Geological characterization of the Prestige sinking area

The tanker Prestige sank off NW Iberia on the 19th November 2002. The stern and bow of the Prestige wreck are located on the southwestern edge of the Galicia Bank, at 3565 m and 3830 m water depths, respectively. This bank is a structural high controlled by major faults with predominant N-S, NNE-SSW, and NNW-SEE trends. It is characterized by moderate to low seismic activity. The faults have controlled the local depositional architecture, deforming, fracturing, relocating and distributing sediments since the Valangian (early Cretaceous). The Prestige sinking area corresponds to an asymmetric half-graben structure with a N-S trend, which conditions the present-day morphology. The faulted flank outcrops and its activity and erosion have favoured the occurrence of mass-movements (slumps, slump debris, mass-flows and turbidity currents), building valleys and depositional lobes. Nearsurface sediments comprise mostly terrigenous and biogenous turbiditic muds and sands with a minor presence of hemipelagic muds, except on the fault scarp where pelagites predominate. Potential geological hazards resulting from tectonic and sedimentary processes affect almost the entire Prestige sinking area.     

Estimation of recharge from floods in disconnected stream-aquifer systems

Stream-aquifer interaction has been the subject of much research for cases of good hydraulic connection (continuous saturated zone) between a river and an aquifer. Under these conditions, floods do not represent a very large net input to the aquifer because most of the water that enters the aquifer during the flood returns to the river when its stage recedes. The situation is different in disconnected stream-aquifer systems, where the streambed lies above the water level in the aquifer, thus preventing return flow from the aquifer. Under these conditions, floods may represent large, but hard to quantify, water inputs. Here, we present a methodology to estimate recharge from floods for disconnected stream-aquifer systems. Recharge is estimated as the product of a flood time function (dependent on the streamflow) and an unknown factor, which is obtained from calibrating a ground water flow model to aquifer heads. The approach can also benefit from concentration data, which can be very informative when river water concentrations vary over time. This methodology is applied to a field situation where recharge from river flooding is found to amount to nearly 15 million m(3)/year on the average, which represents 40% of the total aquifer inputs. Recharge from flooding helps explain major head recoveries, suggesting that basin water management programs should allow some floods to occur.     

Computational and conceptual issues in the calibration of seawater intrusion models

The inverse problem of seawater intrusion (SWI) is reviewed. It represents a challenge because of both conceptual and computational difficulties and because coastal aquifer models display many singularities: (1) head measurements need to be complemented with density information; (2) salinity concentration data are very sensitive to flow within the borehole. Data problems can be reduced by incorporating the measurement process within model calibration; (3) SWI models are extremely sensitive to aquifer bottom topography; (4) the initial conditions may be far from steady state and depend on the location and type of sea-aquifer connection. Problems with aquifer geometry and initial conditions can be addressed by parameterization, which allows for modification during inversion. The four sets of difficulties can be partly overcome by using tidal response and electrical conductivity data, which are highly informative and provide extensive coverage. Still, SWI inversion is extremely demanding from a computation point of view. Computational improvements are discussed.     

Sediment and Nutrient Deposition Associated with Hurricane Wilma in Mangroves of the Florida Coastal Everglades

The distribution of mangrove biomass and forest structure along Shark River estuary in the Florida Coastal Everglades (FCE) has been correlated with elevated total phosphorus concentration in soils thought to be associated with storm events. The passage of Hurricane Wilma across Shark River estuary in 2005 allowed us to quantify sediment deposition and nutrient inputs in FCE mangrove forests associated with this storm event and to evaluate whether these pulsing events are sufficient to regulate nutrient biogeochemistry in mangrove forests of south Florida. We sampled the spatial pattern of sediment deposits and their chemical properties in mangrove forests along FCE sites in December 2005 and October 2006. The thickness (0.5 to 4.5 cm) of hurricane sediment deposits decreased with distance inland at each site. Bulk density, organic matter content, total nitrogen (N) and phosphorus (P) concentrations, and inorganic and organic P pools of hurricane sediment deposits differed from surface (0–10 cm) mangrove soils at each site. Vertical accretion resulting from this hurricane event was eight to 17 times greater than the annual accretion rate (0.30 ± 0.03 cm year⁻¹) averaged over the last 50 years. Total P inputs from storm-derived sediments were equivalent to twice the average surface soil nutrient P density (0.19 mg cm⁻³). In contrast, total N inputs contributed 0.8 times the average soil nutrient N density (2.8 mg cm⁻³). Allochthonous mineral inputs from Hurricane Wilma represent a significant source of sediment to soil vertical accretion rates and nutrient resources in mangroves of southwestern Everglades. The gradient in total P deposition to mangrove soils from west to east direction across the FCE associated with this storm event is particularly significant to forest development due to the P-limited condition of this carbonate ecosystem. This source of P may be an important adaptation of mangrove forests in the Caribbean region to projected impacts of sea-level rise.     

Environmental Forcing of Phytoplankton in a Mediterranean Estuary (Guadiana Estuary,South-western Iberia): A Decadal Study of Anthropogenic and Climatic Influences

Phytoplankton seasonal and interannual variability in the Guadiana upper estuary was analyzed during 1996–2005, a period that encompassed a climatic controlled reduction in river flow that was superimposed on the construction of a dam. Phytoplankton seasonal patterns revealed an alternation between a persistent light limitation and episodic nutrient limitation. Phytoplankton succession, with early spring diatom blooms and summer–early fall cyanobacterial blooms, was apparently driven by changes in nutrients, water temperature, and turbulence, clearly demonstrating the role of river flow and climate variability. Light intensity in the mixed layer was a prevalent driver of phytoplankton interannual variability, and the increased turbidity caused by the Alqueva dam construction was linked to pronounced decreases in chlorophyll a concentration, particularly at the start and end of the phytoplankton growing period. Decreases in annual maximum and average abundances of diatoms, green algae, and cyanobacteria were also detected. Furthermore, chlorophyll a decreases after dam filling and a decrease in turbidity may point to a shift from light limitation towards a more nutrient-limited mode in the near future.     

Contribution of a sewage sludge application to the short-term carbon sequestration across a wide range of agricultural soils

The atmospheric levels of carbon dioxide (CO₂) and other greenhouse gases (GHGs) have increased dramatically since the industrial revolution. The atmospheric enrichment with CO₂ and other GHGs has resulted in multiple negative consequences: such as the increase in the average temperature and the rise of the sea level. Hence, there is a growing interest in developing feasible methods to reduce the atmospheric levels of these gases. One of these strategies is to enhance C sequestration through the increase of soil organic carbon (SOC) pool by the amendment of agricultural soils with sewage sludge. However, there is considerable uncertainty about the effects (positive or negative) of sewage sludge applications on the SOC pool. Thus, a simple approach developed under laboratory conditions is presented to discern the effect of a single sewage sludge application of 50 t ha⁻¹ on the short-term SOC pool in 60 contrasting agricultural soils. The role of soil factors in the C sequestration of the recently added carbon was also studied. The application of sewage sludge supposed a mean increase of 1.7 ± 1.6 g SOC kg⁻¹, with peak increases of up to 3.8 g SOC kg⁻¹ and decreases of up to 4.6 g SOC kg⁻¹. The initial SOC contents conditioned the C sequestration after sewage sludge application, and no other soil property was related.     

Mapping soil pollution by spatial analysis and fuzzy classification

Spatial analysis and fuzzy classification techniques were used to estimate the spatial distributions of heavy metals in soil. The work was applied to soils in a coastal region that is characterized by intense urban occupation and large numbers of different industries. Concentrations of heavy metals were determined using geostatistical techniques and classes of risk were defined using fuzzy classification. The resulting prediction mappings identify the locations of high concentrations of Pb, Zn, Ni, and Cu in topsoils of the study area. The maps show that areas of high pollution of Ni and Cu are located at the northeast, where there is a predominance of industrial and agricultural activities; Pb and Zn also occur in high concentrations in the northeast, but the maps also show significant concentrations of Pb and Zn in other areas, mainly in the central and southeastern parts, where there are urban leisure activities and trade centers. Maps were also prepared showing levels of pollution risk. These maps show that (1) Cu presents a large pollution risk in the north–northwest, midwest, and southeast sectors, (2) Pb represents a moderate risk in most areas, (3) Zn generally exhibits low risk, and (4) Ni represents either low risk or no risk in the studied area. This study shows that combining geostatistics with fuzzy theory can provide results that offer insight into risk assessment for environmental pollution.