Mitigating the Davos dilemma: towards a global self-sustainability index

The ‘Davos dilemma’ posits a sustainability crisis, provoked by rising human population and intense competitive behaviours, in terms of control and access to depleting natural resources. More broadly understood as an ecological problem, rather than just socio-economic behavioural deficiencies, the call is for better integrated social, natural and business-indexed reporting within planetary boundaries. This poses challenges for nationally governed societies to equitably account for self-sustainability performance, in enabling their successive government agendas to re-orientate policies and industry investments as innovation towards achieving this in the longer term. We propose and test a global self-sustainability index for countries across four metrics: economic, environmental, social and innovation. Our tentative findings from a cross-country analysis of 27 countries during 2007–2010 illustrate the approach for wider systematic analysis and as a basis for future large-scale assessments on self-sustainability within and between countries.     

Exploratory study of suspended sediment concentrations downstream of harvested peat bogs

Peat bog harvesting is an important industry in many countries, including Canada. To harvest peat, bogs are drained and drainage water is evacuated towards neighboring rivers, estuaries or coastal waters. High suspended sediment concentrations (SSC) were found in the drainage water at one particular site during the 2001–2002 spring seasons in New Brunswick (Canada). The main objective of this study was to verify this observation at other sites, compare SSC levels leaving harvested peat bogs with those leaving an unharvested bog, and to determine if high SSC events happen only in Spring or all year round. Suspended sediment concentrations were monitored downstream of three harvested peat bogs and an unharvested reference bog located in New Brunswick during the ice free seasons of 2003–2004. On average, SSC at the harvested sites exceeded 25 mg/l, which is the recommended daily maximum concentration, 72% of the time, while the same concentration was exceeded 30% of the time at the unharvested sites. SSC were found to be significantly higher at harvested sites than at the reference sites for all seasons. The highest SSC medians were recorded in the Fall but SSC was elevated in all seasons. High SSC levels in receiving waters may be caused by field ditching activities and insufficient sediment controls. Findings suggest the NB Peat Harvesting 25 mg/l SSC guideline should be reviewed.     

A statistical approach for the assessment and redesign of the Nile Delta drainage system water-quality-monitoring locations

There are several deficiencies in the statistical approaches proposed in the literature for the assessment and redesign of surface water-quality-monitoring locations. These deficiencies vary from one approach to another, but generally include: (i) ignoring the attributes of the basin being monitored; (ii) handling multivariate water quality data sequentially rather than simultaneously; (iii) focusing mainly on locations to be discontinued; and (iv) ignoring the reconstitution of information at discontinued locations. In this paper, a methodology that overcomes these deficiencies is proposed. In the proposed methodology, the basin being monitored is divided into sub-basins, and a hybrid-cluster analysis is employed to identify groups of sub-basins with similar attributes. A stratified optimum sampling strategy is then employed to identify the optimum number of monitoring locations at each of the sub-basin groups. An aggregate information index is employed to identify the optimal combination of locations to be discontinued. The proposed approach is applied for the assessment and redesign of the Nile Delta drainage water quality monitoring locations in Egypt. Results indicate that the proposed methodology allows the identification of (i) the optimal combination of locations to be discontinued, (ii) the locations to be continuously measured and (iii) the sub-basins where monitoring locations should be added. To reconstitute information about the water quality variables at discontinued locations, regression, artificial neural network (ANN) and maintenance of variance extension (MOVE) techniques are employed. The MOVE record extension technique is shown to result in a better performance than regression or ANN for the estimation of information about water quality variables at discontinued locations.     

Bayesian Nonstationary Frequency Analysis of Hydrological Variables1

Ouarda, T.B.M.J. and S. El‐Adlouni, 2011. Bayesian Nonstationary Frequency Analysis of Hydrological Variables. Journal of the American Water Resources Association (JAWRA) 47(3):496‐505. DOI: 10.1111/j.1752‐1688.2011.00544.x Abstract: The present paper provides a discussion of nonstationary frequency analysis models in hydrology with a focus on the Bayesian approach. The Bayesian model provides an efficient estimation framework of hydrological quantiles in the presence of nonstationarity. In nonstationary frequency analysis models, the parameters are functions of covariates, allowing for dependent parameters and trends. The use of the nonstationary Generalized Maximum Likelihood Estimation method in hydrologic frequency analysis is discussed. This model allows using prior information concerning the variables under study and considering a number of models (linear, quadratic, etc.) of the dependence of the parameters on covariates. A discussion is also provided concerning the use of the reversible jump Monte Carlo Markov Chain procedure which allows carrying out the estimation of the posterior distributions of the parameters and the selection of the Bayesian model at the same time. An application to a case study is presented to illustrate the potential of the model.     

INDEXED SEQUENTIAL HYDROLOGIC MODELING FOR HYDROPOWER CAPACITY ESTIMATION1

ABSTRACT: The indexed sequential hydrologic modeling (ISM) methodology is utilized by the Western Area Power Administration as the basis for risk-based estimation of project-dependable hydropower capacity for several federally owned/operated projects. ISM is a technique based on synthetic generation of a series of overlapping short-term inflow sequences obtained directly from the historical record. The validity of ISM is assessed through application to the complex multireservoir hydropower system of the Colorado River basin for providing risk estimates associated with determination of reliable hydrogeneration capacity. Performance of ISM is compared with results from stochastically generated streamflow input data to the Colorado River Simulation System (CRSS). Statistical analysis and comparison of results are based on monthly power capacity, energy generation, and downstream water deliveries. Results indicate that outputs generated from ISM synthetically generated sequences display an acceptable correspondence with those obtained from stochastically generated hydrologic data for the Colorado River Basin.     

MULTIVARIATE ANALYSIS OF WATER QUALITY IN THE RICHIBUCTO DRAINAGE BASIN (NEW BRUNSWICK,CANADA)1

ABSTRACT: Specific conductivity, pH, dissolved oxygen, carbon, phosphorous, and nitrogen species were measured at 36 stations in the Richibucto River drainage basin, including the estuary, in New Brunswick, Canada, over the six‐year period 1996 through 2001. Each station was sampled between 1 and 26 times (mean = 7.5, standard deviation = 6.0) during the ice free seasons without regard to tide. There was significant variance among stations in most parameters. Principal component analysis (PCA) was used to identify the processes explaining the observed variance in water quality. Because of the high variability in specific conductance, stations were first grouped in a freshwater subset and an estuarine (brackish water) subset. For freshwater stations, most of the variance in water quality was explained by pH and total organic carbon, as well as high nutrient concentrations. These high nutrient concentrations, along with water salinity, which varies with flow and tides, are also important in determining water quality variability in brackish water. It is recommended that water quality parameters that were found to explain most of the variance by PCA be monitored more closely, as they are key elements in understanding the variability in water quality in the Richibucto drainage basin. Cluster analyses showed that high phosphorous and nitrate concentrations were mostly found in areas of peat runoff, tributaries receiving treated municipal effluent, and lentic zones upstream of culverts. Peat runoff was also shown to be acidic, whether it is runoff from a harvested area or a natural bog.