Multi-temporal scale analysis of complementarity between hydro and solar power along an alpine transect

Variable renewable energy sources display different space-time variability driving the availability of energy generated from these sources. Complementarity among variable renewable energies in time and space allows reducing the variability of power supply and helps matching the electricity demand curve. This work investigates the temporal structure of complementarity along an alpine transect in North-East Italy, considering a 100% renewable energy mix scenario composed by photovoltaic and run-of-the-river energy. We analyze the dominant scales of variability of variable renewable energy sources and electricity demand. In addition, we introduce a new metric, the wavelet-based complementarity index, to quantify the potential complementarity between two different energy sources. We show that this index varies at different temporal scales and it helps explaining the discrepancy between demand and supply in the study area. Continuous and discrete wavelet analyses are applied to assess the energy balance variability at multiple temporal scales and to identify the optimal mix of renewable energies, respectively. This work describes therefore an effective approach to investigate the temporal-scale dependency of the variance in the energy balance and can be further extended to different and more complex situations.

Quantification of subsurface hydrologic connectivity in four headwater catchments using graph theory

Hillslope-stream connectivity significantly affects streamflow and water quality responses during rainfall and snowmelt events, but is difficult to quantify. One approach to quantify subsurface hillslope-stream connectivity is graph theory, which considers linear connections between groundwater measurement sites. We quantified subsurface connectivity based on surface topography and shallow groundwater data from four small (<14 ha) headwater catchments in the Italian Dolomites and the Swiss pre-Alps, determined the relation between rainfall, antecedent wetness conditions and subsurface connectivity and assessed the sensitivity of the results to changes in the measurement network. Event total stormflow was correlated to maximum subsurface connectivity. Subsurface connectivity increased during rainfall events but maximum connectivity occurred later than peak streamflow, resulting in anti-clockwise hysteretic relations between the two. Subsurface connectivity was positively correlated to rainfall amount. Maximum subsurface connectivity was related to the sum of total rainfall plus antecedent rainfall for the Dolomitic catchments, but these relations were less clear for the pre-alpine catchments. For the pre-alpine catchments, the fractions of time that the groundwater monitoring sites were connected to the stream were significantly correlated to the upslope site characteristics, such as the Topographic Wetness Index. For the Dolomitic catchments, the fractions of time that the monitoring sites were connected to the stream were correlated to the topographic characteristics of the upslope contributing area for the catchment with the small riparian zone, and with the distance to the nearest stream for the catchment with the large riparian zone. The leave-one-out sensitivity analysis showed that small changes in the structure of the groundwater monitoring networks had a limited influence on the results, suggesting that graph-theory approaches can be used to describe subsurface hydrologic connectivity. However, the proposed graph-theory approach should be verified in other catchments with different groundwater monitoring networks.

Basin-scale analysis of the geomorphic effectiveness of flash floods: A study in the northern Apennines (Italy)

Large floods may produce remarkable channel changes, which determine damages and casualties in inhabited areas. However, our knowledge of such processes remains poor, as is our capability to predict them. This study analyses the geomorphic response of the Nure River (northern Italy) and nine tributaries to a high-magnitude flood that occurred in September 2015. The adopted multi-disciplinary approach encompassed: (i) hydrological and hydraulic analysis; (ii) analysis of sediment delivery to the stream network by means of landslides mapping; (iii) assessment of morphological modifications of the channels, including both channel width and bed elevation changes. The spatial distribution of rainfall showed that the largest rainfall amounts occur in the upper portions of the catchment, with cumulative rainfall reaching 300 mm in 12 h, and recurrence intervals exceeding 100-150 years. The unit peak discharge ranged between 5.2 and 25 m³ s^-1 km^-2. Channel widening was the most evident effect. In the tributaries, the ratio between post-flood and pre-flood channel width averaged 3.3, with a maximum approaching 20. Widening was associated with channel aggradation up to 1.5 m and removal of riparian vegetation. New islands formed due to the fragmentation of the former floodplain. In the Nure River, the average width ratio was 1.7, and here widening occurred mainly at the expenses of islands. Bed level dynamics in the Nure were varied, including aggradation, incision, and overall stability. The flood geomorphic effectiveness was more pronounced in the middle-higher portions of the basin. Planimetric and elevation changes were well correlated. Regression analysis of the relationship between widening and morphological/ hydraulic controlling factors indicated that unit stream power and confinement index were the most relevant variables. The study provides useful insights for river management, especially with regard to the proportion of the valley floor subject to erosion and/or deposition during large events.

Runoff generation in mountain catchments: long-term hydrological monitoring in the Rio Vauz Catchment, Italy

Trying to obtain a more detailed understanding of the hydrological functioning of mountain catchments represents an important challenge in the effort of counteracting possible consequences of climate and land use change on water resources availability. Long-term (> 10 years) hydro-meteorological monitoring in small (typically < 10 km2) experimental catchments constitutes a valuable tool to achieve these goal. One of these sites is the Rio Vauz Catchment (1.9 km2), in the Italian Dolomites, that represents an excellent example of long-term snowmelt-dominated catchment in Dolomitic regions. The strong elevation gradient of the Rio Vauz Catchment and the different physiographic properties of its nested subcatchments make this a unique site for investigating fundamental runoff generation mechanisms in mountain headwaters. In this work, we provide a review of physical processes that have been inferred from 12 years of hydrological monitoring in this catchment. We present the available dataset and summarize the main hydrological mechanisms that explain the internal functioning of the Rio Vauz Catchment, primarily focusing on three characterizing hydrological behaviours, namely thresholds, hysteresis and connectivity. The main control on surface and subsurface runoff threshold response is constituted by a combination of soil moisture antecedent conditions, rainfall amount and topography. Changes in hysteresis patterns (clockwise and anti-clockwise loops) between streamflow and soil moisture, water table depth and electrical conductivity were governed by distinct runoff generation processes and rainfall event characteristics. Hillslope-riparian-stream subsurface connectivity was controlled by antecedent wetness conditions and rainfall amount. The composition in environmental tracers (stable isotopes of water and electrical conductivity) in different water sources and the application of tracer-based mixing models helped to distinguish the geographical sources to runoff and to quantify the role of rainfall and snowmelt in streamflow. Finally, we define a perceptual model of runoff generation processes for dry and wet conditions that can be considered representative for many mountain headwater catchments in the world.

Land use change impacts on floods at the catchment scale: Challenges and opportunities for future research

Research gaps in understanding flood changes at the catchment scale caused by changes in forest management, agricultural practices, artificial drainage, and terracing are identified. Potential strategies in addressing these gaps are proposed, such as complex systems approaches to link processes across time scales, long-term experiments on physical-chemical-biological process interactions, and a focus on connectivity and patterns across spatial scales. It is suggested that these strategies will stimulate new research that coherently addresses the issues across hydrology, soil and agricultural sciences, forest engineering, forest ecology, and geomorphology.

Breast fat volume measurement using wide-bore 3 T MRI: comparison of traditional mammographic density evaluation with MRI density measurements using automatic segmentation

AIM

To compare magnetic resonance imaging (MRI)-derived breast density measurements using automatic segmentation algorithms with radiologist estimations using the Breast Imaging Reporting and Data Systems (BI-RADS) density classification.

MATERIALS AND METHODS

Forty women undergoing mammography and dynamic breast MRI as part of their clinical management were recruited. Fat-water separated MRI images derived from a two-point Dixon technique, phase-sensitive reconstruction, and atlas-based segmentation were obtained before and after intravenous contrast medium administration. Breast density was assessed using software from Advanced MR Analytics (AMRA), Linköping, Sweden, with results compared to the widely used four-quartile quantitative BI-RADS scale.

RESULTS

The proportion of glandular tissue in the breast on MRI was derived from the AMRA sequence. The mean unenhanced breast density was 0.31±0.22 (mean±SD; left) and 0.29±0.21 (right). Mean breast density on post-contrast images was 0.32±0.19 (left) and 0.32±0.2 (right). There was "almost perfect" correlation between pre- and post-contrast breast density quantification: Spearman's correlation rho=0.98 (95% confidence intervals [CI]: 0.97-0.99; left) and rho=0.99 (95% CI: 0.98-0.99; right). The 95% limits of agreement were -0.11-0.08 (left) and -0.08-0.03 (right). Interobserver reliability for BI-RADS was "substantial": weighted Kappa k=0.8 (95% CI: 0.74-0.87). The Spearman correlation coefficient between BI-RADS and MRI breast density was rho=0.73 (95% CI: 0.60-0.82; left) and rho=0.75 (95% CI: 0.63-0.83; right) which was also "substantial".

CONCLUSION

The AMRA sequence provides a fully automated, reproducible, objective assessment of fibroglandular breast tissue proportion that correlates well with mammographic assessment of breast density with the added advantage of avoidance of ionising radiation.

Automatic Tuning of Spatially Varying Transfer Functions for Blood Vessel Visualization

Computed Tomography Angiography (CTA) is commonly used in clinical routine for diagnosing vascular diseases. The procedure involves the injection of a contrast agent into the blood stream to increase the contrast between the blood vessels and the surrounding tissue in the image data. CTA is often visualized with Direct Volume Rendering (DVR) where the enhanced image contrast is important for the construction of Transfer Functions (TFs). For increased efficiency, clinical routine heavily relies on preset TFs to simplify the creation of such visualizations for a physician. In practice, however, TF presets often do not yield optimal images due to variations in mixture concentration of contrast agent in the blood stream. In this paper we propose an automatic, optimization-based method that shifts TF presets to account for general deviations and local variations of the intensity of contrast enhanced blood vessels. Some of the advantages of this method are the following. It computationally automates large parts of a process that is currently performed manually. It performs the TF shift locally and can thus optimize larger portions of the image than is possible with manual interaction. The method is based on a well known vesselness descriptor in the definition of the optimization criterion. The performance of the method is illustrated by clinically relevant CT angiography datasets displaying both improved structural overviews of vessel trees and improved adaption to local variations of contrast concentration.

Seasonal characteristics of flood regimes across the Alpine-Carpathian range

The aim of this paper is to analyse the differences in the long-term regimes of extreme precipitation and floods across the Alpine-Carpathian range using seasonality indices and atmospheric circulation patterns to understand the main flood-producing processes. This is supported by cluster analyses to identify areas of similar flood processes, both in terms of precipitation forcing and catchment processes. The results allow to isolate regions of similar flood generation processes including southerly versus westerly circulation patterns, effects of soil moisture seasonality due to evaporation and effects of soil moisture seasonality due to snow melt. In many regions of the Alpine-Carpathian range, there is a distinct shift in flood generating processes with flood magnitude as evidenced by a shift from summer to autumn floods. It is argued that the synoptic approach proposed here is valuable in both flood analysis and flood estimation.

Small baseline volume of left hippocampus is associated with subsequent conversion of MCI into dementia: the Göteborg MCI study

BACKGROUND

Earlier studies have reported that hippocampal atrophy can to some extent predict which patients with mild cognitive impairment (MCI) will subsequently convert to dementia, and that converters have an enhanced rate of hippocampal volume loss.

OBJECTIVE

To further validate the hypothesis that hippocampal atrophy predicts conversion from MCI to dementia, to relate baseline hippocampal volume to different forms of dementia, and to investigate the role of hippocampal side differences and rate of volume loss over time.

PATIENTS

The subjects (N=68) include patients with MCI at baseline and progression to dementia at the two-year follow-up (N=21), stable MCI patients (N=21), and controls (N=26). Among the progressing patients, 13 were diagnosed as having AD.

METHODS

The Göteborg MCI study is a clinically based longitudinal study with biannual clinical assessments. Hippocampal volumetry was performed manually on the MRI investigations at baseline and at the two-year follow-up.

RESULTS

Hippocampal volumetry could predict conversion to dementia in both the AD and the non-AD subgroup of converters. Left hippocampal volume in particular discriminated between converting and stable MCI. Cut off points for individual discrimination were shown to be potentially useful. The converting MCI group had a significantly higher rate of hippocampal volume loss as compared to the stable MCI group.

CONCLUSIONS

In MCI patients, hippocampal volumetry at baseline gives prognostic information about possible development of AD and non-AD dementia. Contrary to earlier studies, we found that left hippocampal volume has the best predictive power. Reliable predictions appear to be possible in many individual cases.

Detection of mild emphysema by computed tomography density measurements

PURPOSE

To assess the ability of a conventional density mask method to detect mild emphysema by high-resolution computed tomography (HRCT); to analyze factors influencing quantification of mild emphysema; and to validate a new algorithm for detection of mild emphysema.

MATERIAL AND METHODS

Fifty-five healthy male smokers and 34 never-smokers, 61-62 years of age, were examined. Emphysema was evaluated visually, by the conventional density mask method, and by a new algorithm compensating for the effects of gravity and artifacts due to motion and the reconstruction algorithm. Effects of the reconstruction algorithm, slice thickness, and various threshold levels on the outcome of the density mask area were evaluated.

RESULTS

Forty-nine percent of the smokers had mild emphysema. The density mask area was higher the thinner the slice irrespective of the reconstruction algorithm and threshold level. The sharp algorithm resulted in increased density mask area. The new reconstruction algorithm could discriminate between smokers with and those without mild emphysema, whereas the density mask method could not. The diagnostic ability of the new algorithm was dependent on lung level. At about 90% specificity, sensitivity was 65-100% in the apical levels, but low in the rest of the lung.

CONCLUSION

The conventional density mask method is inadequate for detecting mild emphysema, while the new algorithm improves the diagnostic ability but is nevertheless still imperfect.

Fibre-optic array for curvature assessment: application in otitis diagnosis

A contact-free sensor consisting of two parallel optical-fibre arrays was designed to assess surface shapes of diffusely scattering media. By sequentially illuminating objects using one fibre array and detecting the diffusely back-scattered photons by the other, a source-detector intensity matrix was formed, where the matrix element (i, j) was the intensity at detector j when light source i was excited. Experimental data from convex and concave polyacetal plastic surfaces were recorded. A mathematical model was used for simulating source-detector intensity matrices for the surfaces analysed in the experiments. Experimental results from the system were compared with the theoretically expected results provided by the mathematical model. The shape and relative amplitude showed similar behaviour in the experiments and simulations. A convex/concave discriminator index D, representing the detected intensity difference between two source-detector separations, was defined. The relative dynamic range of D, defined as the difference between the maximum and the minimum divided by the mean of the index, was 1.37 for convex surfaces and 0.68 for concave surfaces, at a measuring distance of 4.5 mm. The index D was positive for convex surfaces and negative for concave surfaces, which showed that the system could distinguish between convex and concave surfaces, an important result for the diagnosis of otitis media.

Detection of neural activity in functional MRI using canonical correlation analysis

A novel method for detecting neural activity in functional magnetic resonance imaging (fMRI) data is introduced. It is based on canonical correlation analysis (CCA), which is a multivariate extension of the univariate correlation analysis widely used in fMRI. To detect homogeneous regions of activity, the method combines a subspace modeling of the hemodynamic response and the use of spatial relationships. The spatial correlation that undoubtedly exists in fMR images is completely ignored when univariate methods such as as t-tests, F-tests, and ordinary correlation analysis are used. Such methods are for this reason very sensitive to noise, leading to difficulties in detecting activation and significant contributions of false activations. In addition, the proposed CCA method also makes it possible to detect activated brain regions based not only on thresholding a correlation coefficient, but also on physiological parameters such as temporal shape and delay of the hemodynamic response. Excellent performance on real fMRI data is demonstrated. Magn Reson Med 45:323-330, 2001.