Model evaluation of potential impacts of on-site wastewater systems on phosphorus in Turkey creek watershed

Nutrient loading to surface water systems has traditionally been associated with agricultural sources. Sources such as on-site wastewater systems (OWS) may be of concern especially in rural, nonagricultural watersheds. The impact of various point and nonpoint sources including OWS in Turkey Creek Watershed was evaluated using the Watershed Analysis Risk Management Framework, which was calibrated using 10 yr of observed stream flow and total P concentrations. Doubling the population in the watershed or OWS septic tank effluent P concentration increased mean stream total P concentration by a factor of 1.05. Converting all the OWS to a conventional sewer system with a removal efficiency of 93% at the wastewater treatment plant increased the mean total P concentration at the watershed outlet by a factor of 1.26. Reducing the soil adsorption capacity by 50% increased the mean stream total P concentration by a factor of 3.2. Doubling the initial P concentration increased the mean stream total P concentration by a factor of 1.96. Stream flow and sediment transport also substantially affected stream P concentration. The results suggest that OWS contribution to stream P in this watershed is minimal compared with other factors within the simulated time frame of 10 yr.     

A review on thermal analyses of cyclodextrins and cyclodextrin complexes

Environmental Chemistry Letters - Cyclodextrins are valuable natural or synthetically modified cyclic oligosaccharides that are widely used for ameliorating properties of biologically active...     

Novel Glycopolymers Based on d-Mannose and Methacrylates: Synthesis, Thermal Stability and Biodegradability Testing

This paper presents the synthesis, thermal stability and biodegradability of new d-mannose glycopolymers. These glycopolymers have been obtained by free radical bulk copolymerization of d-mannose based glycomonomer, 1-O-(2′-hydroxy-3′-methacryloyloxypropyl)-2,3:5,6-di-O-isopropylidene-d-mannofuranose (Mm), and respectively d-mannose derived oligomer (Mo) with methyl methacrylate and respectively 2-hydroxypropyl methacrylate. The chemical structures of Mm and Mo have been confirmed via FTIR, ¹H-NMR and HPLC–MS spectroscopy. The copolymerization process has been investigated using differential scanning calorimetry, which allowed calculating the activation energies by applying Kissinger–Akahira–Sunose method. The glycopolymers are thermally stable, fact assessed by TG analysis; their glass transition temperature exceeds 50 °C, so they are part of the glassy class of polymers. The biodegradability of these glycopolymers has been investigated in vitro, using pure cultures of Zymomonas mobilis and Trichoderma reesei. The glycopolymers lose up to 55 % weight in just 14 days of incubation as their surface and composition is altered by colonies of microorganisms that grow on/into them, fact demonstrated using SEM/EDX.     

STUMOD—a Tool for Predicting Fate and Transport of Nitrogen in Soil Treatment Units

A typical onsite wastewater treatment system consists of a septic tank and a soil treatment unit to treat wastewater before it is discharged through the vadose zone to an aquifer. A tool was developed for the purpose of predicting the fate and transport of nitrogen in soil treatment units (STUMOD or Soil Treatment Unit Model). STUMOD calculates nitrogen species concentrations and the fraction of total nitrogen reaching the aquifer or a specified soil depth. Input data include parameters for hydraulics and nutrient transport and transformation. An analytical solution is used to calculate the profile of pressure based on Darcy’s equation and the relationships between suction head, unsaturated hydraulic conductivity, and soil moisture. Chemical transport is based on simplification of the advection–dispersion equation. STUMOD is relatively simple to use but accounts for important processes such as ammonium sorption, nitrification, and denitrification. STUMOD accounts for the effect of soil moisture content (a surrogate for redox conditions) on nitrification and denitrification reactions. The model has provisions to handle the influence of temperature and organic carbon content on nitrogen transformation. Model outputs, generated based on input parameters obtained from extensive literature review, were compared to a numerical model and data from laboratory tests and field sites. Both measured data and STUMOD outputs show a relatively higher removal in clayey soils compared to sandy soils. Consistent with literature data for most soils, STUMOD predicted ammonium conversion to nitrate within the first foot below the trench infiltrative surface.     

Effects of soil data resolution on SWAT model stream flow and water quality predictions

The prediction accuracy of agricultural nonpoint source pollution models such as Soil and Water Assessment Tool (SWAT) depends on how well model input spatial parameters describe the characteristics of the watershed. The objective of this study was to assess the effects of different soil data resolutions on stream flow, sediment and nutrient predictions when used as input for SWAT. SWAT model predictions were compared for the two US Department of Agriculture soil databases with different resolution, namely the State Soil Geographic database (STATSGO) and the Soil Survey Geographic database (SSURGO). Same number of sub-basins was used in the watershed delineation. However, the number of HRUs generated when STATSGO and SSURGO soil data were used is 261 and 1301, respectively. SSURGO, with the highest spatial resolution, has 51 unique soil types in the watershed distributed in 1301 HRUs, while STATSGO has only three distributed in 261 HRUS. As a result of low resolution STATSGO assigns a single classification to areas that may have different soil types if SSURGO were used. SSURGO included Hydrologic Response Units (HRUs) with soil types that were generalized to one soil group in STATSGO. The difference in the number and size of HRUs also has an effect on sediment yield parameters (slope and slope length). Thus, as a result of the discrepancies in soil type and size of HRUs stream flow predicted was higher when SSURGO was used compared to STATSGO. SSURGO predicted less stream loading than STATSGO in terms of sediment and sediment-attached nutrients components, and vice versa for dissolved nutrients. When compared to mean daily measured flow, STATSGO performed better relative to SSURGO before calibration. SSURGO provided better results after calibration as evaluated by R(2) value (0.74 compared to 0.61 for STATSGO) and the Nash-Sutcliffe coefficient of Efficiency (NSE) values (0.70 and 0.61 for SSURGO and STATSGO, respectively) although both are in the same satisfactory range. Modelers need to weigh the benefits before selecting the type of data resolution they are going to use depending on the watershed size and level of accuracy required because more effort is required to prepare and calibrate the model when a fine resolution soil data is used.