Improving the applicability of radar rainfall estimates for urban pluvial flood modelling and forecasting

This work explores the possibility of improving the applicability of radar rainfall estimates (whose accuracy is generally insufficient) to the verification and operation of urban storm-water drainage models by employing a number of local gauge-based radar rainfall adjustment techniques. The adjustment techniques tested in this work include a simple mean-field bias (MFB) adjustment, as well as a more complex Bayesian radar-raingauge data merging method which aims at better preserving the spatial structure of rainfall fields. In addition, a novel technique (namely, local singularity analysis) is introduced and shown to improve the Bayesian method by better capturing and reproducing storm patterns and peaks. Two urban catchments were used as case studies in this work: the Cranbrook catchment (9 km2) in North-East London, and the Portobello catchment (53 km2) in the East of Edinburgh. In the former, the potential benefits of gauge-based adjusted radar rainfall estimates in an operational context were analysed, whereas in the latter the potential benefits of adjusted estimates for model verification purposes were explored. Different rainfall inputs, including raingauge, original radar and the aforementioned merged estimates were fed into the urban drainage models of the two catchments. The hydraulic outputs were compared against available flow and depth records. On the whole, the tested adjustment techniques proved to improve the applicability of radar rainfall estimates to urban hydrological applications, with the Bayesian-based methods, in particular the singularity sensitive one, providing more realistic and accurate rainfall fields which result in better reproduction of the urban drainage system’s dynamics. Further testing is still necessary in order to better assess the benefits of these adjustment methods, identify their shortcomings and improve them accordingly

Searching for Very High Energy Emission from Pulsars Using the High Altitude Water Cherenkov (HAWC) Observatory

There are currently over 160 known gamma-ray pulsars. While most of them are detected only from space, at least two are now seen also from the ground. MAGIC and VERITAS have measured the gamma ray pulsed emission of the Crab pulsar up to hundreds of GeV and more recently MAGIC has reported emission at $\sim2$ TeV. Furthermore, in the Southern Hemisphere, H.E.S.S. has detected the Vela pulsar above 30 GeV. In addition, non-pulsed TeV emission coincident with pulsars has been detected by many groups, including the Milagro Collaboration. These GeV-TeV observations open the possibility of searching for very-high-energy (VHE, > 100GeV) pulsations from gamma-rays pulsars in the HAWC field of view.Comment: Presented at the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. See arXiv:1508.03327 for all HAWC contribution

Quark mass hierarchy in 3-3-1 models

We study the mass spectrum of the quark sector in an special type I-like model with gauge symmetry $SU(3)_c \otimes SU(3)_L \otimes U(1)_X$. By considering couplings with scalar triplets at large ($\sim TeV$) and small ($\sim GeV$) scales, we obtain specific zero-texture mass matrices for the quarks which predict three massless quarks ($u,d,s$) and three massive quarks ($c,b,t$) at the electroweak scale ($\sim$ GeV). Taking into account mixing couplings with three heavy quarks at large scales predicted by the model, the three massless quarks obtain masses at small order that depends on the inverse of the large scale. Thus, masses of the form $m_u \lesssim m_d < m_s \sim MeV$ and $m_{c,b,t} \sim GeV$ can be obtained naturally from the gauge structure of the model

On the use of semi-distributed and fully-distributed urban stormwater models

Urban stormwater models comprise four main components: rainfall, rainfall-runoff, overland flow and sewer flow modules. They can be considered semi-distributed (SD) or fully distributed (FD) according to the rainfall-runoff module definition. SD models are based on sub-catchments units through which rainfall is applied to the model and at which runoff volumes are estimated. In FD models, the runoff volumes are estimated and applied directly on every element of a twodimensional (2D) model of the surface. This poster presents a comparison of SD and FD models based on two case studies: Zona Central catchment at Coimbra, Portugal, and Cranbrook catchment at London, UK. SD and FD modelling results are compared against water depth and flow records in sewers, and photographic records of a flood event. In general, FD models are theoretically more realistic and physically-based, but the results of this study suggest that the implementation of these models requires higher resolution (more detailed) elevation, land use and sewer network data than is normally used in the implementation of SD models. Failing to use higher resolution data for the implementation of FD models could result in poor-performing models. In cases when high resolution data are not available, the use of SD models could be a better choice

Surface water flood warnings in England: overview, Assessment and recommendations based on survey responses and workshops

Following extensive surface water flooding (SWF) in England in summer 2007, progress has been made in improving the management and prediction of this type of flooding. A rainfall threshold-based extreme rainfall alert (ERA) service was launched in 2009 and superseded in 2011 by the surface water flood risk assessment (SWFRA). Through survey responses from local authorities (LAs) and the outcome of workshops with a range of flood professionals, this paper examines the understanding, benefits, limitations and ways to improve the current SWF warning service. The current SWFRA alerts are perceived as useful by district and county LAs, although their understanding of them is limited. The majority of LAs take action upon receipt of SWFRA alerts, and their reactiveness to alerts appears to have increased over the years and as SWFRA superseded ERA. This is a positive development towards increased resilience to SWF. The main drawback of the current service is its broad spatial resolution. Alternatives for providing localised SWF forecast and warnings were analysed, and a two-tier national-local approach, with pre-simulated scenario-based local SWF forecasting and warning systems, was deemed most appropriate by flood professionals given current monetary, human and technological resources

Interactions and magnetic moments near vacancies and resonant impurities in graphene

The effect of electronic interactions in graphene with vacancies or resonant scatterers is investigated. We apply dynamical mean-field theory in combination with quantum Monte Carlo simulations, which allow us to treat non-perturbatively quantum fluctuations beyond Hartree-Fock approximations. The interactions narrow the width of the resonance and induce a Curie magnetic susceptibility, signaling the formation of local moments. The absence of saturation of the susceptibility at low temperatures suggests that the coupling between the local moment and the conduction electrons is ferromagnetic

Stochastic evaluation of sewer inlet capacity on urban pluvial flooding

In this paper we present an innovative methodology to stochastically assess the impact of sewer inlet conditions on urban pluvial flooding. The results showed that sewer inlet capacity can have a large impact on the occurrence of urban pluvial flooding. The methodology is a useful tool for dealing with uncertainties in sewer inlet operational conditions and contribute to comprehensive assessment of urban pluvial risk assessment

Mode of action of the hemin-controlled inhibitor of protein synthesis

Despite the finding that the hemin-controlled translational inhibitor in reticulocyte lysates is a cyclic AMP-independent protein kinase that phosphorylates the small subunit of the initiation factor eIF-2, the mechanism of inhibition of translation remained unexplained. Whereas treatment of hemin-containing lysates with inhibitor in the presence of ATP inhibited translation, the same treatment of highly purified eIF-2 did not affect its ability to form a ternary complex with initiator Met-tRNA and GTP or a 40S initiation complex. We have isolated from ribosomal salt washes a protein (eIF-2 stimulating protein) that enhances the capacity of unphosphorylated eIF-2 to form ternary or 40S initiation complexes but has no effect on the phosphorylated factor. At low concentrations, eIF-2 is virtually inactive without this stimulating protein. Therefore, the translational inhibitor acts by converting eIF-2 to a form that is not stimulated by the stimulating protein

Stochastic urban pluvial flood hazard maps based upon a spatial-temporal rainfall generator

It is a common practice to assign the return period of a given storm event to the urban pluvial flood event that such storm generates. However, this approach may be inappropriate as rainfall events with the same return period can produce different urban pluvial flooding events, i.e., with different associated flood extent, water levels and return periods. This depends on the characteristics of the rainfall events, such as spatial variability, and on other characteristics of the sewer system and the catchment. To address this, the paper presents an innovative contribution to produce stochastic urban pluvial flood hazard maps. A stochastic rainfall generator for urban-scale applications was employed to generate an ensemble of spatially—and temporally—variable design storms with similar return period. These were used as input to the urban drainage model of a pilot urban catchment (~9 km2) located in London, UK. Stochastic flood hazard maps were generated through a frequency analysis of the flooding generated by the various storm events. The stochastic flood hazard maps obtained show that rainfall spatial-temporal variability is an important factor in the estimation of flood likelihood in urban areas. Moreover, as compared to the flood hazard maps obtained by using a single spatially-uniform storm event, the stochastic maps generated in this study provide a more comprehensive assessment of flood hazard which enables better informed flood risk management decisions