Recent developments in predictive uncertainty assessment based on the model conditional processor approach

Abstract. The work aims at discussing the role of predictive uncertainty in flood forecasting and flood emergency management, its relevance to improve the decision making process and the techniques to be used for its assessment. Real time flood forecasting requires taking into account predictive uncertainty for a number of reasons. Deterministic hydrological/hydraulic forecasts give useful information about real future events, but their predictions, as usually done in practice, cannot be taken and used as real future occurrences but rather used as pseudo-measurements of future occurrences in order to reduce the uncertainty of decision makers. Predictive Uncertainty (PU) is in fact defined as the probability of occurrence of a future value of a predictand (such as water level, discharge or water volume) conditional upon prior observations and knowledge as well as on all the information we can obtain on that specific future value from model forecasts. When dealing with commensurable quantities, as in the case of floods, PU must be quantified in terms of a probability distribution function which will be used by the emergency managers in their decision process in order to improve the quality and reliability of their decisions. After introducing the concept of PU, the presently available processors are introduced and discussed in terms of their benefits and limitations. In this work the Model Conditional Processor (MCP) has been extended to the possibility of using two joint Truncated Normal Distributions (TNDs), in order to improve adaptation to low and high flows. The paper concludes by showing the results of the application of the MCP on two case studies, the Po river in Italy and the Baron Fork river, OK, USA. In the Po river case the data provided by the Civil Protection of the Emilia Romagna region have been used to implement an operational example, where the predicted variable is the observed water level. In the Baron Fork River example, the data set provided by the NOAA's National Weather Service, within the DMIP 2 Project, allowed two physically based models, the TOPKAPI model and TETIS model, to be calibrated and a data driven model to be implemented using the Artificial Neural Network. The three model forecasts have been combined with the aim of reducing the PU and improving the probabilistic forecast taking advantage of the different capabilities of each model approach

Recent advances in flood forecasting and flood risk assessment

International audienceRecent large floods in Europe have led to increased interest in research and development of flood forecasting systems. Some of these events have been provoked by some of the wettest rainfall periods on record which has led to speculation that such extremes are attributable in some measure to anthropogenic global warming and represent the beginning of a period of higher flood frequency. Whilst current trends in extreme event statistics will be difficult to discern, conclusively, there has been a substantial increase in the frequency of high floods in the 20th century for basins greater than 2x105 km2. There is also increasing that anthropogenic forcing of climate change may lead to an increased probability of extreme precipitation and, hence, of flooding. There is, therefore, major emphasis on the improvement of operational flood forecasting systems in Europe, with significant European Community spending on research and development on prototype forecasting systems and flood risk management projects. This Special Issue synthesises the most relevant scientific and technological results presented at the International Conference on Flood Forecasting in Europe held in Rotterdam from 3-5 March 2003. During that meeting 150 scientists, forecasters and stakeholders from four continents assembled to present their work and current operational best practice and to discuss future directions of scientific and technological efforts in flood prediction and prevention. The papers presented at the conference fall into seven themes, as follows

Stochastic rainfall interpolation and downscaling

No Abstract

Follicular development, plasma Inhibin-A and Estradiol-17-beta concentrations in Buffalo cows during different treatment schedules for MOET programs

Buffalo cows were submitted to three superovulatory treatments. T1 (n = 7): PRID for 10 days (d0-d9) plus decreasing doses of 500 IU FSH/LH (12 h-intervals d7‑d10); T2 (n = 8): PRID for 11 d (d0-d10) plus 2000 IU PMSG at d7; T3 (n = 9): PRID for 11 d plus 2000 IU PMSG at d7 and decreasing doses of 175 IU FSH/LH (12 h-intervals d10‑ d11). Overall plasma inhibin‑A (In-A) concentrations correlated with large follicles (LF, diameter >6mm, R=0.83, P10 mm at d12- 13 (T1=5.0+/-1.4, T2=1.2+/-0.9, T3=8.3+/-2.3). In-A concentrations significantly rised at d11-13 of T1 and T3. In-A seems a good indicator of the follicular development during superovulation in buffalo cows, while E2 is not. Furthermore T3 was followed by better ovarian follicular responses

Venous wall ultrastructure in generalized venomegaly.

The ultrastructure of thè v. colica sinistra in a case of generalized vasomegaìy in man was examined. Elastic material was found in three forms: as a lightly osmiophii amorphous material bordering on myocytes, as a highly osmiophii elastic membrana, and as highly osmiophii slim elastic fibres of different orientation in thè tunica media and adventitia. The slightly osmiophii elastic material is assumed to be newly formed. by pinocytotic activity of thè myocytes. The highly osmiophii elastic material indicatss its impairment. No typical atherosclerotic changes were found in thè examined vein. Based on a comparison with previous findings in thè case of vasomegaìy of thè a. mesenterica inferior, thè authors conclude that thè venomegaly phenomenon is connected with degenerative changes in thè elastic material of thè vessel wall

Dietary integration with oregano (Origanum vulgare L.) essential oil improves growth rate and oxidative status in outdoor, but not indoor, reared pigs

The effects of a diet supplemented with oregano essential oil on performance, oxidative status, pork quality traits and sensorial properties were evaluated. In two studies, 72 pigs in indoor or outdoor conditions were assigned to either a control diet or an identical diet supplemented with 0.2% oregano essential oil. Pigs reared outdoor showed lower live weight, average daily gain and average gain:feed ratio compared to indoor pigs. The oregano supplementation improved the growth performance of the outdoor‐ but not the indoor‐reared animals. The serum oxidative status was influenced by the diet. A higher oxidative stability was observed in the oregano‐supplemented groups. As for the rearing conditions, the data suggest that after an initial adapting period, the free‐range farming systems could be better tolerated by pigs. Meat derived from pigs reared outdoor showed higher pH and a* values. Lightness was influenced by both the diet and the rearing conditions. The control group reared indoor showed shear force values higher than both supplemented groups, while no differences were detected with the control group reared outdoor. In the consumer test performed under blind conditions, the oregano groups achieved higher consistency scores compared with the control. Under informed conditions, the meat derived from the oregano‐supplemented pigs reared outdoor received the highest scores for consistency and overall liking regardless of the rearing system. The same result for the overall liking score was obtained in the expectation test. The data obtained showed that dietary oregano essential oil can be effective in reducing performance losses due to the outdoor‐rearing system, increasing the oxidative status of the animal and oxidative stability of the meat, without modifying the meat quality traits and improving consumer perceptions of the meat quality

Spectrally resolved observations of atmospheric emitted radiance in the H2O rotation band

This paper presents the project Earth Cooling by Water Vapor Radiation, an observational programme, which aims at developing a database of spectrally resolved far infrared observations, in atmospheric dry conditions, in order to validate radiative transfer models and test the quality of water vapor continuum and line parameters. The project provides the very first set of far-infrared spectral downwelling radiance measurements, in dry atmospheric conditions, which are complemented with Raman Lidar-derived temperature and water vapor profiles

Is GRB 050904 at z=6.3 absorbed by dust?

Claim of dust extinction for this GRB has been debated in the past. We suggest that the discrepant results occur primarily because most of previous studies have not simultaneously investigated the X-ray to near-IR spectral energy distribution of this GRB. The difficulty with this burst is that the X-ray afterglow is dominated by strong flares at early times and is poorly monitored at late times. In addition, the Z band photometry, which is the most sensitive to dust extinction, has been found to be affected by strong systematics. In this paper we carefully re-analyze the Swift/XRT afterglow observations of this GRB, using extensive past studies of X-ray flare properties when computing the X-ray afterglow flux level and exploiting the recent reanalysis of the optical (UV rest frame) data of the same GRB. We extract the X-ray to optical/near-IR afterglow SED for the three epochs where the best spectral coverage is available: 0.47, 1.25, and 3.4 days after the trigger. A spectral power-law model has been fitted to the extracted SEDs. We discuss that no spectral breaks or chromatic temporal breaks are expected in the epochs of interest. To fit any UV rest-frame dust absorption, we tested the Small Magellanic Cloud (SMC) extinction curve, the mean extinction curve (MEC) found for a sample of QSO at $z>4$ and its corresponding attenuation curve, as well as a starburst attenuation curve, and the extinction curve consistent with a supernova dust origin (SN-type). The SMC extinction curve and the SN-type one provide good fit to the data at all epochs, with an average amount of dust absorption at $\lambda_{rest} = 3000 \AA$ of $A_{3000} = 0.25\pm 0.07$ mag. These results indicate that the primeval galaxy at $z = 6.3$ hosting this GRB has already enriched its ISM with dust.Comment: 8 pages, 3 figures, accepted for publication in Astronomy and Astrophysics; figure 1 has been degraded, full resolution version at http://dl.dropbox.com/u/1670579/fig01.p

Pressure-dependent EPANET extension

In water distribution systems (WDSs), the available flow at a demand node is dependent on the pressure at that node. When a network is lacking in pressure, not all consumer demands will be met in full. In this context, the assumption that all demands are fully satisfied regardless of the pressure in the system becomes unreasonable and represents the main limitation of the conventional demand driven analysis (DDA) approach to WDS modelling. A realistic depiction of the network performance can only be attained by considering demands to be pressure dependent. This paper presents an extension of the renowned DDA based hydraulic simulator EPANET 2 to incorporate pressure-dependent demands. This extension is termed “EPANET-PDX” (pressure-dependent extension) herein. The utilization of a continuous nodal pressure-flow function coupled with a line search and backtracking procedure greatly enhance the algorithm’s convergence rate and robustness. Simulations of real life networks consisting of multiple sources, pipes, valves and pumps were successfully executed and results are presented herein. Excellent modelling performance was achieved for analysing both normal and pressure deficient conditions of the WDSs. Detailed computational efficiency results of EPANET-PDX with reference to EPANET 2 are included as well