Comparing Scaling Approaches to Estimate Unimpaired Streamflow Timeseries and Seasonal Flow Metrics at Ungauged Streams

River ecosystems are controlled in part by natural variation in the flow regime and streamflow alterations that impair these natural variations often have negative impacts for aquatic species. Flow metrics describing attributes of the natural flow regime can inform environmental water management goals to maintain and restore river ecosystems by mirroring critical aspects of the natural flow regime. However, unimpaired daily streamflow data needed to calculate these flow metrics is not always readily available. Statistical scaling approaches present an opportunity to estimate unimpaired flow metrics at ungauged locations to better address environmental water management objectives. This study evaluates a suite of scaling approaches for their ability to estimate ecologically significant daily unimpaired flow metrics applied across the State of California. Results demonstrate the utility of stratification by hydrologic and water-year-type to improve statistical scaling methods and indicate that different scaling approaches are better suited to estimate certain flow metrics. Aggregated dimensionless reference hydrographs accounted for spatial and inter-annual variability better than a single index site for improved representation across large regions. This is the first known example of combining hydrologic classifications and stream class stratified reference hydrographs to refine scaling streamflow relationships and capture natural streamflow magnitude and timing patterns across a large heterogeneous region. Results are intended to inform selection of appropriate streamflow scaling approaches for a given study region based on the specific flow metrics of interest, stream classes present, and reference gauge density and distribution. Better prediction of unimpaired daily flow metrics will lead to more accurate streamflow regime characterization and better flow management decisions

Flow Turbulence And Information Quality

A crucial aspect of managing the corporate information resource is the ability to assess and maintain information quality.  This paper proposes criteria for defining and measuring information quality based on established parameters of information flow.  We develop a conceptual model linking information flow metrics and information qualities.  The basic premise of the model is that changes in flow metrics affect the usefulness criteria of information, which in turn impact information quality.  The usefulness criteria of information are based on established accounting standards.  This mapping of flow metrics to information quality is a necessary and critical step towards the development of a robust instrument for quality assessment.  The implications of the proposed model for managing information flows resulting from business processes are discussed

A multi‐scale study of the dominant catchment characteristics impacting low‐flow metrics

Low flows can impact water use and instream ecology. Therefore, reliable predictions of low-flow metrics are crucial. In this study, we assess which catchment characteristics (climate, topography, geology and landcover) can explain the spatial variability of low-flow metrics at two different scales: the regional scale and the small headwater catchment scale. For the regional-scale analysis, we calculated the mean 7-day annual minimum flow (qmin), the mean of the flow that is exceeded 95% of the year (q95), and the master recession constant (C) for 280 independent gauging stations across the Swiss Plateau and the Swiss Alps for the 2000–2018 period. We assessed the relation between 44 catchment characteristics and the three low-flow metrics based on correlation analysis and a random forest model. Low-flow magnitudes across the Swiss Plateau were positively correlated with the fraction of the area covered by sandstone bedrock or alluvium, and with the area that has a slope between 10° and 30°. Across the Swiss Alps, low-flow magnitudes were positively correlated with the fraction of area with slopes between 30° and 60°, and the area with glacial deposits and debris cover. There was good agreement between observations and predictions by the random forest regression model with the top 11 catchment characteristics for both regions: for 80% of the Swiss Plateau catchments and 60% of the Swiss Alpine catchments, we could predict the three low-flow metrics within an error of 30%. The residuals of the regression model, however, varied across short distances, suggesting that local catchment characteristics affect the variability of low-flow metrics. For the local-scale headwater catchments, we conducted 1-day snapshot field campaigns in 16 catchments during low-flow periods in 2015 and 2016. The measurements in these sub-catchments also showed that areas with sandstone bedrock and a good storage-to-river connectivity had above average low-flow magnitudes. Including knowledge on local catchment characteristics may help to improve regional low-flow predictions, however, not all local catchment characteristics were useful descriptors at larger scales

Integer linear programming formulations for treewidth

In this paper we consider an ILP-based approach to tackle the problem of determining a treewidth of the graph. We give an overview of existing attempts and develop further LP-based techniques for the problem. We present two different ILP formulations for the treewidth. To obtain the first one we merge the chordalization-based ILP by Koster and Bodlaender and flow metrics approach by Bornstein and Vempala. The second brand-new ILP is based on the structural properties of the tree-decomposition. It has a nice application of the local branching techniques by Fischetti and Lodi.mathematical applications;

Changes in precipitation and river flow in northeast Turkey: associations with the North Atlantic Oscillation

This paper explores the relationships between the North Atlantic Oscillation (NAO) index and precipitation and river flow over northeast Turkey. Precipitation totals and maximum, mean and minimum river flow are analysed at the seasonal scale for 12 and 10 stations, respectively. Pearson’s and Mann-Kendall correlation tests are applied to assess relationships between the NAO index and precipitation and river flow metrics, and to detect trends in time-series. Autumn precipitation totals display significant increasing trends, especially for coastal stations, while inland stations show significant increasing trends for spring precipitation. Minimum and maximum river flow decreases significantly for spring and summer. This tendency implies varying conditions towards a drier regime. Seasonal precipitation patterns show a negative association with the NAO for December–January–February (DJF), March–April–May (MAM) and September–October–November (SON) for some stations. Positive associations between the NAO and winter-extended winter (December–March) river flows are detected for some stations in northeast Turkey

Insight into High-quality Aerodynamic Design Spaces through Multi-objective Optimization

An approach to support the computational aerodynamic design process is presented and demonstrated through the application of a novel multi-objective variant of the Tabu Search optimization algorithm for continuous problems to the aerodynamic design optimization of turbomachinery blades. The aim is to improve the performance of a specific stage and ultimately of the whole engine. The integrated system developed for this purpose is described. This combines the optimizer with an existing geometry parameterization scheme and a well- established CFD package. The system’s performance is illustrated through case studies – one two-dimensional, one three-dimensional – in which flow characteristics important to the overall performance of turbomachinery blades are optimized. By showing the designer the trade-off surfaces between the competing objectives, this approach provides considerable insight into the design space under consideration and presents the designer with a range of different Pareto-optimal designs for further consideration. Special emphasis is given to the dimensionality in objective function space of the optimization problem, which seeks designs that perform well for a range of flow performance metrics. The resulting compressor blades achieve their high performance by exploiting complicated physical mechanisms successfully identified through the design process. The system can readily be run on parallel computers, substantially reducing wall-clock run times – a significant benefit when tackling computationally demanding design problems. Overall optimal performance is offered by compromise designs on the Pareto trade-off surface revealed through a true multi-objective design optimization test case. Bearing in mind the continuing rapid advances in computing power and the benefits discussed, this approach brings the adoption of such techniques in real-world engineering design practice a ste

Stratification of a population of intracranial aneurysms using blood flow metrics.

Indices of the intra-aneurysm hemodynamic environment have been proposed as potentially indicative of their longitudinal outcome. To be useful, the indices need to be used to stratify large study populations and tested against known outcomes. The first objective was to compile the diverse hemodynamic indices reported in the literature. Furthermore, as morphology is often the only patient-specific information available in large population studies, the second objective was to assess how the ranking of aneurysms in a population is affected by the use of steady flow simulation as an approximation to pulsatile flow simulation, even though the former is clearly non-physiological. Sixteen indices of aneurysmal hemodynamics reported in the literature were compiled and refined where needed. It was noted that, in the literature, these global indices of flow were always time-averaged over the cardiac cycle. Steady and pulsatile flow simulations were performed on a population of 198 patient-specific and 30 idealised aneurysm models. All proposed hemodynamic indices were estimated and compared between the two simulations. It was found that steady and pulsatile flow simulations had a strong linear dependence (r ≥ 0.99 for 14 indices; r ≥ 0.97 for 2 others) and rank the aneurysms in an almost identical fashion (ρ ≥ 0.99 for 14 indices; ρ ≥ 0.96 for other 2). When geometry is the only measured piece of information available, stratification of aneurysms based on hemodynamic indices reduces to being a physically grounded substitute for stratification of aneurysms based on morphology. Under such circumstances, steady flow simulations may be just as effective as pulsatile flow simulation for estimating most key indices currently reported in the literature

Using a Combination of Measurement Tools to Extract Metrics from Open Source Projects

Software measurement can play a major role in ensuring the quality and reliability of software products. The measurement activities require appropriate tools to collect relevant metric data. Currently, there are several such tools available for software measurement. The main objective of this paper is to provide some guidelines in using a combination of multiple measurement tools especially for products built using object-oriented techniques and languages. In this paper, we highlight three tools for collecting metric data, in our case from several Java-based open source projects. Our research is currently based on the work of Card and Glass, who argue that design complexity measures (data complexity and structural complexity) are indicators/predictors of procedural/cyclomatic complexity (decision counts) and errors (discovered from system tests). Their work was centered on structured design and our work is with object-oriented designs and the metrics we use parallel those of Card and Glass, being, Henry and Kafura's Information Flow Metrics, McCabe's Cyclomatic Complexity, and Chidamber and Kemerer Object-oriented Metrics

Dimensioning the relationship between availability and data center energy flow metrics

The advancement of technology and the growing number of applications available to network users have increased the demand for services hosted in cloud environments. In 2020, more than 4 billion of people access these services through the Internet, a value 7% higher in comparison to the same period in 2019. To support the demand for such services, an environment that provides such conditions for applications available whenever needed has grown in importance. These environments are generally available from large data centers, which consume large amounts of electricity to provide such demand service capacity. In this context, this work proposes an integrated and dynamic strategy that demonstrates the impact of the availability on the energyconsumption of the devices that compose the data center system architecture. In order to accomplish this, colored Petri net models were proposed for quantifying the cost, environmental impact and availability of the electric energy infrastructure ofdata centers. The models presented in this work are supported by the developed prototype. Two case studies illustrate the applicability of the proposed models and strategy. Significant results were obtained, showing an increase close to 100% in the system availability, with practically the same operational cost and environmental impact