Real-time forecasts of flood hazard and impact: some UK experiences

Major UK floods over the last decade have motivated significant technological and scientific advances in operational flood forecasting and warning. New joint forecasting centres between the national hydrological and meteorological operating agencies have been formed that issue a daily, national Flood Guidance Statement (FGS) to the emergency response community. The FGS is based on a Flood Risk Matrix approach that is a function of potential impact severity and likelihood. It has driven an increased demand for robust, accurate and timely forecast and alert information on fluvial and surface water flooding along with impact assessments. The Grid-to-Grid (G2G) distributed hydrological model has been employed across Britain at a 1km resolution to support the FGS. Novel methods for linking dynamic gridded estimates of river flow and surface runoff with more detailed offline flood risk maps have been developed to obtain real-time probabilistic forecasts of potential impacts, leading to operational trials. Examples of the national-scale G2G application are provided along with case studies of forecast flood impact from (i) an operational Surface Water Flooding (SWF) trial during the Glasgow 2014 Commonwealth Games, (ii) SWF developments under the Natural Hazards Partnership over England & Wales, and (iii) fluvial applications in Scotland

Forecasting snowmelt flooding over Britain using the Grid-to-Grid model: a review and assessment of methods

In many regions of high annual snowfall, snowmelt modelling can prove to be a vital component of operational flood forecasting and warning systems. Although Britain as a whole does not experience prolonged periods of lying snow, with the exception of the Scottish Highlands, the inclusion of snowmelt modelling can still have a significant impact on the skill of flood forecasts. Countrywide operational flood forecasts over Britain are produced using the national Grid-to-Grid (G2G) distributed hydrological model. For Scotland, snowmelt is included in these forecasts through a G2G snow hydrology module involving temperature-based snowfall/rainfall partitioning and functions for temperature-excess snowmelt, snowpack storage and drainage. Over England and Wales, the contribution of snowmelt is included by pre-processing the precipitation prior to input into G2G. This removes snowfall diagnosed from weather model outputs and adds snowmelt from an energy budget land surface scheme to form an effective liquid water gridded input to G2G. To review the operational options for including snowmelt modelling in G2G over Britain, a project was commissioned by the Environment Agency through the Flood Forecasting Centre (FFC) for England and Wales and in partnership with the Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW). Results obtained from this snowmelt review project will be reported on here. The operational methods used by the FFC and SEPA are compared on past snowmelt floods, alongside new alternative methods of treating snowmelt. Both case study and longer-term analyses are considered, covering periods selected from the winters 2009-2010, 2012-2013, 2013-2014 and 2014-2015. Over Scotland, both of the snowmelt methods used operationally by FFC and SEPA provided a clear improvement to the river flow simulations. Over England and Wales, fewer and less significant snowfall events occurred, leading to less distinction in the results between the methods. It is noted that, for all methods considered,large uncertainties remain in flood forecasts influenced by snowmelt. Understanding and quantifying these uncertainties should lead to more informed flood forecasts and associated guidance information

Deriving snow water equivalent using cosmic-ray neutron sensors from the COSMOS-UK network for modelling snowmelt floods

The COSMOS-UK sensor network has the potential to provide new insights into extreme snowfall and snowmelt events in the UK and to improve the modelling of snowmelt floods. The network consist of approximately 50 measurement sites, each equipped with a Cosmic-Ray Neutron Sensor (CRNS). A number of these sites additionally include a “SnowFox” sensor for measuring snow water equivalent (SWE) and an ultrasonic snow depth sensor. Although the CRNS is currently used to produce estimates of soil moisture, it is also sensitive to water held as a snowpack. Moreover, the large (hundreds of metres) footprint of the CRNS potentially allows representative measurements of SWE even for inhomogeneous snowpacks. However, to date, there has been little attempt to produce snow products using the COSMOS-UK network, and soil moisture estimates during snowfall events are simply removed from the record. Here, a method is developed for using the COSMOS-UK network to derive snow products for the UK, where shallow, ephemeral snowpacks are the norm. The challenges posed by noise from the random nature of cosmic ray events, and the problem of separating the snow signal from moisture within the soil, are discussed. A comparison is made of SWE derived from the COSMOS-UK network and modelled using the snow hydrology component of the Grid-to-Grid (G2G) distributed hydrological model, and the effect on simulated river flows discussed

Investigating potential future changes in surface water flooding hazard and impact

Surface water flooding (SWF) is a recurrent hazard that affects lives and livelihoods. Climate change is projected to change the frequency of extreme rainfall events that can lead to SWF. Increasingly, data from Regional Climate Models (RCMs) are being used to investigate the potential water‐related impacts of climate change; such assessments often focus on broad‐scale fluvial flooding and the use of coarse resolution (>12 km) RCMs. However, high‐resolution (<4 km) convection‐permitting RCMs are now becoming available that allow impact assessments of more localised SWF to be made. At the same time, there has been an increasing demand for more robust and timely real‐time forecast and alert information on SWF. In the UK, a real‐time SWF Hazard Impact Model framework has been developed. The system uses 1‐km gridded surface runoff estimates from a hydrological model to simulate the SWF hazard. These are linked to detailed inundation model outputs through an Impact Library to assess impacts on property, people, transport, and infrastructure for four severity levels. Here, a set of high‐resolution (1.5 km and 12 km) RCM data has been used as input to a grid‐based hydrological model over southern Britain to simulate Current (1996–2009) and Future (~2100s; RCP8.5) surface runoff. Counts of threshold‐exceedance for surface runoff and precipitation (at 1‐, 3‐ and 6‐hr durations) are analysed. Results show that the percentage increases in surface runoff extremes, are less than those of precipitation extremes. The higher‐resolution RCM simulates the largest percentage increases, which occur in winter, and the winter exceedance counts are greater than summer exceedance counts. For property impacts, the largest percentage increases are also in winter; however, it is the 12‐km RCM output that leads to the largest percentage increase in impacts. The added‐value of high‐resolution climate model data for hydrological modelling is from capturing the more intense convective storms in surface runoff estimates

Parity-Violating Excitation of the \Delta(1232): Hadron Structure and New Physics

We consider prospects for studying the parity-violating (PV) electroweak excitation of the \Delta(1232) resonance with polarized electron scattering. Given present knowledge of Standard Model parameters, such PV experiments could allow a determination of the N -> \Delta electroweak helicity amplitudes. We discuss the experimental feasibility and theoretical interpretability of such a determination as well as the prospective implications for hadron structure theory. We also analyze the extent to which a PV N -> \Delta measurement could constrain various extensions of the Standard Model.Comment: 43 pages, RevTex, 8 PS figures, uses epsf.sty, rotate.sty, version to appear in Nucl. Phys. A, main points emphasized, some typos correcte

Distributed hydrological modelling for forecasting water discharges from the land area draining to the Great Barrier Reef coastline

The physical-conceptual distributed hydrological model Grid-to-Grid, or G2G, is applied across the 426, 000 km2 land area draining to the Great Barrier Reef (GBR) coastline of Queensland, Australia. Of this area, 76, 600 km2 is ungauged, this being the land between the most downstream gauging locations and the coastline. G2G provides gridded hourly river flows across the model domain, of use for both flood and water availability forecasting in Queensland, as well as hourly coastal discharges required by marine models of the Reef environment employed for conservation purposes. G2G is underpinned by spatial datasets on terrain, land-cover and soil properties. The best sources for these datasets have been identified and developed to support generic application of G2G across Australia. These include the Australian Digital Elevation Model and Digital Atlas of Australian Soils and serve to shape the hydrological response to rainfall patterns in time and space. Raingauge observations along with the AustralianWater Availability Project (AWAP) gridded rainfall are used to generate 1 km gridded historical rainfall. The ACCESS-R numerical weather prediction model is used to generate 1 km gridded forecast rainfall over a lead-time of three days. The model’s area-wide formulation allows for the production of real-time flow forecasts everywhere on a 1km grid across the model domain, including those areas which are ungauged. G2G is calibrated over the GBR land area, and the modelling capability assessed through comparison with gauged river flow records at 276 locations over a nine year period. A novel method, employing data assimilation of the furthest downstream gauged river flows, is used to obtain improved coastal discharge estimates required by the marine models. The G2G historical simulations and nowcasts are linked to statistical water quality models to generate sediment, nitrogen and phosphorus loads for use in biogeochemistry models, and are being used in generating GBR Annual Report Cards by the Australian Government. Currently, the G2G modelling system to generate long-term historical simulations, nowcasts and forecasts is not operational but work is in progress to make the system operational in the near future. The work is a collaboration between the Bureau of Meteorology Australia and the Centre for Ecology & Hydrology in the UK, and forms part of the eReefs Programme in support of the Reef 2050 Plan

Prevalence, predictors, and outcomes of poststroke falls in acute hospital setting

Abstract—Falls are a serious medical complication following stroke. The objectives of this study were to (1) confirm the prevalence of falls among patients with stroke during acute hospitalization, (2) identify factors associated with falls during the acute stay, and (3) examine whether in-hospital falls were associated with loss of function after stroke (new dependence at discharge). We completed a secondary analysis of data from a retrospective cohort study of patients with ischemic stroke who were hospitalized at one of four hospitals. We used logistic regression to identify factors associated with inpatient falls and examine the association between falls and loss of function. Among 1,269 patients with stroke, 65 (5%) fell during the acute hospitalization period. We found two characteristics independently associated with falls: greater stroke severity (National Institutes of Health Stroke Scale [NIHSS] 8, adjusted odds ratio [OR] = 3.63, 95% confidence interval [CI]: 1.46–9.00) and history of anxiety (adjusted OR = 4.90, 95% CI: 1.70–13.90). Falls were independently associated with a loss of function (adjusted OR = 9.85, 95% CI: 1.22–79.75) even after adjusting for age, stroke severity, gait abnormalities, and past stroke. Stroke severity (NIHSS 8) may be clinically useful during the acute inpatient setting in identifying those at greatest risk of falling. Given the association between falls and poor patient outcomes, rehabilitation interventions should be implemented to prevent falls poststroke