Microplankton dynamics of a coastal lagoon,Chilika: interactive effect of environmental parameters on microplankton groups

Microplankton population of Asia’s largest coastal lagoon Chilika was studied for five major groups, bacillariophyceae, cyanophyceae, chlorophyceae, dinophyceae, rotifera, and tintinninae. The study reported presence of 233 species of microplankton whose average annual abundance was 1631 cells/l. The physicochemical parameters contributing to the spatio-temporal fluctuations in microplankton diversity, abundance, and community structure were identified as salinity, pH, DO, nitrate, and silicate. Salinity, transparency, depth, and silicate most explained the abundance of bacillariophyceae; nitrate, pH, and DO influenced cyanophyceae; salinity, transparency, and chlorophyll concentration influenced chlorophyceae; salinity, depth, and water temperature influenced dinophyceae; salinity, free CO2, and nitrate-influenced rotifers, whereas salinity, pH, DO, and depth influenced tintinnids. Biotic-abiotic relationships revealed particular preference of environmental conditions at species level in groups like bacillariophyceae, cyanophyceae, and dinophyceae. Although the lagoon is shallow, bacillariophyceae-environment interaction showed depth can be a critical factor for species like Aulocoseira sp., Amphipleura sp., and Rhophalodia sp. Species of dinoflagellates like Dinophysis caudata, Noctiluca scintillans, and Protoperidinium proliferated in lower level of silicate. Unlike other cyanophyceae species Streptococcus sp., Chroococcus sp., Diplococcus sp., Aphanocapsa sp., and Gloeocapsa sp. were negatively influenced by nitrate concentration. The study provides better scope for ecological management of the lagoon with respect to conserving biodiversity and hydrological quality of the ecosystem.     

Modeling Changes to Streamflow,Sediment, and Nutrient Loading from Land Use Changes Due to Potential Natural Gas Development

Natural gas development using hydraulic fracturing has many potential environmental impacts, but among the most certain is the land disturbance required to build the well pads and other infrastructure required to drill and extract the gas. We used the Soil and Water Assessment Tool (SWAT) model to investigate how natural gas development could impact streamflow and sediment, total nitrogen (TN), and total phosphorous (TP) loadings in the upper Delaware River Basin (DRB), a relatively undeveloped watershed of 7,950 km² that lies above the Marcellus Shale formation. If gas development was permitted, our projections show the DRB could experience development of over 600 well pads to extract natural gas at build out, which, with supporting infrastructure (roads, gathering pipelines), could convert over 5,000 ha from existing land uses in the study area. In subbasins with development activity we found sediment, TN, and TP yields could increase by an average of 15, 0.08, and 0.03 kg/ha/yr, respectively (an increase of 2, 3, and 15%, respectively) for each one percent of subbasin land area converted into natural gas infrastructure. At the study area outlet on the Delaware River at Port Jervis, New York, we found increases in the annual average streamflow and sediment, nitrogen, and phosphorus loads of up to 0.01, 0.2, 0.2, and 1%, respectively, for a rapid development year, and 0.08, 1.3, 2.0, and 11%, respectively, for the full development scenario. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Runoff Simulation of the Headwaters of the Yellow River Using The SWAT Model With Three Snowmelt Algorithms1

Abstract: The Soil and Water Assessment Tool (SWAT) model combined with different snowmelt algorithms was evaluated for runoff simulation of an 114,345 km² mountainous river basin (the headwaters of the Yellow River), where snowmelt is a significant process. The three snowmelt algorithms incorporated into SWAT were as follows: (1) the temperature‐index, (2) the temperature‐index plus elevation band, and (3) the energy budget based SNOW17. The SNOW17 is more complex than the temperature‐based snowmelt algorithms, and requires more detailed meteorological and topographical inputs. In order to apply the SNOW17 in the SWAT framework, SWAT was modified to operate at the pixel scale rather than the normal Hydrologic Response Unit scale. The three snowmelt algorithms were evaluated under two parameter scenarios, the default and the calibrated parameters scenarios. Under the default parameters scenario, the parameter values were determined based on a review of the current literature. The purpose of this type of evaluation was to assess the applicability of SWAT in ungauged basins, where there is little observed data available for calibration. Under the calibrated parameters scenario, the parameters were calibrated using an automatic calibration program, the Shuffled Complex Evolution (SCE‐UA). The purpose of this type of evaluation was to assess the applicability of SWAT in gauged basins. Two time periods (1975‐1985 and 1986‐1990) of monthly runoff data were used in this study to evaluate the performance of SWAT with different snowmelt algorithms. Under the default parameters scenario, the SWAT model with complex energy budget based SNOW17 performed the best for both time periods. Under the calibrated parameters scenario, the parameters were calibrated using monthly runoff from 1975‐1985 and validated using monthly runoff from 1986‐1990. After parameter calibration, the performance of SWAT with the three snowmelt algorithms was improved from the default parameters scenario. Further, the SWAT model with temperature‐index plus elevation band performed as well as the SWAT model with SNOW17. The SWAT model with temperature‐index algorithm performed the poorest for both time periods under both scenarios. Therefore, it is suggested that the SNOW17 model be used for modeling ungauged basins; however, for gauged basins, the SNOW17 and simple temperature‐index plus elevation band models could provide almost equally good runoff simulation results.     

Evaluation of CFSR climate data for hydrologic prediction in data‐scarce watersheds: an application in the Blue Nile River Basin

Data scarcity has been a huge problem in modeling the water resources of the Upper Blue Nile basin, Ethiopia. Satellite data and different statistical methods have been used to improve the quality of conventional meteorological data. This study assesses the applicability of the National Centers for Environmental Prediction's Climate Forecast System Reanalysis (CFSR) climate data in modeling the hydrology of the region. The Soil and Water Assessment Tool was set up to compare the performance of CFSR weather with that of conventional weather in simulating observed streamflow at four river gauging stations in the Lake Tana basin — the upper part of the Upper Blue Nile basin. The conventional weather simulation performed satisfactorily (e.g., NSE ≥ 0.5) for three gauging stations, while the CFSR weather simulation performed satisfactorily for two. The simulations with CFSR and conventional weather yielded minor differences in the water balance components in all but one watershed, where the CFSR weather simulation gave much higher average annual rainfall, resulting in higher water balance components. Both weather simulations gave similar annual crop yields in the four administrative zones. Overall the simulation with the conventional weather performed better than the CFSR weather. However, in data‐scarce regions such as remote parts of the Upper Blue Nile basin, CFSR weather could be a valuable option for hydrological predictions where conventional gauges are not available.     

Aerobic biometer analysis of glucose and starch biodegradation

The ASTM D5210-91 protocol for evaluating the biodegradability of a polymer was examined. The reactor design was modified not only to account for the total CO₂ evolved but also to allow for the simultaneous carbon assessment in microbes, soluble products, and solid samples. Improvements in the test procedure were implemented such as (1) refining the CO₂ pretrap and posttrap design, (2) optimizing the carbon dioxide removal efficiency, (3) accounting for the total polymeric carbon, (4) standardizing the inoculum, and (5) revising the nutrient medium. By growing the sludge on a suitable substrate prior to polymeric exposure, a constant microbial density was obtained. The modified ASTM method provides an assessment of the polymeric carbon degradation at any given time. The results of this work have specific significance to the behavior of polymers in a sewage waste treatment plant, where sludge is continuously being acrated, and also for aerobic biodegradation in general.     

Estrogen-related receptor disruption of source water and drinking water treatment processes extracts

Environmental chemicals in drinking water can impact human health through nuclear receptors. Additionally, estrogen-related receptors (ERRs) are vulnerable to endocrine-disrupting e ects. To date, however, ERR disruption of drinking water potency has not been reported. We used ERR two-hybrid yeast assay to screen ERR disrupting activities in a drinking water treatment plant (DWTP) located in north China and in source water from a reservoir, focusing on agonistic, antagonistic, and inverse agonistic activity to 4-hydroxytamoxifen (4-OHT). Water treatment processes in the DWTP consisted of pre-chlorination, coagulation, coal and sand filtration, activated carbon filtration, and secondary chlorination processes. Samples were extracted by solid phase extraction. Results showed that ERR antagonistic activities were found in all sample extracts, but agonistic and inverse agonistic activity to 4-OHT was not found. When calibrated with the toxic equivalent of 4-OHT, antagonistic e uent e ects ranged from 3.4 to 33.1 g/L. In the treatment processes, secondary chlorination was e ective in removing ERR antagonists, but the coagulation process led to significantly increased ERR antagonistic activity. The drinking water treatment processes removed 73.5% of ERR antagonists. To our knowledge, the occurrence of ERR disruption activities on source and drinking water in vitro had not been reported previously. It is vital, therefore, to increase our understanding of ERR disrupting activities in drinking water.     

Seasonal variation of heavy metals in ambient air and precipitation at a single site in Washington, DC

Atmospheric samples of precipitation and ambient air were collected at a single site in Washington, DC, for 7 months (for ambient air samples) and 1 year (for wet deposition samples) and analyzed for arsenic, cadmium, chromium and lead. The ranges of heavy metal concentrations for 6-day wet deposition samples collected over the 1-year period were 0.20-1.3 microg/l, 0.060-5.1 microg/l, 0.062-4.6 microg/l and 0.11-3.2 microg/l for arsenic, cadmium, chromium and lead, respectively, with a precision better than 5% for more than 95% of the measurements. The ranges of heavy metal concentrations for the 6-day ambient air samples were 0.800-15.7 ng/m(3), 1.50-30.0 ng/m(3), 16.8-112 ng/m(3), and 2.90-137 ng/m(3) for arsenic, cadmium, chromium and lead, respectively, with a precision better than 10%. The spread in the heavy metal concentration over the observation period suggests a high seasonal variability for heavy metal content in both ambient air and wet deposition samples.     

Introduction to SWAT+, A Completely Restructured Version of the Soil and Water Assessment Tool

SWAT+ is a completely restructured version of the Soil and Water Assessment Tool (SWAT) that was developed to face present and future challenges in water resources modeling and management and to meet the needs of the worldwide user community. It is expected to improve code development and maintenance; support data availability, analysis, and visualization; and enhance the model's capabilities in terms of the spatial representation of elements and processes within watersheds. The most important change is the implementation of landscape units and flow and pollutant routing across the landscape. Also, SWAT+ offers more flexibility than SWAT in defining management schedules, routing constituents, and connecting managed flow systems to the natural stream network. To test the basic hydrologic function of SWAT+, it was applied to the Little River Experimental Watershed (Georgia) without enhanced overland routing and compared with previous models. SWAT+ gave similar results and inaccuracies as these models did for streamflow and water balance. Taking full advantage of the new capabilities of SWAT+ regarding watershed discretization and landscape and river interactions is expected to improve simulations in future studies. While many capabilities of SWAT have already been enhanced in SWAT+ and new capabilities have been added, the model will continue to evolve in response to advancements in scientific knowledge and the demands of the growing worldwide user community. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.