Optimal Operation of the Multireservoir System in the Seine River Basin Using Deterministic and Ensemble Forecasts

International audienceThis article investigates the improvement of the operation of a four-reservoir system in the Seine River basin, France, by use of deterministic and ensemble weather forecasts and real-time control. In the current management, each reservoir is operated independently from the others and following prescribed rule-curves, designed to reduce floods and sustain low flows under the historical hydrological conditions. However, this management system is inefficient when inflows are significantly different from their seasonal average and may become even more inadequate to cope with the predicted increase in extreme events induced by climate change. In this work, a centralized real-time control system is developed to improve reservoirs operation by exploiting numerical weather forecasts that are becoming increasingly available. The proposed management system implements a well-established optimization technique, model predictive control (MPC), and its recently modified version that can incorporate uncertainties, tree-based model predictive control (TB-MPC), to account for deterministic and ensemble forecasts respectively. The management system is assessed by simulation over historical events and compared to the no-forecasts strategy based on rule-curves. Simulation results show that the proposed real-time control system largely outperforms the no-forecasts management strategy, and that explicitly considering forecast uncertainty through ensembles can compensate for the loss in performance due to forecast inaccuracy

Technical Note: The CREDIBLE Uncertainty Estimation (CURE) toolbox: facilitating the communication of epistemic uncertainty

There is a general trend for increasing inclusion of uncertainty estimation in the environmental modelling domain. We present the CREDIBLE Uncertainty Estimation (CURE) Toolbox, an open source MATLABTM toolbox for uncertainty estimation aimed at scientists and practitioners that are not necessarily experts in uncertainty estimation. The toolbox focusses on environmental simulation models and hence employs a range of different Monte Carlo methods for forward and conditioned uncertainty estimation. The methods included span both formal statistical and informal approaches, which are demonstrated using a range of modelling applications set up as workflow scripts. The workflow scripts provide examples of how to utilise toolbox functions for a variety of modelling applications and hence aid the user in defining their own workflow: additional help is provided by extensively commented code. The toolbox implementation aims to increase the uptake of uncertainty estimation methods within a framework designed to be open and explicit, in a way that tries to represent best practice in applying the methods included. Best practice in the evaluation of modelling assumptions and choices, specifically including epistemic uncertainties, is also included by the incorporation of a condition tree that allows users to record assumptions and choices made as an audit trail log.</p

The Clinical Translation Gap in Child Health Exercise Research: A Call for Disruptive Innovation

In children, levels of play, physical activity, and fitness are key indicators of health and disease and closely tied to optimal growth and development. Cardiopulmonary exercise testing (CPET) provides clinicians with biomarkers of disease and effectiveness of therapy, and researchers with novel insights into fundamental biological mechanisms reflecting an integrated physiological response that is hidden when the child is at rest. Yet the growth of clinical trials utilizing CPET in pediatrics remains stunted despite the current emphasis on preventative medicine and the growing recognition that therapies used in children should be clinically tested in children. There exists a translational gap between basic discovery and clinical application in this essential component of child health. To address this gap, the NIH provided funding through the Clinical and Translational Science Award (CTSA) program to convene a panel of experts. This report summarizes our major findings and outlines next steps necessary to enhance child health exercise medicine translational research. We present specific plans to bolster data interoperability, improve child health CPET reference values, stimulate formal training in exercise medicine for child health care professionals, and outline innovative approaches through which exercise medicine can become more accessible and advance therapeutics across the child health spectrum

Technical note: The CREDIBLE Uncertainty Estimation (CURE) toolbox: facilitating the communication of epistemic uncertainty

There is a general trend toward the increasing inclusion of uncertainty estimation in the environmental modelling domain. We present the Consortium on Risk in the Environment: Diagnostics, Integration, Benchmarking, Learning and Elicitation (CREDIBLE) Uncertainty Estimation (CURE) toolbox, an open-source MATLABTM toolbox for uncertainty estimation aimed at scientists and practitioners who are not necessarily experts in uncertainty estimation. The toolbox focusses on environmental simulation models and, hence, employs a range of different Monte Carlo methods for forward and conditioned uncertainty estimation. The methods included span both formal statistical and informal approaches, which are demonstrated using a range of modelling applications set up as workflow scripts. The workflow scripts provide examples of how to utilize toolbox functions for a variety of modelling applications and, hence, aid the user in defining their own workflow; additional help is provided by extensively commented code. The toolbox implementation aims to increase the uptake of uncertainty estimation methods within a framework designed to be open and explicit in a way that tries to represent best practice with respect to applying the methods included. Best practice with respect to the evaluation of modelling assumptions and choices, specifically including epistemic uncertainties, is also included by the incorporation of a condition tree that allows users to record assumptions and choices made as an audit trail log.</p

Dalhousie dyspnea scales: construct and content validity of pictorial scales for measuring dyspnea

BACKGROUND: Because there are no child-friendly, validated, self-report measures of dyspnea or breathlessness, we developed, and provided initial validation, of three, 7-item, pictorial scales depicting three sub-constructs of dyspnea: throat closing, chest tightness, and effort. METHODS: We developed the three scales (Throat closing, Chest tightness, and Effort) using focus groups with 25 children. Subsequently, seventy-nine children (29 children with asthma, 30 children with cystic fibrosis. and 20 children who were healthy) aged 6 to 18 years rated each picture in each series, using a 0–10 scale. In addition, each child placed each picture in each series on a 100-cm long Visual Analogue Scale, with the anchors "not at all" and "a lot". RESULTS: Children aged eight years or older rated the scales in the correct order 75% to 98% correctly, but children less than 8 years of age performed unreliably. The mean distance between each consecutive item in each pictorial scale was equal. CONCLUSION: Preliminary results revealed that children aged 8 to 18 years understood and used these three scales measuring throat closing, chest tightness, and effort appropriately. The scales appear to accurately measure the construct of breathlessness, at least at an interval level. Additional research applying these scales to clinical situations is warranted

Value of long-term streamflow forecasts to reservoir operations for water supply in snow-dominated river catchments

We present a forecast-based adaptive management framework for water supply reservoirs and evaluate the contribution of long-term inflow forecasts to reservoir operations. Our framework is developed for snow-dominated river basins that demonstrate large gaps in forecast skill between seasonal and inter-annual time horizons. We quantify and bound the contribution of seasonal and inter-annual forecast components to optimal, adaptive reservoir operation. The framework uses an Ensemble Streamflow Prediction (ESP) approach to generate retrospective, one-year-long streamflow forecasts based on the Variable Infiltration Capacity (VIC) hydrology model. We determine the optimal sequence of daily release decisions using the Model Predictive Control (MPC) optimization scheme. We then assess the forecast value by comparing system performance based on the ESP forecasts with the performances based on climatology and perfect forecasts. We distinguish among the relative contributions of the seasonal component of the forecast versus the inter-annual component by evaluating system performance based on hybrid forecasts, which are designed to isolate the two contributions. As an illustration, we first apply the forecast-based adaptive management framework to a specific case study, i.e., Oroville Reservoir in California, and we then modify the characteristics of the reservoir and the demand to demonstrate the transferability of the findings to other reservoir systems. Results from numerical experiments show that, on average, the overall ESP value in informing reservoir operation is 35% less than the perfect forecast value and the inter-annual component of the ESP forecast contributes 20–60% of the total forecast value.</p

Semantic mapping of discourse and activity, using Habermas’s theory of communicative action to analyze process

Our primary objective is evaluation of quality of process. This is addressed through semantic mapping of process. We note how this is complementary to the primacy of output results or products. We use goal-oriented discourse as a case study. We draw benefit from how social and political theorist, Jürgen Habermas, uses what was termed “communicative action”. An orientation in Habermas’s work, that we use, is analysis of communication or discourse. For this, we take Twitter social media. In our case study, we map the discourse semantically, using the Correspondence Analysis platform for such latent semantic analysis. This permits qualitative and quantitative analytics. Our case study is a set of eight carefully planned Twitter campaigns relating to environmental issues. The aim of these campaigns was to increase environmental awareness and behaviour. Each campaign was launched by an initiating tweet. Using the data gathered in these Twitter campaigns, we sought to map them, and hence to track the flow of the Twitter discourse. This mapping was achieved through semantic embedding. The semantic distance between an initiating act and the aggregate semantic outcome is used as a measure of process effectiveness

Racemic epinephrine compared to salbutamol in hospitalized young children with bronchiolitis; a randomized controlled clinical trial [ISRCTN46561076]

BACKGROUND: Bronchiolitis is the most common cause of lower respiratory tract illness in infancy, and hospital admission rates appear to be increasing in Canada and the United States. Inhaled beta agonists offer only modest short-term improvement. Trials of racemic epinephrine have shown conflicting results. We sought to determine if administration of racemic epinephrine during hospital stay for bronchiolitis improved respiratory distress, was safe, and shortened length of stay. METHODS: The study was a randomized, double-blind controlled trial of aerosolized racemic epinephrine compared to salbutamol every one to 4 hours in previously well children aged 6 weeks to ≤ 2 years of age hospitalized with bronchiolitis. The primary outcome was symptom improvement as measured by the Respiratory Distress Assessment Instrument (RDAI); secondary outcomes were length of stay in hospital, adverse events, and report of symptoms by structured parental telephone interview one week after discharge. RESULTS: 62 children with a mean age of 6.4 months were enrolled; 80% of children had Respiratory Syncytial Virus (RSV). Racemic epinephrine resulted in significant improvement in wheezing and the total RDAI score on day 2 and over the entire stay (p < 0.05). The mean LOS in the epinephrine arm was 2.6 days (95% CI 2, 3.2) v. 3.4 days in those in the salbutamol group (95% CI 2.6, 4.2) (p > 0.05). Adverse events were not significantly different in the two arms. At one week post-discharge, over half of parents reported that their child still had a respiratory symptom and 40% had less than normal feeding. CONCLUSION: Racemic epinephrine relieves respiratory distress in hospitalized infants with bronchiolitis and is safe but does not abbreviate hospital stay. Morbidity associated with bronchiolitis as identified by parents persists for at least one week after hospital discharge in most infants