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Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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237 KiB

Open AccessEditor’s ChoiceReview

Evaluating Stream Restoration Projects: What Do We Learn from Monitoring?

by Zan Rubin, G. Mathias Kondolf and Blanca Rios-Touma

Water 2017, 9(3), 174; https://doi.org/10.3390/w9030174 - 28 Feb 2017

Cited by 70 | Viewed by 11839

Abstract

Two decades since calls for stream restoration projects to be scientifically assessed, most projects are still unevaluated, and conducted evaluations yield ambiguous results. Even after these decades of investigation, do we know how to define and measure success? We systematically reviewed 26 studies of stream restoration projects that used macroinvertebrate indicators to assess the success of habitat heterogeneity restoration projects. All 26 studies were previously included in two meta-analyses that sought to assess whether restoration programs were succeeding. By contrast, our review focuses on the evaluations themselves, and asks what exactly we are measuring and learning from these evaluations. All 26 studies used taxonomic diversity, richness, or abundance of invertebrates as biological measures of success, but none presented explicit arguments why those metrics were relevant measures of success for the restoration projects. Although changes in biodiversity may reflect overall ecological condition at the regional or global scale, in the context of reach-scale habitat restoration, more abundance and diversity may not necessarily be better. While all 26 studies sought to evaluate the biotic response to habitat heterogeneity enhancement projects, about half of the studies (46%) explicitly measured habitat alteration, and 31% used visual estimates of grain size or subjectively judged ‘habitat quality’ from protocols ill-suited for the purpose. Although the goal of all 26 projects was to increase habitat heterogeneity, 31% of the studies either sampled only riffles or did not specify the habitats sampled. One-third of the studies (35%) used reference ecosystems to define target conditions. After 20 years of stream restoration evaluation, more work remains for the restoration community to identify appropriate measures of success and to coordinate monitoring so that evaluations are at a scale capable of detecting ecosystem change. Full article

(This article belongs to the Special Issue Stream Ecosystems and Restoration: Linking Bioassessments to Improved Planning and Design Strategies)

1706 KiB

Open AccessEditor’s ChoiceArticle

Detection of Viable Bacteria during Sludge Ozonation by the Combination of ATP Assay with PMA-Miseq Sequencing

by Shaonan Tian, Zhe Tian, Hong Yang, Min Yang and Yu Zhang

Water 2017, 9(3), 166; https://doi.org/10.3390/w9030166 - 26 Feb 2017

Cited by 56 | Viewed by 6314

Abstract

Using sludge obtained from municipal sewage treatment plants, the response of viable bacterial populations during the sludge ozonation process was investigated by a combination of adenosine triphosphate (ATP) assay and propidium monoazide (PMA)-Miseq sequencing. The ATP assay was first optimized for application on sludge samples by adjusting the sludge solid contents and reaction time. PMA-modified polymerase chain reaction (PCR) was also optimized by choosing the suitable final PMA concentration. The quantity and composition of viable bacterial populations during sludge ozonation were further elucidated using the optimized ATP and PMA-modified PCR methods. The results indicated that after the sludge was exposed to ozone (O₃) at 135 mg·O₃/g total suspended solids (TSS), the viable biomass displayed a substantial decrease, with a reduction rate reaching 70.89%. The composition of viable bacterial communities showed a faster succession, showing that an ozone dosage of 114 mg·O₃/g TSS is enough to significantly change the viable bacterial population structure. Floc-forming genera, such as Zoogloea, Ferruginibacter, Thauera and Turneriella, are sensitive to ozonation, while the relative abundances of some functional bacterial genera, including SM1A02, Nitrospira and Candidatus Accumulibacter, remained constant or increased in the viable bacterial population during sludge ozonation, indicating that they are more resistant to ozonation. Full article

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1837 KiB

Open AccessEditor’s ChoiceArticle

Machine Learning Algorithms for the Forecasting of Wastewater Quality Indicators

by Francesco Granata, Stefano Papirio, Giovanni Esposito, Rudy Gargano and Giovanni De Marinis

Water 2017, 9(2), 105; https://doi.org/10.3390/w9020105 - 9 Feb 2017

Cited by 198 | Viewed by 14014

Abstract

Stormwater runoff is often contaminated by human activities. Stormwater discharge into water bodies significantly contributes to environmental pollution. The choice of suitable treatment technologies is dependent on the pollutant concentrations. Wastewater quality indicators such as biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total suspended solids (TSS), and total dissolved solids (TDS) give a measure of the main pollutants. The aim of this study is to provide an indirect methodology for the estimation of the main wastewater quality indicators, based on some characteristics of the drainage basin. The catchment is seen as a black box: the physical processes of accumulation, washing, and transport of pollutants are not mathematically described. Two models deriving from studies on artificial intelligence have been used in this research: Support Vector Regression (SVR) and Regression Trees (RT). Both the models showed robustness, reliability, and high generalization capability. However, with reference to coefficient of determination R2 and root‐mean square error, Support Vector Regression showed a better performance than Regression Tree in predicting TSS, TDS, and COD. As regards BOD5, the two models showed a comparable performance. Therefore, the considered machine learning algorithms may be useful for providing an estimation of the values to be considered for the sizing of the treatment units in absence of direct measures. Full article

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3645 KiB

Open AccessEditor’s ChoiceArticle

Energy Recovery in Existing Water Networks: Towards Greater Sustainability

by Modesto Pérez-Sánchez, Francisco Javier Sánchez-Romero, Helena M. Ramos and P. Amparo López-Jiménez

Water 2017, 9(2), 97; https://doi.org/10.3390/w9020097 - 8 Feb 2017

Cited by 113 | Viewed by 10869

Abstract

Analyses of possible synergies between energy recovery and water management are essential for achieving sustainable improvements in the performance of irrigation water networks. Improving the energy efficiency of water systems by hydraulic energy recovery is becoming an inevitable trend for energy conservation, emissions reduction, and the increase of profit margins as well as for environmental requirements. This paper presents the state of the art of hydraulic energy generation in drinking and irrigation water networks through an extensive review and by analyzing the types of machinery installed, economic and environmental implications of large and small hydropower systems, and how hydropower can be applied in water distribution networks (drinking and irrigation) where energy recovery is not the main objective. Several proposed solutions of energy recovery by using hydraulic machines increase the added value of irrigation water networks, which is an open field that needs to be explored in the near future. Full article

(This article belongs to the Special Issue Water Systems towards New Future Challenges)

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1672 KiB

Open AccessEditor’s ChoiceArticle

Water Savings of Crop Redistribution in the United States

by Kyle Frankel Davis, Antonio Seveso, Maria Cristina Rulli and Paolo D’Odorico

Water 2017, 9(2), 83; https://doi.org/10.3390/w9020083 - 30 Jan 2017

Cited by 43 | Viewed by 8737

Abstract

Demographic growth, changes in diet, and reliance on first-generation biofuels are increasing the human demand for agricultural products, thereby enhancing the human pressure on global freshwater resources. Recent research on the food-water nexus has highlighted how some major agricultural regions of the world lack the water resources required to sustain current growth trends in crop production. To meet the increasing need for agricultural commodities with limited water resources, the water use efficiency of the agricultural sector must be improved. In this regard, recent work indicates that the often overlooked strategy of changing the crop distribution within presently cultivated areas offers promise. Here we investigate the extent to which water in the United States could be saved while improving yields simply by replacing the existing crops with more suitable ones. We propose crop replacement criteria that achieve this goal while preserving crop diversity, economic value, nitrogen fixation, and food protein production. We find that in the United States, these criteria would greatly improve calorie (+46%) and protein (+34%) production and economic value (+208%), with 5% water savings with respect to the present crop distribution. Interestingly, greater water savings could be achieved in water-stressed agricultural regions of the US such as California (56% water savings), and other western states. Full article

(This article belongs to the Special Issue Water Footprint Assessment)

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6922 KiB

Open AccessEditor’s ChoiceArticle

Comparison of Multi-Criteria Decision Support Methods for Integrated Rehabilitation Prioritization

by Franz Tscheikner-Gratl, Patrick Egger, Wolfgang Rauch and Manfred Kleidorfer

Water 2017, 9(2), 68; https://doi.org/10.3390/w9020068 - 24 Jan 2017

Cited by 133 | Viewed by 12931

Abstract

The decisions taken in rehabilitation planning for the urban water networks will have a long lasting impact on the functionality and quality of future services provided by urban infrastructure. These decisions can be assisted by different approaches ranging from linear depreciation for estimating the economic value of the network over using a deterioration model to assess the probability of failure or the technical service life to sophisticated multi-criteria decision support systems. Subsequently, the aim of this paper is to compare five available multi-criteria decision-making (MCDM) methods (ELECTRE, AHP, WSM, TOPSIS, and PROMETHEE) for the application in an integrated rehabilitation management scheme for a real world case study and analyze them with respect to their suitability to be used in integrated asset management of water systems. The results of the different methods are not equal. This occurs because the chosen score scales, weights and the resulting distributions of the scores within the criteria do not have the same impact on all the methods. Independently of the method used, the decision maker must be familiar with its strengths but also weaknesses. Therefore, in some cases, it would be rational to use one of the simplest methods. However, to check for consistency and increase the reliability of the results, the application of several methods is encouraged. Full article

(This article belongs to the Special Issue Synergies in Urban Water Infrastructure Modeling)

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