108 research outputs found

    Definition of efficient scarcity-based water pricing policies through stochastic programming

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    [EN] Finding ways to improve the efficiency in water usage is one of the most important challenges in integrated water resources management. One of the most promising solutions is the use of scarcity-based pricing policies. This contribution presents a procedure to design efficient pricing policies based in the opportunity cost of water at the basin scale. Time series of the marginal value of water are obtained using a stochastic hydro-economic model. Those series are then post-processed to define step pricing policies, which depend on the state of the system at each time step. The case study of the Mijares River basin system (Spain) is used to illustrate the method. The results show that the application of scarcitybased pricing policies increases the economic efficiency of water use in the basin, allocating water to the highest-value uses and generating an incentive for water conservation during the scarcity periods. 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    Identifying key water resource vulnerabilities in data‐scarce transboundary river basins

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    This paper presents a two‐step framework to identify key water resource vulnerabilities in transboundary river basins where data availability on both hydrological fluxes and the operation of man‐made facilities is either limited or nonexistent. In a first step, it combines two state‐of‐the‐art modeling tools to overcome data limitations and build a model that provides a lower bound on risks estimated in that basin. Land data assimilation (process‐based hydrological modeling taking remote‐sensed products as inputs) is needed to evaluate hydrological fluxes, that is, streamflow data and consumptive use in irrigated agriculture—a lower‐end estimate of demand. Hydroeconomic modeling provides cooperative water allocation policies that reflect the best‐case management of storage capacity under hydrological uncertainty at a monthly time step for competing uses—hydropower, irrigation. In a second step, the framework uses additional scenarios to proceed with the in‐depth analysis of the vulnerabilities identified despite the use of what is by definition a best‐case model. We implement this approach to the Tigris‐Euphrates river basin, a politically unstable region where water scarcity has been hypothesized to serve as a trigger for the Syrian revolution and ensuing war. Results suggest that even under the framework's best‐case assumptions, the Euphrates part of the basin is close to a threshold where it becomes reliant on transfers of saline water from other parts of the basin to ensure irrigation demands are met. This Tigris‐Euphrates river basin application demonstrates how the proposed framework quantifies vulnerabilities that have been hitherto discussed in a mostly qualitative, speculative way

    A mutual reference shape based on information theory

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    International audienceIn this paper, we propose to consider the estimation of a refer-ence shape from a set of different segmentation results using both active contours and information theory. The reference shape is defined as the minimum of a criterion that benefits from both the mutual information and the joint entropy of the input segmentations and called a mutual shape. This energy criterion is here justified using similarities between informa-tion theory quantities and area measures, and presented in a continuous variational framework. This framework brings out some interesting evaluation measures such as the speci-ficity and sensitivity. In order to solve this shape optimization problem, shape derivatives are computed for each term of the criterion and interpreted as an evolution equation of an active contour. Some synthetical examples allow us to cast the light on the difference between our mutual shape and an average shape. Our framework has been considered for the estimation of a mutual shape for the evaluation of cardiac segmentation methods in MRI

    Integrated modelling of cost-effective siting and operation of flow-control infrastructure for river ecosystem conservation

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    Wetland and floodplain ecosystems along many regulated rivers are highly stressed, primarily due to a lack of environmental flows of appropriate magnitude, frequency, duration, and timing to support ecological functions. In the absence of increased environmental flows, the ecological health of river ecosystems can be enhanced by the operation of existing and new flow-control infrastructure (weirs and regulators) to return more natural environmental flow regimes to specific areas. However, determining the optimal investment and operation strategies over time is a complex task due to several factors including the multiple environmental values attached to wetlands, spatial and temporal heterogeneity and dependencies, nonlinearity, and time-dependent decisions. This makes for a very large number of decision variables over a long planning horizon. The focus of this paper is the development of a nonlinear integer programming model that accommodates these complexities. The mathematical objective aims to return the natural flow regime of key components of river ecosystems in terms of flood timing, flood duration, and interflood period. We applied a 2-stage recursive heuristic using tabu search to solve the model and tested it on the entire South Australian River Murray floodplain. We conclude that modern meta-heuristics can be used to solve the very complex nonlinear problems with spatial and temporal dependencies typical of environmental flow allocation in regulated river ecosystems. The model has been used to inform the investment in, and operation of, flow-control infrastructure in the South Australian River Murray.<br /

    Le partage de la ressource en eau sur la Durance en 2050 : vers une Ă©volution du mode de gestion des grands ouvrages duranciens ?

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    CongrÚs SHF: Water Tensions in Europe and in the Mediterranean: water crisis by 2050?, Paris, FRA, 08-/10/2015 - 09/10/2015International audienceUne vision prospective de la gestion de l'eau du bassin de la Durance et des territoires alimentés par ses eaux à l'horizon 2050 a été élaborée, appuyée par une chaine de modÚles incluant des représentations du climat, de la ressource naturelle, des demandes en eau et du fonctionnement des grands ouvrages hydrauliques (Serre-Ponçon, Castillon et Sainte-Croix), sous contraintes de respect des débits réservés, de cotes touristiques dans les retenues et de restitution d'eau stockée pour des usages en aval. Cet ensemble, validé en temps présent, a été alimenté par des projections climatiques et paramétré pour intégrer les évolutions du territoire décrites par des scénarios de développement socio-économique avec une hypothÚse de conservation des rÚgles de gestion actuelles. Les résultats suggÚrent à l'horizon 2050 : une hausse de la température moyenne de l'air impactant l'hydrologie de montagne ; une évolution incertaine des précipitations ; une réduction des stocks de neige et une fonte avancée dans l'année qui induisent une réduction des débits au printemps ; une diminution de la ressource en eau en période estivale ; une diminution de la demande globale en eau à l'échelle du territoire, cette demande étant fortement conditionnée par les scénarios territoriaux élaborés ici ; la satisfaction des demandes en eau en aval des ouvrages considérées comme prioritaires, au détriment de la production d'énergie en hiver (flexibilité moindre en période de pointe) et du maintien de cotes touristiques en été ;une diminution de la production d'énergie due notamment à la réduction des apports en amont des ouvrages hydroélectriques

    Characterization of primary human hepatocytes, HepG2 cells, and HepaRG cells at the mRNA level and CYP activity in response to inducers and their predictivity for the detection of human hepatotoxins

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    In the pharmaceutical industry, improving the early detection of drug-induced hepatotoxicity is essential as it is one of the most important reasons for attrition of candidate drugs during the later stages of drug development. The first objective of this study was to better characterize different cellular models (i.e., HepG2, HepaRG cells, and fresh primary human hepatocytes) at the gene expression level and analyze their metabolic cytochrome P450 capabilities. The cellular models were exposed to three different CYP450 inducers; beta-naphthoflavone (BNF), phenobarbital (PB), and rifampicin (RIF). HepG2 cells responded very weakly to the different inducers at the gene expression level, and this translated generally into low CYP450 activities in the induced cells compared with the control cells. On the contrary, HepaRG cells and the three human donors were inducible after exposure to BNF, PB, and RIF according to gene expression responses and CYP450 activities. Consequently, HepaRG cells could be used in screening as a substitute and/or in complement to primary hepatocytes for CYP induction studies. The second objective was to investigate the predictivity of the different cellular models to detect hepatotoxins (16 hepatotoxic and 5 nonhepatotoxic compounds). Specificity was 100% with the different cellular models tested. Cryopreserved human hepatocytes gave the highest sensitivity, ranging from 31% to 44% (depending on the donor), followed by lower sensitivity (13%) for HepaRG and HepG2 cells (6.3%). Overall, none of the models under study gave desirable sensitivities (80–100%). Consequently, a high metabolic capacity and CYP inducibility in cell lines does not necessarily correlate with a high sensitivity for the detection of hepatotoxic drugs. Further investigations are necessary to compare different cellular models and determine those that are best suited for the detection of hepatotoxic compounds

    On the visual detection of non-natural records in streamflow time series: challenges and impacts

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    Large datasets of long-term streamflow measurements are widely used to infer and model hydrological processes. However, streamflow measurements may suffer from what users can consider anomalies, i.e. non-natural records that may be erroneous streamflow values or anthropogenic influences that can lead to misinterpretation of actual hydrological processes. Since identifying anomalies is time consuming for humans, no study has investigated their proportion, temporal distribution, and influence on hydrological indicators over large datasets. This study summarizes the results of a large visual inspection campaign of 674 streamflow time series in France made by 43 evaluators, who were asked to identify anomalies falling under five categories, namely, linear interpolation, drops, noise, point anomalies, and other. We examined the evaluators' individual behaviour in terms of severity and agreement with other evaluators, as well as the temporal distributions of the anomalies and their influence on commonly used hydrological indicators. We found that inter-evaluator agreement was surprisingly low, with an average of 12 % of overlapping periods reported as anomalies. These anomalies were mostly identified as linear interpolation and noise, and they were more frequently reported during the low-flow periods in summer. The impact of cleaning data from the identified anomaly values was higher on low-flow indicators than on high-flow indicators, with change rates lower than 5 % most of the time. We conclude that the identification of anomalies in streamflow time series is highly dependent on the aims and skills of each evaluator, which raises questions about the best practices to adopt for data cleaning.</p

    Climate Change, Coral Reef Ecosystems, and Management Options for Marine Protected Areas

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    Marine protected areas (MPAs) provide place-based management of marine ecosystems through various degrees and types of protective actions. Habitats such as coral reefs are especially susceptible to degradation resulting from climate change, as evidenced by mass bleaching events over the past two decades. Marine ecosystems are being altered by direct effects of climate change including ocean warming, ocean acidification, rising sea level, changing circulation patterns, increasing severity of storms, and changing freshwater influxes. As impacts of climate change strengthen they may exacerbate effects of existing stressors and require new or modified management approaches; MPA networks are generally accepted as an improvement over individual MPAs to address multiple threats to the marine environment. While MPA networks are considered a potentially effective management approach for conserving marine biodiversity, they should be established in conjunction with other management strategies, such as fisheries regulations and reductions of nutrients and other forms of land-based pollution. Information about interactions between climate change and more “traditional” stressors is limited. MPA managers are faced with high levels of uncertainty about likely outcomes of management actions because climate change impacts have strong interactions with existing stressors, such as land-based sources of pollution, overfishing and destructive fishing practices, invasive species, and diseases. Management options include ameliorating existing stressors, protecting potentially resilient areas, developing networks of MPAs, and integrating climate change into MPA planning, management, and evaluation
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