Description: This paper presents a critical review of the physical impacts of decentralized water supply systems on existing centralized water infrastructures. This paper highlights the combination of centralized and decentralized systems, which is referred to as hybrid water supply systems. The system is hypothesized to generate more sustainable and resilient urban water systems. The basic concept is to use decentralized water supply options such as rainwater tanks, storm water harvesting and localized wastewater treatment and reuse in combination with centralized systems. Currently the impact of hybrid water supply technologies on the operational performance of the downstream infrastructure and existing treatment processes is yet to be known. The paper identifies a number of significant research gaps related to interactions between centralized and decentralized urban water services. It indicates that an improved understanding of the interaction between these systems is expected to provide a better integration of hybrid systems by improved sewerage and drainage design, as well as facilitate operation and maintenance planning. The paper also highlights the need for a framework to better understand the interaction between different components of hybrid water supply systems.

Description: The study of the impact of economic activities on natural resources through global supply chains is increasingly demanded in the context of the growing globalization of economies and product fragmentation. Taking Spain as a case study and a sector with significant economic and environmental impacts, the agri-food industry, the objective of this work is two-fold. First, we estimate the associated water impact, both from the production and consumption perspectives, paying special attention to the water embodied in production exchanges among countries and sectors. To that aim, we use an environmentally-extended multiregional input-output model (MRIO). Second, we assess the main driving factors behind changes in direct and embodied water consumption between the years 1995 and 2009 by means of a structural decomposition analysis. The MRIO model provides a comprehensive estimate of the economic linkages among regions and economic sectors and, therefore, allows calculating the environmental impacts over international value chains. The results indicate that the food industry exerts large impacts on global water resources, particularly given the remarkable interactions with the domestic and foreign agricultural sectors, These growing linkages show how consumption patterns, and, therefore, lifestyles, involve large environmental impacts through the whole and global supply chains.

Description: Cohesive sediment has different characteristics compared to non-cohesive sediment. The density and size of a cohesive sediment aggregate (a so-called, floc) continuously changes through the flocculation process. The variation of floc size and density can cause a change of volumetric concentration under the condition of constant mass concentration. This study investigates how the volumetric concentration is affected by different conditions such as flow velocity, water depth, and sediment suspension. A previously verified, one-dimensional vertical numerical model is utilized here. The flocculation process is also considered by floc in the growth type flocculation model. Idealized conditions are assumed in this study for the numerical experiments. The simulation results show that the volumetric concentration profile of cohesive sediment is different from the Rouse profile. The volumetric concentration decreases near the bed showing the elevated maximum in the cases of both current and oscillatory flow. The density and size of floc show the minimum and the maximum values near the elevation of volumetric concentration maximum, respectively. This study also shows that the flow velocity and the critical shear stress have significant effects on the elevated maximum of volumetric concentration. As mechanisms of the elevated maximum, the strong turbulence intensity and increased mass concentration are considered because they cause the enhanced flocculation process. This study uses numerical experiments. To the best of our knowledge, no laboratory or field experiments on the elevated maximum have been carried out until now. It is of great necessity to conduct well-controlled laboratory experiments in the near future.

Description: Subtropical rivers support a highly diverse array of benthic macroinvertebrates. In this study, by combining historical data and new data, we identified specific changes in the Guanlan River, in South China, from 1981 to 2011, and evaluated the effectiveness of an ecological restoration project under highly polluted conditions. From 1981 to 2011, the water quality in the Guanlan River underwent three major stages. With the deterioration of water quality, there was an overall decrease in the species number of macroinvertebrates in the Guanlan River, an increase in macroinvertebrate density, and a reduction of the biodiversity, and a reduction of functional feeding groups. In 2011, after five years of comprehensive remediation, the Guanlan River was somewhat improved. Macroinvertebrate biodiversity in the middle reach of the Guanlan River, where a key ecological restoration engineering project was implemented, did not differ significantly from other sites. This finding indicates that the effectiveness of ecological restoration measures in highly polluted rivers, particularly at the reach-scale, is very limited and even ineffective.

Description: The Xinjiang Region in Northwest China is known as the “dust center” of the Eurasian mainland. Dust on the leaf surface affects overall plant development. While emphasis was on studying the impacts of industrial dust particles on crop development, the effect of natural dust deposition on the physiological parameters of cotton had not been studied before. The objective of this study was to examine the effects of dust deposits on cotton leaves and to estimate their impact on crop development and yield. For this purpose, an experiment was set up having two treatments and a control. In Treatment 1, cotton leaves were cleaned with water at three-day intervals or after a natural dust fall. In Treatment 2, 100 g·m−2 of dust was applied at 10-day intervals. The control received neither additional dust nor cleaning. In all of the treatments, stomatal conductance, leaf temperature, biomass and yield were measured. The results show a 28% reduction in yield and 30% reduction in stomatal conductance of the dust treatment compared to the control treatment. This indicates blocking of the stomata on the top of the leaf surface. In addition, the canopy temperature of the dust-applied leaves was always higher than the control and treatment.

Description: River flow forecasting is critical for flood forecasting, reservoir operations, and water resources management. However, flow forecasting can be difficult, challenging and time consuming due to the spatial and temporal variability of climatic conditions and watershed characteristics. From a practical point of view, a simple and intuitive approach might be more preferable than a complex modeling approach. In this study, our objective was to develop short-term (i.e., daily) flow forecasting models in the Bow River at the city of Calgary, Alberta, Canada. Here, we evaluated the performance of several regression models, along with a newly proposed “base difference” model, by using antecedent daily river flow values from three gauge stations (i.e., Banff, Seebe, and Calgary). Our analyses revealed that using a multivariable linear regression formulated as a function of upstream gauge stations (i.e., Banff or Seebe) and the station of interest (i.e., Calgary) using antecedent flows demonstrated strong relationships (i.e., having r2 (coefficient of determination) and RMSE (root-mean-square deviation) of approximately 0.93 and 14 m3/s, respectively). As such, we opted to suggest that the use of Banff and Calgary stations in forecasting the flows at Calgary could be considered as it would require a relatively lower number of gauge stations.

Description: Nitrates pollution of waters is a worldwide problem and its remediation is a big challenge from the technical and the scientific point of view. One of the most used and promising cleaning techniques is the biological treatment of wastewaters operated by denitrifying bacteria. In this paper we begin a thorough study of denitrifying performances of the bacterium Azospira sp. OGA 24, recently isolated from the highly polluted Sarno river in the south of Italy. Here, the kinetics of nitrates consumption operated by bacteria in a specifically devised batch bioreactor, in anoxic condition and with acetate as the organic substrate, has been characterized. Experimental data were then used in a simplified model of a real wastewater treatment plant to find that OGA 24 can clean water with efficiency up to 90%. The denitrifying performances of OGA 24 match the requirements of Italian laws and make the bacterium suitable for its employment in treatment plants.

Description: Bioelectrochemical systems (BES) and forward osmosis (FO) are two emerging technologies with great potential for energy-efficient water/wastewater treatment. BES takes advantage of microbial interaction with a solid electron acceptor/donor to accomplish bioenergy recovery from organic compounds, and FO can extract high-quality water driven by an osmotic pressure. The strong synergy between those two technologies may complement each other and collaboratively address water-energy nexus. FO can assist BES with achieving water recovery (for future reuse), enhancing electricity generation, and supplying energy for accomplishing the cathode reactions; while BES may help FO with degrading organic contaminants, providing sustainable draw solute, and stabilizing water flux. This work has reviewed the recent development that focuses on the synergy between BES and FO, analyzed the advantages of each combination, and provided perspectives for future research. The findings encourage further investigation and development for efficient coordination between BES and FO towards an integrated system for wastewater treatment and reuse.

Description: Agricultural irrigation leachate is often the largest source for aquifer recharge in semi-arid groundwater basins, but contamination from fertilizers and other agro-chemicals may degrade the quality of groundwater. Affected communities are frequently economically disadvantaged, and water supply alternatives may be too costly. This study aimed to demonstrate that, when addressing these issues, environmental sustainability and market profitability are not incompatible. We investigated the viability of two low impact crops, alfalfa and vineyards, and new recharge basins as an alternative land use in recharge buffer zones around affected communities using an integrated hydrologic, socio-geographic, and economic analysis. In the southern Central Valley, California, study area, alfalfa and vineyards currently constitute 30% of all buffer zone cropland. Economic analyses of alternative land use scenarios indicate a wide range of revenue outcomes. Sector output gains and potential cost saving through land use conversion and resulting flood control result in gains of at least $2.3 billion, as compared to costs of $0.3 to $0.7 billion for treatment options over a 20 year period. Buffer zones would maintain the economic integrity of the region and concur with prevailing policy options. Thus, managed agricultural recharge buffer zones are a potentially attractive option for communities facing financial constraint and needing to diversify their portfolio of policy and infrastructure approaches to meet drinking water quality objectives.

Description: Partial Least Squares Regression (PLSR) can integrate a great number of variables and overcome collinearity problems, a fact that makes it suitable for intensive agronomical practices such as land application. In the present study a PLSR model was developed to predict important management goals, including biomass production and nutrient recovery (i.e., nitrogen and phosphorus), associated with treatment potential, environmental impacts, and economic benefits. Effluent loading and a considerable number of soil parameters commonly monitored in effluent irrigated lands were considered as potential predictor variables during the model development. All data were derived from a three year field trial including plantations of four different plant species (Acacia cyanophylla, Eucalyptus camaldulensis, Populus nigra, and Arundo donax), irrigated with pre-treated domestic effluent. PLSR method was very effective despite the small sample size and the wide nature of data set (with many highly correlated inputs and several highly correlated responses). Through PLSR method the number of initial predictor variables was reduced and only several variables were remained and included in the final PLSR model. The important input variables maintained were: Effluent loading, electrical conductivity (EC), available phosphorus (Olsen-P), Na+, Ca2+, Mg2+, K2+, SAR, and NO3−-N. Among these variables, effluent loading, EC, and nitrates had the greater contribution to the final PLSR model. PLSR is highly compatible with intensive agronomical practices such as land application, in which a large number of highly collinear and noisy input variables is monitored to assess plant species performance and to detect impacts on the environment.