An interdisciplinary modelling framework for selecting adaptation measures at the river basin scale in a global change scenario

Shaping global change adaptation strategy in water resource systems requires an interdisciplinary approach to deal with the multiple dimensions of the problem. The modelling framework presented integrates climate, economic, agronomic and hydrological scenarios to design a programme of adaptation measures at the river basin scale. Future demand scenarios; combined with a down-scaled climate scenario, provide the basis to estimate the demand and water resources in 2030. A least-cost river basin optimisation model is then applied to select adaptation measures ensuring that environmental and supply management goals are achieved. In the Orb river basin (France), the least-cost portfolio selected suggests mixing demand and supply side measures to adapt to global change. Trade-offs among the cost of the programme of measures, the deficit in agricultural water supply and the level of environmental flows are investigated. The challenges to implement such interdisciplinary approaches in the definition of adaptation strategies are finally discussed. (C) 2015 Elsevier Ltd. All rights reserved.The study has been partially supported by ONEMA, by the Scarce Project (Consolider-Ingenio 2010 CSD2009-00065) and IMPADAPT project (CGL2013-48424-C2-1-R) of the Spanish ministry MINECO (Ministerio de Economia y Competitividad) with European FEDER funds. Corentin Girard is supported by a grant from the University Lecturer Training Program (FPU12/03803) of the Ministry of Education, Culture and Sports of Spain. We also acknowledge the CERFACS for the climate scenarios provided from their SCRATCH 2010 dataset (March 2012 release - http://www.cerfacs.fr/similar to page/work/scratch/). We are very grateful to S. Chazot (BRLi), E. Vier and F. Aigoui (GINGERGROUP) and L. Rippert and its team from the SMVOL for their advice during the research and for the data provided. We thank as well the anonymous reviewers, and the Editor-in-Chief of Environmental Modelling and Software, Anthony Jakeman, for their support in the improvement of the manuscript and their encouraging comments.Girard, CDP.; Rinaudo, J.; Pulido-Velazquez, M.; Caballero, Y. (2015). An interdisciplinary modelling framework for selecting adaptation measures at the river basin scale in a global change scenario. Environmental Modelling and Software. 69:42-54. https://doi.org/10.1016/j.envsoft.2015.02.023S42546

Development of clustering and classification strategies for the determination of geographical origin of honey by using atomic and molecular spectrometry

Thesis (Doctoral)--İzmir Institute of Technology, Chemistry, İzmir, 2011Includes bibliographical references (leaves: 81-84)Text in English; Abstract: Turkish and Englishxiii, 84 leavesHoney is a natural, nutritious and healthy food produced by honeybees from the nectar of plants. The classification of honey based on geographical origin is of great interest since the quality of honey depends on its chemical composition and geographical origin. In this study, it is aimed to develop classification models using elemental and molecular composition of honey samples via atomic and molecular spectrometry. For this purpose, honey samples from different regions of Turkey were collected from producers and they were scanned with Fourier Transform infrared spectrometer equipped with attenuated total reflectance (FTIR-ATR) accessory, and fluorescence spectrophotometer (synchronous fluorescence mode and 3D excitation emission mode). Afterwards, any clustering of the samples based on their regions was investigated using principal component analysis (PCA) and hierarchical cluster analysis (HCA) and soft independent modeling of class analogies (SIMCA). Finally, inductively coupled plasma mass spectrometry was applied to determine the metal concentrations (Mg, Al, Mn, Fe, Co, Ni, Cu, Zn, Sr, Ba) in honey samples and then the same classification methods were performed to compare the results. In conclusion, molecular spectrometry gave better classification results based on geographical origin compared to the results obtained with atomic spectrometry. Molecular spectrometry is more advantageous for the classification of honey samples in the case of saving time, saving chemicals and ease of usage

Magnetic Stimulation on the Growth of the Microalga Nannochloropsis oculata

Fossil fuels, our principal sources of energy supply, are non-renewable and research is needed on alternatives that are renewable and potentially more environmentally friendly. Microalgae have been investigated as a future feedstock alternative to petroleum but the technology is still expensive and improvements are needed. Reduction in costs might be achieved by increasing algal biomass and lipid productivity. The lipids can be used to produce biofuels such as biodiesel and biojet fuel. The marine microalga Nannochloropsis oculata grows well and can accumulate high lipid content. In this study, the effects of static magnetic field stimulation (SMF) of 0 (control), 5, 10 and 15 mT were investigated in terms of growth and biochemical composition of this microalga. In comparison to the control, the cells grown at 10 mT had the highest increase in biomass productivity (45%) and lipid productivity (57%) in addition to increase in other co-product yields. Some of the co-products could potentially be used for high value-added applications, thus helping to offset costs even further. The use of magnetic field stimulation on microalgae is a promising technique to enhance growth and productivity, and Nannochloropsis oculata was shown in this study to be a suitable microalgae species to be considered for biodiesel applications

Water Resources Decision Making Under Uncertainty

Uncertainty is in part about variability in relation to the physical characteristics of water resources systems. But uncertainty is also about ambiguity (Simonovic, 2009). Both variability and ambiguity are associated with a lack of clarity because of the behaviour of all system components, a lack of data, a lack of detail, a lack of structure to consider water resources management problems, working and framing assumptions being used to consider the problems, known and unknown sources of bias, and ignorance about how much effort it is worth expending to clarify the management situation. Climate change, addressed in this research project (CFCAS, 2008), is another important source of uncertainty that contributes to the variability in the input variables for water resources management. This report presents a set of examples that illustrate (a) probabilistic and (b) fuzzy set approaches for solving various water resources management problems. The main goal of this report is to demonstrate how information provided to water resources decision makers can be improved by using the tools that incorporate risk and uncertainty. The uncertainty associated with water resources decision making problems is quantified using probabilistic and fuzzy set approaches. A set of selected examples are presented to illustrate the application of probabilistic and fuzzy simulation, optimization, and multi-objective analysis to water resources design, planning and operations. Selected examples include dike design, sewer pipe design, optimal operations of a single purpose reservoir, and planning of a multi-purpose reservoir system. Demonstrated probabilistic and fuzzy tools can be easily adapted to many other water resources decision making problems.https://ir.lib.uwo.ca/wrrr/1035/thumbnail.jp

Implementation of a National Reference Laboratory for Buruli Ulcer Disease in Togo

Background: In a previous study PCR analysis of clinical samples from suspected cases of Buruli ulcer disease (BUD) from Togo and external quality assurance (EQA) for local microscopy were conducted at an external reference laboratory in Germany. The relatively poor performance of local microscopy as well as effort and time associated with shipment of PCR samples necessitated the implementation of stringent EQA measures and availability of local laboratory capacity. This study describes the approach to implementation of a national BUD reference laboratory in Togo. Methodology: Large scale outreach activities accompanied by regular training programs for health care professionals were conducted in the regions "Maritime'' and "Central,'' standard operating procedures defined all processes in participating laboratories (regional, national and external reference laboratories) as well as the interaction between laboratories and partners in the field. Microscopy was conducted at regional level and slides were subjected to EQA at national and external reference laboratories. For PCR analysis, sample pairs were collected and subjected to a dry-reagent-based IS2404-PCR (DRB-PCR) at national level and standard IS2404 PCR followed by IS2404 qPCR analysis of negative samples at the external reference laboratory. Principal Findings: The inter-laboratory concordance rates for microscopy ranged from 89% to 94%; overall, microscopy confirmed 50% of all suspected BUD cases. The inter-laboratory concordance rate for PCR was 96% with an overall PCR case confirmation rate of 78%. Compared to a previous study, the rate of BUD patients with non-ulcerative lesions increased from 37% to 50%, the mean duration of disease before clinical diagnosis decreased significantly from 182.6 to 82.1 days among patients with ulcerative lesions, and the percentage of category III lesions decreased from 30.3% to 19.2%. Conclusions: High inter-laboratory concordance rates as well as case confirmation rates of 50% (microscopy), 71% (PCR at national level), and 78% (including qPCR confirmation at external reference laboratory) suggest high standards of BUD diagnostics. The increase of non-ulcerative lesions, as well as the decrease in diagnostic delay and category III lesions, prove the effect of comprehensive EQA and training measures involving also procedures outside the laboratory

Integrating top-down and bottom-up approaches to design global change adaptation at the river basin scale

The high uncertainty associated with the effect of global change on water resource systems calls for a better combination of conventional top-down and bottom-up approaches, in order to design robust adaptation plans at the local scale. The methodological framework presented in this article introduces bottom-up meets top-down integrated approach to support the selection of adaptation measures at the river basin level by comprehensively integrating the goals of economic efficiency, social acceptability, environmental sustainability and adaptation robustness. The top-down approach relies on the use of a chain of models to assess the impact of global change on water resources and its adaptive management over a range of climate projections. Future demand scenarios and locally prioritised adaptation measures are identified following a bottom-up approach through a participatory process with the relevant stakeholders and experts. The optimal combinations of adaptation measures are then selected using a hydro-economic model at basin scale for each climate projection. The resulting adaptation portfolios are, finally, climate checked to define a robust least-regret programme of measures based on trade-offs between adaptation costs and the reliability of supply for agricultural demands. This innovative approach has been applied to a Mediterranean basin, the Orb river basin (France). Mid-term climate projections, downscaled from 9 General Climate Models, are used to assess the uncertainty associated with climate projections. Demand evolution scenarios are developed to project agricultural and urban water demands on the 2030 time horizon. The results derived from the integration of the bottom-up and top-down approaches illustrate the sensitivity of the adaptation strategies to the climate projections, and provide an assessment of the trade-offs between the performance of the water resource system and the cost of the adaptation plan to inform local decision-making. The article contributes new methodological elements for the development of an integrated framework for decision-making under climate change uncertainty, advocating an interdisciplinary approach that bridges the gap between bottom-up and top-down approaches.The study has been financially supported by BRGM-ONEMA joint project on Hydro-economic modelling and by the IMPADAPT project (CGL2013-48424-C2-1-R) from the Spanish ministry MINECO (Ministerio de Economia y Competitividad) with European FEDER funds. Corentin Girard is supported by a grant from the University Lecturer Training Program (FPU12/03803) of the Ministry of Education, Culture and Sports of Spain. We also acknowledge the CERFACS for the climate scenarios provided from the SCRATCH 2010 dataset (March 2012 release - http://www.cerfacs.fr/similar to page/work/scratch/). We thank as well the anonymous reviewers and the Editors of Global Environmental Change, for their useful and encouraging comments during the review process.Girard, CDP.; Pulido-Velazquez, M.; Rinaudo, J.; Page Oliva, C.; Caballero, I. (2015). Integrating top-down and bottom-up approaches to design global change adaptation at the river basin scale. Global Environmental Change. 34:132-146. https://doi.org/10.1016/j.gloenvcha.2015.07.002S1321463

Response of Estuarine Fish Biomass to Restoration in the Penobscot River, Maine

Diadromous fish require both freshwater and marine habitat to complete their life cycle. Dams restrict the movement between these habitats and as a result, many populations are historically low across their range. The Penobscot River is the second largest river in Maine and once had large populations of diadromous fish and it has been the focus of mainstem dam removals, dam passage improvements, and stocking with the goal of restoring those populations. Since 2012, NOAA Fisheries has conducted surveys of the Penobscot Estuary using mobile, multi-frequency echosounders (SIMRAD EK60 split-beam 38 and 120 kHz) combined with mid-water trawl surveys to construct a time series of fish distribution to assess this large-scale restoration. Target strength (TS; dB re m2), the log10 of the backscattering cross section (σbs; m2), is an important variable in fisheries acoustics because it is used to compute biological metrics such as biomass and fish density. TS is difficult to characterize due to its stochastic properties from variability in fish physiology, orientation, behavior, depth, and size. When an assemblage consists of multiple species or multiple size classes, assigning TS to the component species or size classes is difficult due to the inability to distinguish individual components in the composite distributions. We addressed these challenges by a unique combination of techniques to characterize TS in the Penobscot River Estuary, Maine. From trawl data, we determined the estuarine species assemblage was dominated by Clupeids and Osmerids. We used single target detection and echo tracking algorithms to isolate TS values from individual fish. Next, we applied an expectation–maximization algorithm to identify components of the mixed normal TS distribution based on fish total length (TL; cm) data from trawl surveys. Finally, we used ordinary least squares regression to estimate the parameters of TS = α log10 (TL) + β. Our final parameters, α = 31.0 (SE 0.84) and β = -79.5 (SE 0.90), were similar to published studies from these species. However, our slope and intercept were higher than studies from freshwater and lower than from marine systems. These results suggest that acoustic surveys in estuarine systems with mixed species assemblages and large salinity ranges may need to develop site specific relationships between TS and fish length. The combination of these methods is an example of a novel technique to derive reproducible TS estimates in mixed pelagic fish assemblages. We used system-specific parameters to compute biomass from acoustic survey data. We assessed seasonal estimates of biomass from 2012 to 2017 a period spanning pre-restoration (2012-2014) and post-restoration (2015-2017). Biomass varied with season and year and was generally greater in summer and in post-restoration years. Biomass in pre-restoration years ranged from 9,000 to 114,000 kg per survey and 11 of 45 (23%) surveys had biomass greater than 50,000 kg. Compared to post-restoration years ranged from 23,000 to 316,000 kg per survey and 34 of 43 (76%) surveys had biomass greater than 50,000 kg. Changes in biomass were observed with changes in fish length and density where higher density resulted in higher biomass. This analysis demonstrates the utility of hydroacoustics in monitoring large-system restoration by describing multiple metrics in a complex ecosystem. The changes observed by increased density and biomass are indications that river restoration is changing the ecology of the estuary