Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Changes in the sorption and rate of 17β-estradiol biodegradation by dissolved organic matter collected from different water sources

The potential biodegradation and subsequent transformation of 17β-estradiol (E2) to estrone (E1) were examined in the presence of various dissolved organic matter (DOM) isolated from effluent, river and lake waters. In addition, estrogenicity was estimated in association with the removal of E2 via its sorption onto DOM and biodegradation. The more biodegradable lake-derived DOM promoted more extensive transformation of E2 into E1 than the effluent organic matter through a biodegradation process. Overall, under all conditions, biodegradation dominated the removal of E2 in water. The increased dissolved organic carbon (DOC) concentrations in river and lake-derived DOM (e.g. 6.5 mg C L(-1)) reduced the removal of E2 by decreasing its biodegradation due to the moderate sorption of E2 onto DOM. The effluent organic matter showed greater removal of E2 via biodegradation, as well as significantly high sorption. This was associated with a large amount of hydrophobic fulvic acid (FA)- and humic acid (HA)-like organic components, as shown by the small increase in the specific UV absorbance at 254 nm (SUVA(254)). An increase in the DOC concentration reduced the removal of E2, resulting in high estrogenicity. The present study suggests that both organic composition and DOC concentration influenced the removal of E2 and, therefore, should be fully considered when assessing estrogenicity and its impacts on the aquatic environment.     

Selecting Variables for Habitat Suitability of <Emphasis Type="Italic">Asellus</Emphasis> (Crustacea,Isopoda) by Applying Input Variable Contribution Methods to Artificial Neural Network Models

This study aimed to compare different methods to analyse the contribution of individual river characteristics to predict the abundance of Asellus (Crustacea, Isopoda). Six methods which provide the relative contribution and/or the contribution profile of the input variables of artificial neural network models were therefore compared: (1) the ‘partial derivatives’ method; (2) the ‘weights’ method; (3) the ‘perturb’ method; (4) the ‘profile’ method; (5) the ‘classical stepwise’ method; (6) the ‘improved stepwise’ method. Consequently, the key variables which affect the habitat preferences of Asellus could be identified. To evaluate the performance of the artificial neural network model, the model predictions were compared with the results of a multiple linear regression analysis. The dataset consisted of 179 samples, collected over a 3-year period in the Zwalm catchment in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Asellus were used in this study. The different contribution methods seemed to give similar results concerning the order of importance of the input variables. Nevertheless, their diverse computation led to differences in sensitivity and stability of the methods and the derived outcomes on the habitat preferences. From an ecological point of view, the environmental variables describing the stream type (width, depth, stream order and distance to mouth) were the most significant variables for Asellus in the Zwalm catchment during the period 2000–2002 for all applied methods. Indirectly, one can conclude that the water quality is not the limiting factor for the survival of Asellus in the Zwalm catchment.     

Trace element concentrations in surface estuarine and marine sediments along the Mississippi Gulf Coast following Hurricane Katrina

Hurricanes are relatively frequent ecological disturbances that may cause potentially long-term impacts to the coastal environment. Hurricane Katrina hit the Mississippi Gulf Coast in August 2005, and caused a storm surge with the potential to change the trace element content of coastal surface sediments. In this study, surface estuarine and marine sediments were collected monthly following the storm from ten sites along the Mississippi Gulf Coast (Mobile Bay, Grand Bay Bayous Heron and Cumbest, Pascagoula, Ocean Springs, Biloxi Gulf, Back Biloxi Bay, Gulfport Gulf, Gulfport Courthouse Rd, and Gulfport Marina). Concentrations of V, Cr, Mn, Fe, Co, Ni, Zn, As, Cd, and Pb were measured by inductively coupled plasma–mass spectrometry to evaluate their temporal and spatial variations in the year following Hurricane Katrina. Sediments were characterized by pH, particle size distribution and total carbon and nitrogen content. Trace element contents of the sediments were determined in both <2 mm and <63 μm grain size fractions. Results revealed no significant temporal and spatial variability in trace element concentrations, in either size fraction. Potential ecological risk of the sediments was assessed by using NOAA SQuiRTs’ guideline values; most concentrations remained below probable adverse effects guidelines to marine organisms suggesting that trace elements redistributed by Hurricane Katrina would not cause an adverse impact on resident organisms. Instead, the concentrations of trace elements were site-dependent, with specific contaminants relating to the use of the area prior to Hurricane Katrina.     

Evaluation of concentration efficiency of the Pseudomonas aeruginosa phage PP7 in various water matrixes by different methods

Enteric viruses monitoring in surface waters requires the concentration of viruses before detection assays. The aim of this study was to evaluate different methods in terms of recovery efficiencies of bacteriophage PP7 of Pseudomonas aeruginosa, measured by real-time PCR, using it as a viral control process in water analysis. Different nucleic acid extraction methods (silica–guanidinium thiocyanate, a commercial kit (Qiagen Viral RNA Kit) and phenol–chloroform with alcohol precipitation) exhibited very low recovery efficiencies (0.08–4.18 %), being the most efficient the commercial kit used for subsequent experiments. To evaluate the efficiency of three concentration methods, PBS (as model for clean water) and water samples from rivers were seeded to reach high (HC, 10⁶ pfu ml^?1) and low concentrations (LC, 10⁴ pfu ml^?1) of PP7. Tangential ultrafiltration proved to be more efficient (50.36?±?12.91, 17.21?±?9.22 and 12.58?±?2.35 % for HC in PBS and two river samples, respectively) than adsorption–elution with negatively charged membranes (1.00?±?1.34, 2.79?±?2.62 and 0.05?±?0.08 % for HC in PBS and two river samples, respectively) and polyethylene glycol precipitation (15.95?±?7.43, 4.01?±?1.12 and 3.91?±?0.54 %, for HC in PBS and two river samples, respectively), being 3.2–50.4 times more efficient than the others for PBS and 2.7–252 times for river samples. Efficiencies also depended on the initial virus concentration and aqueous matrixes composition. In consequence, the incorporation of an internal standard like PP7 along the process is useful as a control of the water concentration procedure, the nucleic acid extraction, the presence of inhibitors and the variability of the recovery among replicas, and for the calculation of the sample limit of detection. Thus, the use of a process control, as presented here, is crucial for the accurate quantification of viral contamination.     

The effect of changes in land use on nitrate concentration in water supply wells in southern Chester County, Pennsylvania

An analysis of private potable water well data was conducted for seven single family residential developments in southern Chester County, Pennsylvania. Background data were available for 165 wells within the communities when the wells were first drilled in the 1980s and early 1990s. Sampling of 75 wells within these same communities was performed in 2006 to determine whether conversion of the land to residential housing along with the use of conventional on-lot septic systems had resulted in elevated concentration of nitrate-nitrogen in the drinking water aquifer. The data indicate that prior land use influenced the occurrence of nitrate-nitrogen in the drinking water aquifer. The median nitrate-nitrogen concentration for the 165 wells in the background dataset was 2.9 mg/L. One hundred-seven of those wells were drilled on land previously used for active agricultural purposes. The median nitrate concentration in these wells was 3.8 mg/L. Of 48 wells drilled on forested land, the median nitrate concentration was 1.1 mg/L, approximately 3.5 times lower than those drilled on active agricultural land. The median nitrate concentration in the 2006 sampling dataset was 3.6 mg/L, an increase of 0.7 mg/L. The data indicate that conversion of the land has not resulted in contamination of the drinking water aquifer with respect to nitrate-nitrogen. Likewise, the data suggest that the conversion has not resulted in significant improvements to overall water quality.     

Computation of groundwater resources and recharge in Chithar River Basin, South India

Groundwater recharge and available groundwater resources in Chithar River basin, Tamil Nadu, India spread over an area of 1,722 km² have been estimated by considering various hydrological, geological, and hydrogeological parameters, such as rainfall infiltration, drainage, geomorphic units, land use, rock types, depth of weathered and fractured zones, nature of soil, water level fluctuation, saturated thickness of aquifer, and groundwater abstraction. The digital ground elevation models indicate that the regional slope of the basin is towards east. The Proterozoic (Post-Archaean) basement of the study area consists of quartzite, calc-granulite, crystalline limestone, charnockite, and biotite gneiss with or without garnet. Three major soil types were identified namely, black cotton, deep red, and red sandy soils. The rainfall intensity gradually decreases from west to east. Groundwater occurs under water table conditions in the weathered zone and fluctuates between 0 and 25 m. The water table gains maximum during January after northeast monsoon and attains low during October. Groundwater abstraction for domestic/stock and irrigational needs in Chithar River basin has been estimated as 148.84 MCM (million m³). Groundwater recharge due to monsoon rainfall infiltration has been estimated as 170.05 MCM based on the water level rise during monsoon period. It is also estimated as 173.9 MCM using rainfall infiltration factor. An amount of 53.8 MCM of water is contributed to groundwater from surface water bodies. Recharge of groundwater due to return flow from irrigation has been computed as 147.6 MCM. The static groundwater reserve in Chithar River basin is estimated as 466.66 MCM and the dynamic reserve is about 187.7 MCM. In the present scenario, the aquifer is under safe condition for extraction of groundwater for domestic and irrigation purposes. If the existing water bodies are maintained properly, the extraction rate can be increased in future about 10 % to 15 %.