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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.

Increasingly, data from Regional Climate Models (RCMs) are being used to drive hydrological models in order to investigate the potential water-related impacts of climate change, particularly on floods and droughts. Traditionally these climate change assessments have focussed on fluvial flooding, commensurate with coarse resolution (>12km) RCMs. However, high-resolution (1.5km), convection-permitting RCMs are now becoming available and allow impact assessments of Surface Water Flooding (SWF) to be considered. At the same time there has been an increasing demand for more robust and timely real-time forecast and alert information for SWF. In the UK, within the Natural Hazards Partnership (NHP, http://www.naturalhazardspartnership.org.uk/) a real-time Hazard Impact Model (HIM) framework has been developed that includes SWF as one of the hazards chosen for real-time pre-operational trials. The SWF HIM system uses 1km gridded surface runoff estimates from the Grid-to-Grid (G2G) hydrological model to estimate the SWF hazard and links this to detailed inundation model outputs to assess impacts on property, people, transport and infrastructure using a pre-computed Impact Library. Here, a set of Met Office Hadley Centre high resolution (1.5 and 12km) RCM runs have been used to drive the G2G for southern Britain. Results investigating the potential future changes in SWF hazard and property impacts will be presented, including the assessment of the added-value of high-resolution climate model data for hydrological modelling. This research is part of the Hydro-JULES Programme funded by the Natural Environment Research Council.

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.

Operational rainfall and flood forecasting systems across the world are increasingly using ensemble approaches. In Britain such systems are operated by the Flood Forecasting Centre (FFC) over England & Wales and by the Scottish Flood Forecasting Service (SFFS) over Scotland producing ensemble gridded hydrological forecasts out to 5 or 6 days. In order to maximise the practical day-to-day use of these systems for flood guidance and warning, duty hydrometeorologists require a sound understanding of both the meteorological and hydrological ensemble forecast skill. To help meet this requirement, a common framework for the verification of river flow and precipitation ensembles is developed and demonstrated over Britain for eventual use in an operational flood forecasting setting. The river flow ensembles are obtained from the distributed hydrological model Grid-to-Grid (G2G), configured with national coverage on a 1 km grid and using an ensemble of 15 minute precipitation accumulations as input. The precipitation ensemble consists of operational Numerical Weather Prediction (NWP) forecasts from the Met Office Unified Model. Given the different physical characteristics of river flow and catchment precipitation, and differences in forecast verification methodologies routinely employed by the hydrological and meteorological communities, key considerations for the common verification framework are identified and investigated. These include the appropriateness of different precipitation accumulation periods given timing errors and hydrological response times, the operationally relevant use of river flow and rainfall thresholds for contingency tables and skill scores based on them, and the effects of precipitation observation error on verification. The practical challenges of verification using a limited record of precipitation ensembles, from a system only relatively recently made operational, are highlighted. Methods of obtaining more robust verification statistics, given the available ensembles, are presented and demonstrated for example periods in December 2015. At the regional scale, both river flow and precipitation verification results are shown to be dependent on the locations considered and related to variations in precipitation totals. For river flows, catchment size is found to be a key influence on ensemble performance. It is demonstrated how this behaviour can be used to obtain more-robust river flow verification statistics at sub-regional scales.

The use of ensemble forecasts in operational rainfall and flood forecasting systems is rapidly increasing. In the UK, such systems are operated by the Flood Forecasting Centre (FFC) and Scottish Flood Forecasting Service (SFFS) producing ensemble gridded hydrological forecasts out to 6 days. In order to maximise the practical day-to-day use of these systems, for decision-making and warning, duty hydrometeorologists require a sound understanding of both the meteorological and hydrological ensemble forecast skill. A blended Met Office 24-member ensemble precipitation forecast – a mixture of the STEPS nowcast ensemble and STEPS-blended 2.2 km MOGREPS-UK ensemble and 32 km global MOGREPS-G ensemble – drives the Grid-to-Grid (G2G) distributed hydrological model developed by the Centre for Ecology & Hydrology (CEH). G2G uses 15-minute precipitation accumulations as input, and produces river flows at 15-minute intervals on a 1km grid. Phase 1 of the investigation, completed in 2017, formulated and demonstrated a common rainfall and river flow ensemble verification framework. The results gave an initial appreciation of the relative levels of skill in both ensemble rainfall and river flow forecasting systems. In 2018, the verifications of daily and hourly precipitation accumulations will be extended to use 15-minute accumulations. Verifications for three forecast time-horizons – Day 1, Days 2-3 and Days 4-6 – will also be demonstrated. In Phase 1, the sensitivity of verification measures to observation type was illustrated by comparing scores based on radar-only and raingauge-only analyses. Here, in Phase 2, theoretical principles discussed by Ferro (2017) are explored to determine whether a practical application of the theory is possible to gain a more robust measure of forecast performance in the presence of observation uncertainty. Reference Ferro, C.A.T. 2017. Measuring forecast performance in the presence of observation error. Q. J. R. Meteorol. Soc., 143, 2665-2676.