The role of burrowing beds and burrows of the SW Atlantic intertidal crab Chasmagnathus granulata in trapping organochlorine pesticides

The effect of crab beds and bioturbation activity of the SW Atlantic intertidal crab Chasmagnathus granulata on the organochlorine pesticide (OCP) concentrations in Bahía Blanca estuary, Argentina were studied. Total OCP concentration was significantly lower inside than outside the crab burrows. Nevertheless, the concentrations from outside the crab beds were lower than from outside crab burrows, which indicated that crab beds act as sinks of sediment-bound OCP due to the bioturbation activities of the crabs. The same distribution patterns were found in all sediments as well as in crabs, being cyclodienes>HCHs>DDTs, although large amounts of metabolites rather than the respective parental were found in the organism showing the capacity of C. granulata for metabolising parental compounds. These more water-soluble compounds are excreted by the faeces and finally removed by tidal flushing to the sea. Our results suggest that crabs when present play a role in the distribution of sediment-bound OCP and the crab beds are modifiers of the dynamic of organic pollutants in estuarine areas.     

Prediction of the Madden�CJulian oscillation with the POAMA dynamical prediction system

Predictions of the Madden?CJulian oscillation (MJO) are assessed using a 10-member ensemble of hindcasts from POAMA, the Australian Bureau of Meteorology coupled ocean?Catmosphere seasonal prediction system. The ensemble of hindcasts was initialised from observed atmosphere and ocean initial conditions on the first of each month during 1980?C2006. The MJO is diagnosed using the Wheeler-Hendon Real-time Multivariate MJO (RMM) index, which involves projection of daily data onto the leading pair of eigenmodes from an analysis of zonal winds at 200 and 850?hPa and outgoing longwave radiation (OLR) averaged about the equator. Forecasts of the two component (RMM1 and RMM2) index are quantitatively compared with observed behaviour derived from NCEP reanalyses and satellite OLR using the bivariate correlation skill, root-mean-square error (RMSE), and measures of the MJO amplitude and phase error. Comparison is also made with a simple vector autoregressive (VAR) prediction model of RMM as a benchmark. Using the full hindcast set, we find that the MJO can be predicted with the POAMA ensemble out to about 21?days as measured by the bivariate correlation exceeding 0.5 and the bivariate RMSE remaining below ~1.4 (which is the value for a climatological forecast). The VAR model, by comparison, drops to a correlation of 0.5 by about 12?days. The prediction limit from POAMA increases by less than 2?days for times when the MJO has large initial amplitude, and has little sensitivity to the initial phase of the MJO. The VAR model, on the other hand, shows a somewhat larger increase in skill for times of strong MJO variability and has greater sensitivity to initial phase, with lower skill for times when MJO convection is developing in the Indian Ocean. The sensitivity to season is, however, greater for POAMA, with maximum skill occurring in the December?CJanuary?CFebruary season and minimum skill in June?CJuly?CAugust. Examination of the MJO amplitudes shows that individual POAMA members have slightly above observed amplitude after a spin-up of about 10?days, whereas examination of the MJO phase error reveals that the model has a consistent tendency to propagate the MJO slightly slower than observed. Finally, an estimate of potential predictability of the MJO in POAMA hindcasts suggests that actual MJO prediction skill may be further improved through continued development of the dynamical prediction system.     

The impact of atmospheric initialisation on seasonal prediction of tropical Pacific SST

The impact of realistic atmospheric initialisation on the seasonal prediction of tropical Pacific sea surface temperatures is explored with the Predictive Ocean–Atmosphere Model for Australia (POAMA) dynamical seasonal forecast system. Previous versions of POAMA used data from an Atmospheric Model Intercomparison Project (AMIP)-style simulation to initialise the atmosphere for the hindcast simulations. The initial conditions for the hindcasts did not, therefore, capture the true intra-seasonal atmospheric state. The most recent version of POAMA has a new Atmosphere and Land Initialisation scheme (ALI), which captures the observed intra-seasonal atmospheric state. We present the ALI scheme and then compare the forecast skill of two hindcast datasets, one with AMIP-type initialisation and one with realistic initial conditions from ALI, focussing on the prediction of El Niño. For eastern Pacific (Niño3) sea surface temperature anomalies (SSTAs), both experiments beat persistence and have useful SSTA prediction skill (anomaly correlations above 0.6) at all lead times (forecasts are 9 months duration). However, the experiment with realistic atmospheric initial conditions from ALI is an improvement over the AMIP-type initialisation experiment out to about 6 months lead time. The improvements in skill are related to improved initial atmospheric anomalies rather than an improved initial mean state (the forecast drift is worse in the ALI hindcast dataset). Since we are dealing with a coupled system, initial atmospheric errors (or differences between experiments) are amplified though coupled processes which can then lead to long lasting errors (or differences).     

A paleo‐hydro‐geomorphological perspective on urban flood risk assessment

Comprehensive flood risk assessment requires enhanced understanding of the coevolution of the river and its floodplain occupation. Paleoflood analysis to determine flood prone areas in combination with numerical simulations to estimate flood hazard and a historical analysis of urban development to consider the evolution of exposure to floods is a possible way forward. The well‐documented 2006 extreme flood in the Biobío River system and the impacted metropolitan area of Concepción, Chile (~1 million inhabitants) was used as a complex scenario to test the reliability of the proposed method. Results showed that flood prone areas determined with hydro‐geomorphological methods are consistent with those computed with numerical models based on detailed digital elevation models. The flood generation via superficial flow pathways resulting in inundated areas could explain that rivers tend to reactivate paleochannels in extreme conditions. Urban development progressively increased the city's exposure to floods from 0 ha in 1,751 to 1,363 ha in 2006 evidencing a lack of appropriate flood risk management. The 100‐year peak discharge resulted in a high flood risk for about 5% of the total urbanized area of Concepción, and higher discharges are likely to reactivate a paleochannel that crosses the current city centre. We conclude that the proposed paleo hydro‐geomorphology, hydraulic, and urban planning multimethod approach is a necessary tool to enhance understanding of flood risk in complex scenarios to improve flood risk management.     

Interval‐Based Diagnosis of Biological Systems – a Powerful Tool for Highly Uncertain Anaerobic Digestion Processes

Anaerobic digestion (AD) is a highly nonlinear time‐varying process commonly used for biological wastewater treatment, which is subject to large disturbances of both influent concentrations, and flow rates that may lead the process to a breakdown. In order to compensate the effect of these disturbances, the dynamics of the main state variables – including biomass – must be closely monitored and used to improve the process performance. However, AD processes still suffer from a lack of reliable and cheap sensors of key process variables to insure the right process operation. This has led to the development of estimation schemes, which infer the information of such key variables from the available measurements. Nevertheless, reliable measurements are not always possible to get because these readings may be corrupted by noise or erroneous due to sensor failures and as a consequence, they may lead to deteriorated control efforts and the eventual crash of the AD process. In this article, we propose an integrated system for the detection, isolation, and analysis of faults in AD processes by using interval observers (IO). The proposed approach was experimentally implemented on a 1‐m³ pilot scale anaerobic digester. Based on the comparison between the measured outputs and their corresponding estimates, results show that this approach was able to detect sensor failures as well as faults in the basic hypotheses made during the design step.     

Analysis of thunderstorm and lightning activity associated with sprites observed during the EuroSprite campaigns: Two case studies

During the summers of 2003 to 2006 sprites were observed over thunderstorms in France by cameras on mountain tops in Southern France. The observations were part of a larger coordinated effort, the EuroSprite campaigns, with data collected simultaneously from other sources including the French radar network for precipitation structure, Meteosat with images of cloud top temperature and the Météorage network for detection of cloud-to-ground (CG) flash activity. In this paper two storms are analyzed, each producing 27 sprite events. Both storms were identified as Mesoscale Convective Systems (MCS) with a trailing stratiform configuration (ST) and reaching a maximum cloud area of ~ 120,000 km². Most of the sprites were produced while the stratiform area was clearly developed and during periods of substantial increase of rainfall in regions with radar reflectivity between 30 and 40 dBZ. The sprite-producing periods followed a maximum in the CG lightning activity and were characterized by a low CG flash rate with a high proportion of + CG flashes, typically around 50%. All sprites were associated with + CGs except one which was observed after a − CG as detected by the Météorage network. This − CG was estimated to have − 800 C km charge moment change. The peak current of sprite-producing + CG (SP + CG) flashes was twice the average value of + CGs and close to 60 kA with little variation between the periods of sprite activity. The SP + CG flashes were further characterized by short time intervals before a subsequent CG flash (median value < 0.5 s) and with clusters of several CG flashes which suggest that SP + CG flashes often are part of multi-CG flash processes. One case of a lightning process associated with a sprite consisted of 7 CG flashes.     

Coupled surface and subsurface flow modeling of natural hillslopes in the Aburrá Valley (Medellín,Colombia)

Numerical results are presented of surface-subsurface water modeling of a natural hillslope located in the Aburrá Valley, in the city of Medellín (Antioquia, Colombia). The integrated finite-element hydrogeological simulator HydroGeoSphere is used to conduct transient variably saturated simulations. The objective is to analyze pore-water pressure and saturation variation at shallow depths, as well as volumes of water infiltrated in the porous medium. These aspects are important in the region of study, which is highly affected by soil movements, especially during the high-rain seasons that occur twice a year. The modeling exercise considers rainfall events that occurred between October and December 2014 and a hillslope that is currently monitored because of soil instability problems. Simulation results show that rainfall temporal variability, mesh resolution, coupling length, and the conceptual model chosen to represent the heterogeneous soil, have a noticeable influence on results, particularly for high rainfall intensities. Results also indicate that surface-subsurface coupled modeling is required to avoid unrealistic increase in hydraulic heads when high rainfall intensities cause top-down saturation of soil. This work is a first effort towards fostering hydrogeological modeling expertise that may support the development of monitoring systems and early landslide warning in a country where the rainy season is often the cause of hydrogeological tragedies associated with landslides, mud flow or debris flow.     

The role of the Río de la Plata bottom salinity front in accumulating debris

The Río de la Plata, one of the most important South American estuarine environments, is characterized by a bottom salinity front that generates an ecotone between the river and the estuary. Based on bottom trawls and costal sampling we describe the distribution, types, and amount of debris found in the bottom and shoreline across this front. Plastics and plastic bags were the main debris types in both areas. Concentrations of total debris upriver the front were always significantly higher than downriver the front showing that the front acts as a barrier accumulating debris. Moreover, a large part of debris end ups accumulated in the coastal area upriver the frontal position. This area is particularly sensitive because the coastline encompasses an UNESCO Man and the Biosphere Reserve and a Ramsar site, and due to the ecological significance of the front for many valuable species.