Terrain Discontinuity Effects in the Regional Flow of a Complex Karstified Aquifer

Karst aquifers are characterized by spatial heterogeneity due to the presence of highly permeable channels and conduits in low-permeable fractured rocks (matrix block). Recent studies have reported a close relationship between surface and subsurface water in karstic regions due to the water flow through a complicated network of paths formed by fracture intersections. Subsurface flow in karstified aquifers ranges between conduit flow, in large passages with relatively high flow velocities, and diffuse flow, in the matrix block where Darcy’s law is still valid. In this paper, we present the simulation of a complex karstified aquifer system in Crete, Greece, where the presence of main faults drastically affects the regional flow. A discrete fracture approach in conjunction with an equivalent porous medium approach was adopted to simulate the mixed flow in the area of interest. The simulation results have shown that the length and the orientation of the dominant faults, primarily during the rainy season, affect the flow field.     

How Do River Nitrate Concentrations Respond to Changes in Land-use? A Modelling Case Study of Headwaters in the River Derwent Catchment,North Yorkshire,UK

A combined semi-distributed hydrological model (CASCADE/QUESTOR) is used to evaluate the steady-state that may be achieved after changes in land-use or management and to explore what additional factors need to be considered in representing catchment processes. Two rural headwater catchments of the River Derwent (North Yorkshire, UK) were studied where significant change in land-use occurred in the 1990s and the early 2000s. Much larger increases in mean nitrate concentration (55%) were observed in the catchment with significant groundwater influence (Pickering Beck) compared with the surface water-dominated catchment (13% increase). The increases in Pickering Beck were considerably greater than could be explained by the model in terms of land-use change. Consequently, the study serves to focus attention on the long-term increases in nitrate concentration reported in major UK aquifers and the ongoing and chronic impact this trend is likely to be having on surface water concentrations. For river environments, where groundwater is a source, such trends will mask the impact of measures proposed to reduce the risk of nitrate leaching from agricultural land. Model estimates of within-channel losses account for 15–40% of nitrate entering rivers.     

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.     

Inexact Fuzzy-Stochastic Programming for Water Resources Management Under Multiple Uncertainties

In this study, an interval-parameter fuzzy-stochastic two-stage programming (IFSTP) approach is developed for irrigation planning within an agriculture system under multiple uncertainties. A concept of the distribution with fuzzy-interval probability (DFIP) is defined to address multiple uncertainties expressed as integration of intervals, fuzzy sets, and probability distributions. IFSTP integrates the interval programming, two-stage stochastic programming, and fuzzy-stochastic programming within a general optimization framework. IFSTP incorporates the pre-regulated water resources management policies directly into its optimization process to analyze various policy scenarios; each scenario has different economic penalty when the promised amounts are not delivered. IFSTP is applied to an irrigation planning in a water resources management system. Solutions from IFSTP provide desired water allocation patterns, which maximize both the system’s benefits and feasibility. The results indicate that reasonable solutions are generated for objective function values and decision variables; thus, a number of decision alternatives can be generated under different levels of stream flows.     

Bioavailability of copper,cadmium, zinc,and lead in tropical savanna soils assessed by diffusive gradient in thin films (DGT) and ion exchange resin membranes

The technique of diffusion gradient in thin films (DGT) for assessing bioavailable metals has not been tested under field conditions. We assessed the relationships of DGT- and cation exchange resin-membrane-measured concentrations of Cd, Cu, Pb, and Zn with plant uptake of the metals under greenhouse and field conditions. In the greenhouse, the effective concentrations of Cu, Pb, and Zn by DGT correlated significantly with uptake by sorghum (Sorghum bicolor), but cation exchange resin-membrane-measured concentrations of Cd, Pb, and Zn did not correlate with sorghum uptake. In the field, the DGT-measured concentrations of Cd, Pb, and Zn were not linearly related to uptake Cd, Pb, and Zn by lettuce (Lactuca sativa) except for Cu uptake (r = 0.87, p < 0.05). Similarly, it was only the resin-membrane-extractable Pb that correlated with Pb uptake by lettuce (r = 0.77; p < 0.05). However, fitting non-linear regression models improved the plant metal uptake predictions by DGT-measured bioavailable Cd, Cu, Pb, and Zn under field conditions. In conclusion, the DGT technique was fairly predictive of bioavailability in the greenhouse, but not in the field.     

Seagrass resource assessment using remote sensing methods in St. Joseph Sound and Clearwater Harbor,Florida, USA

In the event of a natural or anthropogenic disturbance, environmental resource managers require a reliable tool to quickly assess the spatial extent of potential damage to the seagrass resource. The temporal availability of the Landsat 5 Thematic Mapper (TM) imagery provided a suitable option to detect and assess damage of the submerged aquatic vegetation (SAV). This study examined Landsat TM imagery classification techniques to create two-class (SAV presence/absence) and three-class (SAV estimated coverage) SAV maps of the seagrass resource. The Mahalanobis Distance method achieved the highest overall accuracy (86%) and validation accuracy (68%) for delineating the seagrass resource (two-class SAV map). The Maximum Likelihood method achieved the highest overall accuracy (74%) and validation accuracy (70%) for delineating the seagrass resource three-class SAV map. The Landsat 5 TM imagery classification provided a seagrass resource map product with similar accuracy to the aerial photointerpretation maps (validation accuracy 71%). The results support the application of remote sensing methods to analyze the spatial extent of the seagrass resource.     

Fuzzy logic modeling of bioaccumulation pattern of metals in coastal biota of Ondo State,Nigeria

The accumulation patterns of ten metals in tissues of plant, Eichornia crassipes, and fishes, Hydrocynus forskahlii and Oreochromis mossambicus, were modeled with simple fuzzy classification (SFC) to assess toxic effects of anthropogenic activities on the coastal biota. The plant sample was separated into root, stem, and leaves and the fishes into bones, internal tissues, and muscles. They were analyzed for As, Cd, Cr, Cu, Ni, Pb, V, Fe, Mn, and Zn after wet oxidation of their dried samples. The results were converted into membership functions of five accumulation classes and aggregated with SFC. The classification results showed that there was no metal accumulation in the plant parts while the fishes were classified into low accumulation category. The internal tissues of the fishes had higher metal accumulation than the other parts. Generally, Fe and Mn had highest concentrations in the biota but are natural to the area and may not constitute significant risk. Cr had the highest transfer and accumulation from the coastal water into the aquatic lives and may be indicative of risk prone system being a toxic metal. Metal contaminations in the zone had not significantly accumulated in the biota making them less prone to risk associated with metal accumulation.     

Speciation of heavy metals in biosolids of wastewater treatment plants at Mysore,Karnataka, India

Urban wastewater treatment leads to the generation of large quantities of biosolids. Accumulation of biosolids is a problem of environmental relevance due to the existence of heavy metals in the biosolids. Determination of total metal in biosolid provides information relating pollution levels. Determination of their mobilization capacity and behaviour in the environment is an important task. An experimental approach commonly used for studying the mobility, transport and bioavailability of metal in biosolids is the use of selective sequential extraction procedure. In the present study an attempt has been made to study the heavy metal properties in biosolid samples collected from urban wastewater treatment plants located at Mysore, Karnataka. Few heavy metals selected for the present study are cadmium, chromium, copper, iron, nickel and zinc. The concentration of these metals in biosolids and their partition in different fractions are studied. The speciation of metals based on the sequential extraction scheme was carried out. The concentration of heavy metals is lower than that established by European legislation. The residual fraction has the maximum percentage of heavy metals whereas, only a small fraction of heavy metals (Fe, Zn and Cd) are extracted in the most soluble fractions, exchangeable and carbonate fractions.     

Heavy metal contamination in the Delhi segment of Yamuna basin

Concentration of heavy metals (Cd, Ni, Zn, Fe, Cu, Mn, Pb, Cr, Hg and As) in the waters of River Yamuna and in the soil of agricultural fields along its course in Delhi are reported from 13 sites, spread through the Delhi stretch of Yamuna, starting from the Wazirabad barrage till the Okhla barrage. Varying concentration of heavy metals was found. Peaks were observed in samples collected downstream of Wazirabad and Okhla barrage, indicating the anthropogenic nature of the contamination. The Wazirabad section of the river receives wastewater from Najafgarh and its supplementary drains, whereas the Shahdara drain releases its pollution load upstream of the Okhla barrage. Average heavy metal concentration at different locations in the river water varied in the order of Fe>Cr>Mn>Zn>Pb>Cu>Ni>Hg>As>Cd. The river basin soil shows higher level of contamination with lesser variation than the water samples among sampling locations, thereby suggesting deposition over long periods of time through the processes of adsorption and absorption. The average heavy metal concentration at different locations in soil varied in the order of Fe>Mn>Zn>Cr>Pb>Ni>Hg>Cu>As>Cd.     

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.