Urban stormwater inputs to an adapted coastal wetland : role in water treatment and impacts on wetland biota

The Lake Pertobe wetland system is a semi-natural wetland that has been modified primarily for recreational use. However, this lake system receives stormwater from much of the central business district of Warrnambool City (Victoria, Australia) and serves as a buffer zone between the stormwater system and the Merri River and Merri Marine Sanctuary. This work considers the impact of stormwater inputs on Lake Pertobe and the effectiveness of the lake in protecting the associated marine sanctuary. Sediment contaminants (including heavy metals and polycyclic aromatic hydrocarbons (PAHs)) and water quality parameters within the lake, groundwater and stormwater system were measured. Water quality parameters were highly variable between stormwater drains and rain events. Suspended solids rapidly settled along open drains and shortly after entering the lake. Groundwater inputs increased both salinity and dissolved nitrogen in some stormwater drains. Some evidence of bioaccumulation of metals in the food chain was identified and sediment concentrations of several PAHs were very high. The lake acted as a sink for PAHs and some metals and reductions in Escherichia coli, biological oxygen demand and total phosphorus were observed, affording some protection to the associated marine sanctuary. Nutrient retention was inadequate overall and it was identified that managing the lake primarily as a recreational facility impacted on the effectiveness of stormwater treatment in the system.

A biomimetic sensor for the detection of lead in water.

The monitoring of lead (II) ions (Pb(2+)) in water is essential for both human health and the environment. Herein, a simple yet innovative biosensor for Pb(2+) detection is presented. The sensor is developed by the self-assembly of gold nanoparticles (GNPs) core-satellite structure using naturally occurring tripeptide glutathione (GSH) as linker. The addition of Pb(2+) caused a red-to-blue color change and the localized surface plasmon resonance (LSPR) band was shifted to ca. 650nm. The limit of detection (LOD) is found to be 47.6nM (9.9ppb) by UV-vis spectroscopy with high selectivity against other heavy metals. This method offers a new strategy for heavy metal detection using functionalized GNPs.

Ecosystem relevance of variable jellyfish biomass in the Irish Sea between years, regions and water types

Monitoring the abundance and distribution of taxa is essential to assess their contribution to ecosystem processes. For marine taxa that are difficult to study or have long been perceived of little ecological importance, quantitative information is often lacking. This is the case for jellyfish (medusae and other gelatinous plankton). In the present work, 4 years of scyphomedusae by-catch data from the 2007-2010 Irish Sea juvenile gadoid fish survey were analysed with three main objectives: (1) to provide quantitative and spatially-explicit species-specific biomass data, for a region known to have an increasing trend in jellyfish abundance; (2) to investigate whether year-to-year changes in catch-biomass are due to changes in the numbers or in the size of medusa (assessed as the mean mass per individual), and (3) to determine whether inter-annual variation patterns are consistent between species and water masses. Scyphomedusae were present in 97% of samples (N=306). Their overall annual median catch-biomass ranged from 0.19 to 0.92gm-3 (or 8.6 to 42.4gm-2). Aurelia aurita and Cyanea spp. (Cyanea lamarckii and Cyanea capillata) made up 77.7% and 21.5% of the total catch-biomass respectively, but species contributions varied greatly between sub-regions and years. No consistent pattern was detected between the distribution and inter-annual variations of the two genera, and contrasting inter-annual patterns emerged when considering abundance either as biomass or as density. Significantly, A.aurita medusae were heavier in stratified than in mixed waters, which we hypothesize may be linked to differences in timing and yield of primary and secondary productions between water masses. These results show the vulnerability of time-series from bycatch datasets to phenological changes and highlight the importance of taking species- and population-specific distribution patterns into account when integrating jellyfish into ecosystem models.

Demo abstract: wind measurements for water quality studies in urban reservoirs

Water quality monitoring and prediction are critical for ensuring the sustainability of water resources which are essential for social security, especially for countries with limited land like Singapore. For example, the Singapore government identified water as a new growth sector and committed in 2006 to invest S$ 330 million over the following five years for water research and development [1]. To investigate the water quality evolution numerically, some key water quality parameters at several discrete locations in the reservoir (e.g., dissolved oxygen, chlorophyll, and temperature) and some environmental parameters (e.g., the wind distribution above water surface, air temperature and precipitation) are used as inputs to a three-dimensional hydrodynamics-ecological model, Estuary Lake and Coastal Ocean Model - Computational Aquatic Ecosystem Dynamics Model (ELCOM-CAEDYM) [2]. Based on the calculation in the model, we can obtain the distribution of water quality in the whole reservoir. We can also study the effect of different environmental parameters on the water quality evolution, and finally predict the water quality of the reservoir with a time step of 30 seconds. In this demo, we introduce our data collection system which enables water quality studies with real-time sensor data.

Monitoring the ungulate prey of the Komodo dragon Varanus komodoensis: distance sampling or faecal counts?

Monitoring the abundances of prey is important for informing the management of threatened and endangered predators. We evaluated the usefulness of faecal counts and distance sampling for monitoring the abundances of rusa deer Rusa timorensis, feral pig Sus scrofa and water buffalo Bubalus bubalis, the three key prey of the Komodo dragon Varanus komodoensis, at 11 sites on five islands in and around Komodo National Park, eastern Indonesia. We used species-specific global detection functions and cluster sizes (i.e. multiple covariates distance sampling) to estimate densities of rusa deer and feral pig, but there were too few observations to estimate densities of water buffalo. Rusa deer densities varied from from 2.5 to 165.5 deer/km2 with coefficients of variation (CVs) of 15-105%. Feral pig densities varied from 0.0 to 25.2 pigs/km 2 with CVs of 25-106%. There was a positive relationship between estimated faecal densities and estimated population densities for both rusa deer and feral pig: the form of the relationship was non-linear for rusa deer, but there was similar support for linear and non-linear relationships for feral pig. We found that faecal counts were more useful when ungulate densities were too low to estimate densities with distance sampling. Faecal count methods were also easier for field staff to conduct than distance sampling. Because spatial and temporal variation in ungulate density is likely to influence the population dynamics of the Komodo dragon, we recommend that annual monitoring of ungulates in and around Komodo National Park be undertaken using distance sampling and faecal counts. The relationships reported here will also be useful for managers establishing monitoring programmes for feral pig, rusa deer and water buffalo elsewhere in their native and exotic ranges.

From Smart Meters To Smart Decisions: Web-Based Support For The Water Efficient Household

Smart water metering technologies for residential buildings offer, in principle, great opportunities for sustainable urban water management. However, much of this potential is as yet unrealized. Despite that several ICT solutions have already been deployed aiming at optimum operations on the water utilities side (e.g. real time control for water networks, dynamic pump scheduling etc.), little work has been done to date on the consumer side. This paper presents a web-based platform targeting primarily the household end user. The platform enables consumers to monitor, on a real-time basis, the water demand of their household, providing feedback not only on the total water consumption and relevant costs but also on the efficiency (or otherwise) of specific indoor and outdoor uses. Targeting the reduction of consumption, the provided feedback is combined with notifications about possible leakages\bursts, and customised suggestions to improve the efficiency of existing household uses. It also enables various comparisons, with past consumption or even with that of similar households, aiming to motivate further the householder to become an active player in the water efficiency challenge. The issue of enhancing the platform’s functionality with energy timeseries is also discussed in view of recent advances in smart metering and the concept of “smart cities”. The paper presents a prototype of this web-based application and critically discusses first testing results and insights. It also presents the way in which the platform communicates with central databases, at the water utility level. It is suggested that such developments are closing the gap between technology availability and usefulness to end users and could help both the uptake of smart metering and awareness raising leading, potentially, to significant reductions of urban water consumption. The work has received funding from the European Union FP7 Programme through the iWIDGET Project, under grant agreement no318272.

Decision Tree Classification Model In Water Supply Network

With the service life of water supply network (WSN) growth, the growing phenomenon of aging pipe network has become exceedingly serious. As urban water supply network is hidden underground asset, it is difficult for monitoring staff to make a direct classification towards the faults of pipe network by means of the modern detecting technology. In this paper, based on the basic property data (e.g. diameter, material, pressure, distance to pump, distance to tank, load, etc.) of water supply network, decision tree algorithm (C4.5) has been carried out to classify the specific situation of water supply pipeline. Part of the historical data was used to establish a decision tree classification model, and the remaining historical data was used to validate this established model. Adopting statistical methods were used to access the decision tree model including basic statistical method, Receiver Operating Characteristic (ROC) and Recall-Precision Curves (RPC). These methods has been successfully used to assess the accuracy of this established classification model of water pipe network. The purpose of classification model was to classify the specific condition of water pipe network. It is important to maintain the pipeline according to the classification results including asset unserviceable (AU), near perfect condition (NPC) and serious deterioration (SD). Finally, this research focused on pipe classification which plays a significant role in maintaining water supply networks in the future.

A Diagnostic Assessment Of Evolutionary Multiobjective Optimization For Water Resources Systems

This study contributes a rigorous diagnostic assessment of state-of-the-art multiobjective evolutionary algorithms (MOEAs) and highlights key advances that the water resources field can exploit to better discover the critical tradeoffs constraining our systems. This study provides the most comprehensive diagnostic assessment of MOEAs for water resources to date, exploiting more than 100,000 MOEA runs and trillions of design evaluations. The diagnostic assessment measures the effectiveness, efficiency, reliability, and controllability of ten benchmark MOEAs for a representative suite of water resources applications addressing rainfall-runoff calibration, long-term groundwater monitoring (LTM), and risk-based water supply portfolio planning. The suite of problems encompasses a range of challenging problem properties including (1) many-objective formulations with 4 or more objectives, (2) multi-modality (or false optima), (3) nonlinearity, (4) discreteness, (5) severe constraints, (6) stochastic objectives, and (7) non-separability (also called epistasis). The applications are representative of the dominant problem classes that have shaped the history of MOEAs in water resources and that will be dominant foci in the future. Recommendations are provided for which modern MOEAs should serve as tools and benchmarks in the future water resources literature.

Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Humoral immune response of water buffalo monitored with three different antigens of Toxocara vitulorum

Humoral immune response of water buffalo naturally infected with Toxocara vitulorum was monitored using three different antigens of this parasite in serum and colostrum of buffalo cows and calves. Soluble extract (Ex) and excretory/secretory (ES) larval antigens and perienteric fluid antigen (Pe) of adult T vitulorum were used to measure the antibody levels by an indirect ELISA. Serum of 7-12 buffalo cows for the first 365 days and colostrum of the same number of buffalo cows for the first 60 days of parturition, and serum of 8-10 buffalo calves for the first 365 days afterbirth were assayed. The ELISA detected antibodies against all three T vitulorum antigens in the colostrum and serum of 100% of buffalo cows and calves examined. The highest antibody levels against Ex, ES and Pe antigens were detected in the buffalo cow sera during the perinatal period and were maintained at high levels through 300 days after parturition. on the other hand, colostrum antibody concentrations of all three antigens were highest on the first day post-parturition, but decreased sharply during the first 15 days. Concomitantly to the monitoring of immune response, the parasitic status of the calves was also evaluated. In calves, antibodies passively acquired were at the highest concentrations 24 h after birth and remained at high levels until 45 days coincidentally with the peak of T vitulorum infection. The rejection of the worms by the calves occurred simultaneously with the decline of antibody levels, which reached their lowest levels between 76 and 150 days. Thereafter, probably because of the presence of adults/larvae stimulation, the calves acquired active immunity and the antibodies started to increase slightly in the serum and plateaued between the days 211 and 365. All three antigens were detected by the serum antibodies of buffalo calves; however, the concentration of anti-Pe antibody was higher than anti-EX and anti-ES, particularly after 90 days of age. By conclusion, the buffalo cows develop immunity and keep high levels of antibodies against T vitulorum-Ex, ES and Pe antigens and these antibodies are transferred to their calves through the colostrum. This passively acquired immunity does not protect the calves against the acquisition of the infection, but these antibodies, passively or actively acquired, may have an important role during worm rejection by the calves and prevention of intestinal reinfection. (C) 2004 Elsevier B.V. All rights reserved.

Candida parapsilosis complex water isolates from a haemodialysis unit: biofilm production and in vitro evaluation of the use of clinical antifungals

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Occurrence of fungi in water used at a haemodialysis centre

Aims: The aim of this study was to identify and determine the diversity, occurrence and distribution of fungi in water used at a haemodialysis centre.Methods and Results: Samples in the hydraulic circuit for the distribution of the water, dialysate samples and samples of sterilization solution from dialysers were collected over a 3-month period, and 500 ml of each sample was filtered through membranes. All together 116 isolates of fungi were recovered from 89% of all water samples collected inside the haemodialysis unit, with prevalence of moulds in tap water samples and of yeasts in dialysate samples. Fusarium spp. was the most abundant genus found, whereas Candida parapsilosis was the predominant yeast species.Conclusions: This study demonstrated that various fungi were present in the water system. These data suggest the inclusion of the detection and quantification of fungi in the water of haemodialysis.Significance and Impact of the Study: The recovery of fungi from aqueous haemodialysis environments implies a potential risk for haemodialysis patients and indicates the need for continuous maintenance and monitoring. Further studies on fungi in haemodialysis water systems are required to investigate the organism ability to persist, their role in biofilm formation and their clinical significance.