory diseases. The effect of green area has been less studied in former researches in Tehran, and the reducing effects of green landscape on the mortality of respiratory diseases have not yet been evaluated. To measure the effects of green area landscape patterns (fragmentation, area-edge, shape, and aggregation) on public health, the current study evaluated the pathways and effects of green space on air pollution and the mortality of respiratory diseases using structural equation modeling approach and the partial least squares method. The results of the study indicated green space has a significant mitigating effect on air pollution and mortality of respiratory diseases and also air pollution has a meaningful increasing effect on mortality due to respiratory diseases in Tehran. The most important latent variable in green space is class area that indicates more area of green space is correlated with less mortality of respiratory diseases. The most important indicator of air pollution was the PM2.5 that needs to be considered and controlled by urban policymakers. Accordingly, maximizing the green area and its cohesion and minimizing fragmentation and green patch edge can contribute to a reduction in air pollution and consequently lower mortality of citizens.

SWAT Modeling of Non-Point Source Pollution in Depression-Dominated Basins under Varying Hydroclimatic Conditions.

Non-point source (NPS) pollution from agricultural lands is the leading cause of various water quality problems across the United States. Particularly, surface depressions often alter the releasing patterns of NPS pollutants into the environment. However, most commonly-used hydrologic models may not be applicable to such depression-dominated regions. The objective of this study is to improve water quantity/quality modeling and its calibration for depression-dominated basins under wet and dry hydroclimatic conditions. Specifically, the Soil and Water Assessment Tool (SWAT) was applied for hydrologic and water quality modeling in the Red River of the North Basin (RRB). Surface depressions across the RRB were incorporated into the model by employing a surface delineation method and the impacts of depressions were evaluated for two modeling scenarios, MS1 (basic scenario) and MS2 (depression-oriented scenario). Moreover, a traditional calibration scheme (CS1) was compared to a wet-dry calibration scheme (CS2) that accounted for the effects of hydroclimatic variations on hydrologic and water quality modeling. Results indicated that the surface runoff simulation and the associated water quality modeling were improved when topographic characteristics of depressions were incorporated into the model (MS2). The Nash⁻Sutcliffe efficiency (NSE) coefficient indicated an average increase of 30.4% and 19.6% from CS1 to CS2 for the calibration and validation periods, respectively. Additionally, the CS2 provided acceptable simulations of water quality, with the NSE values of 0.50 and 0.74 for calibration and validation periods, respectively. These results highlight the enhanced capability of the proposed approach for simulating water quantity and quality for depression-dominated basins under the influence of varying hydroclimatic conditions.

Spectral sea surface reflectance of skylight.

In examining the dependence of the sea surface reflectance of skylight ρs on sky conditions, wind speed, solar zenith angle, and viewing geometry, Mobley [Appl. Opt.38, 7442 (1999).10.1364/AO.38.007442] assumed ρs is independent of wavelength. Lee et al. [Opt. Express18, 26313 (2010).10.1364/OE.18.026313] showed experimentally that ρs does vary spectrally due to the spectral difference of sky radiance coming from different directions, which was ignored in Mobley's study. We simulated ρs from 350 nm to 1000 nm by explicitly accounting for spectral variations of skylight distribution and Fresnel reflectance. Furthermore, we separated sun glint from sky glint because of significant differences in magnitude, spectrum and polarization state between direct sun light and skylight light. The results confirm that spectral variation of ρs(λ) mainly arises from the spectral distribution of skylight and would vary from slightly blueish due to normal dispersion of the refractive index of water, to neutral and then to reddish with increasing wind speeds and decreasing solar zenith angles. Polarization moderately increases sky glint by 8 - 20% at 400 nm but only by 0 - 10% at 1000 nm. Sun glint is inherently reddish and becomes significant (>10% of sky glint) when the sun is at the zenith with moderate winds or when the sea is roughened (wind speeds > 10 m s-1) with solar zenith angles < 20°. We recommend a two-step procedure by first correcting the glint due to direct sun light, which is unpolarized, followed by removing the glint due to diffused and polarized skylight. The simulated ρs(λ) as a function of wind speeds, sun angles and aerosol concentrations for currently recommended sensor-sun geometry, i.e., zenith angle = 40° and azimuthal angle relative to the sun = 45°, is available upon request.

Accumulation of heavy metals and As in liver, hair, femur, and lung of Persian jird (Meriones persicus) in Darreh Zereshk copper mine, Iran.

Rodents frequently serve as bioindicator to monitor the quality of the environment. Concentrations of 11 elements (Cd, Co, Ti, Fe, Mn, Cu, Sb, As, Sr, Ni, and Cr) were investigated and compared in liver, hair, femur, and lung of the Persian jird (Meriones persicus) from Darreh Zereshk copper mine, Iran. Metals were determined in different tissues of 39 individuals of Persian jird, collected by snap trap in 2014 from five areas of Darreh Zereshk copper mine. Samples were prepared by wet digestion method, and the contents of elements were analyzed with ICP-OES (VARIAN, 725-ES) instrument. Cadmium, Sb, and Co were below the limit of detection, and Mn and As were found only in hair and liver tissues. We detected the highest concentration of Cu, As, Ti, Fe, Mn, Cr, and Ni in hair in comparison with other tissues. Significant higher levels of Ti in femur and hair; Fe in liver and hair; Mn in liver; As in hair; Sr in lung; Cr in lung, hair, femur, and liver; Cu in femur; and Ni in liver and lung tissues were observed in females. Nearly all element concentrations in the tissues of Persian jird from flotation site, Darreh Zereshk and Hasan Abad villages and leaching site (mining areas) were higher than those from tailing dump site (reference site). We found the highest concentrations of As in liver and hair; Ni and Cr in liver, hair, and lung; and Sr in lung and hair tissues of Persian jird in leaching site. We tried to specify the status of elements before fully exploitation of Darreh Zereshk copper mine by using bioindicator species. Based on our achievements, initial activities did not strongly pollute the surrounded environment of the mine. The high abundance of Persian jird as well as their several proper features makes them a suitable species for biomonitoring programs especially for further studies will be performed after full exploitation of Darreh Zereshk copper mine.

Modeling relationships between catchment attributes and river water quality in southern catchments of the Caspian Sea.

Increasing land utilization through diverse forms of human activities, such as agriculture, forestry, urban growth, and industrial development, has led to negative impacts on the water quality of rivers. To find out how catchment attributes, such as land use, hydrologic soil groups, and lithology, can affect water quality variables (Ca(2+), Mg(2+), Na(+), Cl(-), HCO 3 (-) , pH, TDS, EC, SAR), a spatio-statistical approach was applied to 23 catchments in southern basins of the Caspian Sea. All input data layers (digital maps of land use, soil, and lithology) were prepared using geographic information system (GIS) and spatial analysis. Relationships between water quality variables and catchment attributes were then examined by Spearman rank correlation tests and multiple linear regression. Stepwise approach-based multiple linear regressions were developed to examine the relationship between catchment attributes and water quality variables. The areas (%) of marl, tuff, or diorite, as well as those of good-quality rangeland and bare land had negative effects on all water quality variables, while those of basalt, forest land cover were found to contribute to improved river water quality. Moreover, lithological variables showed the greatest most potential for predicting the mean concentration values of water quality variables, and noting that measure of EC and TDS have inversely associated with area (%) of urban land use.

Contracaecum pyripapillatum n. sp. (Nematoda: Anisakidae) and a description of C. multipapillatum (von Drasche, 1882) from the Australian pelican, Pelecanus conspicillatus.

A new species of nematode, Contracaecum pyripapillatum, is reported from the Australian pelican, Pelecanus conspicillatus. This species resembles Contracaecum multipapillatum which was found in the same host. These two species can be differentiated from one another based on the shape of the preanal papillae, being pyriform in C. pyripapillatum and circular in C. multipapillatum. Genetically, the two species differ in the sequences of first and second internal transcribed spacers (ITS-1 and ITS-2, respectively) of ribosomal DNA (rDNA). C. pyripapillatum and C. multipapillatum differed in the ITS-1 (443 bp in both species) and ITS-2 (between 231 and 233 bp) sequences by 3.4-3.8% and 6.0%, respectively. Based on previous allozyme and mtDNA datasets, genotypes of C. multipapillatum A, B, and C have been reported from Europe and USA. Therefore, C. multipapillatum from Australia has been designated as C. multipapillatum D. A morphological examination of these genotypes is necessary to determine whether they represent distinct species.