Multivariate analyses of the effect of an urban wastewater treatment plant on spatial and temporal variation of water quality and nutrient distribution of a tropical mid-order river

Freshwater resources are increasingly scarce due to human activities, and the understanding of water quality variations at different spatial and temporal scales is necessary for adequate management. Here, we analyze the hypotheses that (1) the presence of a wastewater treatment plant (WWTP) and (2) a polluted tributary that drains downstream from the WWTP change the spatial patterns of physicochemical variables (pH, turbidity, dissolved oxygen, and electrical conductivity) and nutrient concentrations (reactive soluble phosphorus, total phosphorus, nitrogen series, total nitrogen, and total dissolved carbon) along a mid-order river in SE Brazil and that these effects depend on rainfall regime. Six study sites were sampled along almost 4 years to evaluate the impacts of human activities, including sites upstream (1–3) and downstream (5–6) from the WWTP. The impacts were observed presenting an increasing trend from the source (site 1) towards Água Quente stream (site 4, the polluted tributary), with signs of attenuation at site 5 (downstream from both WWTP and site 4) and the river mouth (site 6). Input of nutrients by rural and urban runoff was observed mainly at sites 2 and 3, respectively. At sites 4 and 5, the inputs of both untreated and treated wastewaters increased nutrient concentrations and changed physicochemical variables, with significant impacts to Monjolinho River. Seasonal variations in the measured values were also observed, in agreement with the pluviometric indexes of the region. Univariate analyses suggested no effect of the WWTP for most variables, with continued impacts at sites downstream, but non-parametric multivariate analysis indicated that these sites were recovering to chemical characteristics similar to upstream sites, apparently due to autodepuration. Therefore, multivariate methods that allow rigorous tests of multifactor hypotheses can greatly contribute to determine effects of both point and non-point sources in river systems, thus contributing to freshwater monitoring and management.     

Monitoring saltwater intrusion in Rupert Bay,Québec,Canada, after the partial diversion of a major tributary

As part of a large hydroelectric project in northern Québec (Canada), a portion of the flow of the Rupert River was diverted toward the existing La Grande hydroelectric complex. As a result of the partial diversion, the discharge of the Rupert River at its mouth is reduced by an average of 50% annually. This corresponds to an 18% decrease in the total freshwater inflow into the bay and, thus, to a shift of the upstream limit of the saltwater intrusion in Rupert Bay. Changes in saltwater intrusion had been predicted numerically as part of the project’s environmental impact assessment (EIA). In the project’s conditions of authorization, monitoring the hydraulic conditions and the extent of saltwater intrusion in the Rupert Bay was required by government authorities. The objective of this paper is to present the results of this environmental monitoring and, more specifically, to validate the modifications predicted in the EIA in terms of both saltwater intrusion limit and hydraulic conditions in the Rupert Bay. Results obtained during 2 years of monitoring are within the predicted trends and order of magnitude of changes anticipated in the EIA. The results, thus, confirm that the shift of the upstream limit of the saltwater front along the channels of the bay was conservatively predicted by numerical modeling.     

Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

Sustainability indicators in the swine industry of the Brazilian State of Santa Catarina

In recent decades, there has been a growing concern about measuring and evaluating the results of intensive production practices, such as the mode of integration practiced on a large scale by agro-industries. The present study discusses the application and the results of a Sustainability Indicators System in the context of the swine industry in the Brazilian State of Santa Catarina. These indicators, focused on the level of sustainability maturity, can be used as a way to diagnose and compare the efficiency of the industry from a broader perspective. The research findings indicate that most of the pig farms that have been studied can be classified as “in search of sustainability or sustainable.” Nevertheless, there are differences among the dimensions and between the most ranked farms and the others which must be considered for a better design and application of public policies and company strategies toward an effective and balanced social, economic and environmental sustainability.     

Utilization of Waste Lignin and Hydrolysate From Chromium Tanned Waste in Blends of Hot-Melt Extruded PVA-Starch

The demand for biodegradable plastic material is increasing worldwide. However, the cost remains high in comparison with common forms of plastic. Requirements comprise low cost, good UV-stability and mechanical properties, as well as solubility and water uptake lead to the preparation of multi-component polymer blends based on polyvinyl alcohol and starch in combination with waste products that are hard to utilize—waste lignin and hydrolysate extracted from chromium tanned waste. Surprisingly the addition of such waste products into PVA gives rise to blends with better biodegradability than commercial PVA in an aquatic aerobic environment with non-adapted activated sludge. These blends also exhibited greater solubility in the water and UV stability than commercial PVA. Tests on the processing properties of the blends (melt flow index, tensile strength and elongation at break of the films) as well as their mechanical properties showed that materials based on these blends might be applied in agriculture (for example as the systems for controlled-release pesticide or fertilizer) and, somewhat, in the packaging sector.     

Trees on the move: using decision theory to compensate for climate change at the regional scale in forest social-ecological systems

Regional Environmental Change - The adaptation of social-ecological systems such as managed forests depends largely on decisions taken by forest managers who must choose among a wide range of...     

From mixed farming to intensive agriculture: energy profiles of agriculture in Quebec,Canada, 1871–2011

Regional Environmental Change - This article presents an energy analysis of Quebec agroecoystems at five periods of time: 1871, 1931, 1951, 1981, and 2011, calculating for each year the various...     

From vineyards to feedlots: a fund-flow scanning of sociometabolic transition in the Vallès County (Catalonia) 1860–1956–1999

Regional Environmental Change - We analyse the changes to agricultural metabolism in four municipalities of Vallès County (Catalonia, Iberia) by accounting for their agroecosystem funds and...     

Influence of community-based natural resource management strategies in the resilience of social-ecological systems

Different social-ecological systems around the world are managed under community-based natural resource management (CBNRM) strategies. This paper analyses how CBNRM strategies influence the resilience of social-ecological systems to the disturbances they face, drawing upon the experience of three Latin American cases (two in Mexico and one in Colombia). The cases differ in their CBNRM approach and in the time these governance systems have been in place. By using a mixed-method approach, we review the socio-ecological history and describe each CBNRM characteristics. We then assess their resilience to socioeconomic and environmental disturbances through a set of indicators. We found that CBNRM strategies influence positively and negatively resilience and that internal decisions might address important threats. On the positive side, the social-ecological systems with longer tradition of CBNRM and more local buy-in of commonly agreed objectives appear to be more resilient to environmental challenges. But, internal governance factors such as power imbalances, poor income distribution, and gender inequities linked to CBNRM undermine resilience and foster out migration. Finally, communities appear to have limited capacities to cope with external disturbances such as global drivers of change or national policies that negatively affect their social-ecological resilience.