An early warning and control system for urban, drinking water quality protection: China’s experience

An event-driven, urban, drinking water quality early warning and control system (DEWS) is proposed to cope with China’s urgent need for protecting its urban drinking water. The DEWS has a web service structure and provides users with water quality monitoring functions, water quality early warning functions, and water quality accident decision-making functions. The DEWS functionality is guided by the principles of control theory and risk assessment as applied to the feedback control of urban water supply systems. The DEWS has been deployed in several large Chinese cities and found to perform well insofar as water quality early warning and emergency decision-making is concerned. This paper describes a DEWS for urban water quality protection that has been developed in China.     

Environmental monitoring of water resources around a municipal landfill of the Rio Grande do Sul state,Brazil

Environmental Science and Pollution Research - In Brazil, landfills are commonly used as a method for the final disposal of waste that is compliant with the legislation. This technique, however,...     

Does Organic Farming Face Distinctive Livestock Welfare Issues? – A Conceptual Analysis

The recent development and growth oforganic livestock farming and the relateddevelopment of national and internationalregulations has fueled discussions amongscientists and philosophers concerning theproper conceptualization of animal welfare.These discussions on livestock welfare inorganic farming draw on the conventionaldiscussions and disputes on animal welfare thatinvolve issues such as different definitions ofwelfare (clinical health, absence of suffering,sum of positive and negative experiences,etc.), the possibility for objective measuresof animal welfare, and the acceptable level ofwelfare. It seems clear that livestock welfareis a value-laden concept and that animalwelfare science cannot be made independent ofquestions of values and ethics. The questioninvestigated here is whether those values thatunderpin organic farming, in particular, alsoaffect the interpretation of livestock welfare,and, if so, how. While some of the issuesraised in connection with organic farming arerelatively uncontroversial, others are not. Theintroduction of organic farming values seems tointroduce new criteria for what counts as goodanimal welfare, as well as a different ethicalbasis for making moral decisions on welfare.Organic farming embodies distinctive systemicor communitarian ethical ideas and the organicvalues are connected to a systemic conceptionof nature, of agriculture, of the farm, and ofthe animal. The new criteria of welfare arerelated to concepts such as naturalness,harmony, integrity, and care. While the organicvalues overlap with those involved in theconventional discussion of animal welfare, someof them suggest a need to set new prioritiesand to re-conceptualize animal welfare – forexample, with respect to ``naturalness,' inrelation to the possibilities for expression ofnatural behavior and in relation to animalintegrity as a concept for organismic harmony.The organic perspective also seems to suggest awider range of solutions to welfare problemsthan changes in farm routines or operations onthe animals. The systemic solutions include thechoice and reproduction of suitable breeds,changes in the farm structure, and changes inthe larger production and consumption system – including consumer perceptions andpreferences. But the organic values may alsocall for sacrifices of individual welfare in aconventional sense in order to advance welfarefrom the perspective of organic farming.Whether this is good or bad cannot be decidedwithout entering into an inquiry and discussionof the values and ethics involved.     

A Comparison of Bayesian Methods for Uncertainty Analysis in Hydraulic and Hydrodynamic Modeling

We evaluate and compare the performance of Bayesian Monte Carlo (BMC), Markov chain Monte Carlo (MCMC), and the Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis in hydraulic and hydrodynamic modeling (HHM) studies. The methods are evaluated in a synthetic 1D wave routing exercise based on the diffusion wave model, and in a multidimensional hydrodynamic study based on the Environmental Fluid Dynamics Code to simulate estuarine circulation processes in Weeks Bay, Alabama. Results show that BMC and MCMC provide similar estimates of uncertainty. The posterior parameter densities computed by both methods are highly consistent, as well as the calibrated parameter estimates and uncertainty bounds. Although some studies suggest that MCMC is more efficient than BMC, our results did not show a clear difference between the performance of the two methods. This seems to be due to the low number of model parameters typically involved in HHM studies, and the use of the same likelihood function. In fact, for these studies, the implementation of BMC results simpler and provides similar results to MCMC. The results of GLUE are, on the other hand, less consistent to the results of BMC and MCMC in both applications. The posterior probability densities tend to be flat and similar to the uniform priors, which can result in calibrated parameter estimates centered in the parametric space.     

APPLICATION OF GEOGRAPHIC INFORMATION SYSTEMS TO GROUNDWATER MONITORING NETWORK DESIGN1

ABSTRACT: Effective monitoring configurations for contaminant detection in groundwater can be designed by analyzing the spatial relationships between candidate sampling sites and aquifer zones susceptible to contamination. Examples of such zones are the domain underlying the contaminant source, zones of probable contaminant migration, and areas occupied by water supply wells. Geographic information systems (GIS) are well-suited to performing key groundwater monitoring network design tasks, such as calculating values for distance variables which quantify the proximity of candidate sites to zones of high pollution susceptibility, and utilizing these variables to quantify relative monitoring value throughout a model domain. Through a case study application, this paper outlines the utility of GIS for detection-based groundwater quality monitoring network design. The results suggest that GIS capabilities for analyzing spatially referenced data can enhance the field-applicability of established methodologies for groundwater monitoring network design.