We have obtained common offset, common midpoint (CMP) and borehole vertical (VRP) ground-penetrating radar profiles close to the margin of Falljo« kull, a small, steep temperate valley glacier situated in southeast Iceland. Velocity analysis of CMP and VRP surveys provided a four-layered velocity model. This model was verified by comparison between the depths of englacial reflectors and water channels seen in borehole video, and from the depths of boreholes drilled to the bed. In the absence of sediment within the glacier ice, radar velocity is inversely proportional to water content. Using mixture models developed by Paren and Looyenga, the variation of water content with depth was determined from the radar velocity profile. At the glacier surface the calculated water content is 0.23^0.34% (velocity 0.166 m ns^1), which rises sharply to 3.0^4.1% (velocity 0.149 m ns^1) at 28 m depth, interpreted to be the level of the piezometric surface. Below the piezometric surface the water content drops slowly to 2.4^3.3% (velocity 0.152 m ns^1) until $102 m depth where it falls to 0.09^0.14% (velocity 0.167 m ns^1). The water content of the ice then remains low to the glacier bed at about 112 m. These results suggest storage of a substantial volume of water within the glacier ice, which has significant implications for glacier hydrology, ice rheology and interpretations of both radar and seismic surveys.

Abstract. We present the first large-sample catchment hydrology dataset for Great Britain, CAMELS-GB (Catchment Attributes and MEteorology for Large-sample Studies). CAMELS-GB collates river flows, catchment attributes and catchment boundaries from the UK National River Flow Archive together with a suite of new meteorological time series and catchment attributes. These data are provided for 671 catchments that cover a wide range of climatic, hydrological, landscape, and human management characteristics across Great Britain. Daily time series covering 1970–2015 (a period including several hydrological extreme events) are provided for a range of hydro-meteorological variables including rainfall, potential evapotranspiration, temperature, radiation, humidity, and river flow. A comprehensive set of catchment attributes is quantified including topography, climate, hydrology, land cover, soils, and hydrogeology. Importantly, we also derive human management attributes (including attributes summarising abstractions, returns, and reservoir capacity in each catchment), as well as attributes describing the quality of the flow data including the first set of discharge uncertainty estimates (provided at multiple flow quantiles) for Great Britain. CAMELS-GB (Coxon et al., 2020; available at https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9) is intended for the community as a publicly available, easily accessible dataset to use in a wide range of environmental and modelling analyses.

Contact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner.This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Comparison of these soil water content observations with the Joint UK Land EnvironmentSimulator (JULES) 10 cm soil moisture layer shows that these data can be used to test and diagnose model performance, and indicates the potential for assimilation of these data into hydro-meteorological models. The application of these large-area soil water content measurements to evaluate remotely-sensed soil moisture products is also demonstrated.Numerous applications and the future development of a national COSMOS-UK network are discussed.

Abstract. The Centre for Ecology & Hydrology -Gridded Estimates of Areal Rainfall (CEH-GEAR) data set was developed to provide reliable 1 km gridded estimates of daily and monthly rainfall for Great Britain (GB) and Northern Ireland (NI) (together with approximately 3500 km 2 of catchment in the Republic of Ireland) from 1890 onwards. The data set was primarily required to support hydrological modelling.The rainfall estimates are derived from the Met Office collated historical weather observations for the UK which include a national database of rain gauge observations. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall (AAR), was used to generate the daily and monthly rainfall grids. To derive the monthly estimates, rainfall totals from monthly and daily (when complete month available) rain gauges were used in order to obtain maximum information from the rain gauge network. The daily grids were adjusted so that the monthly grids are fully consistent with the daily grids. The CEH-GEAR data set was developed according to the guidance provided by the British Standards Institution.The CEH-GEAR data set contains 1 km grids of daily and monthly rainfall estimates for GB and NI for the period 1890-2012. For each day and month, CEH-GEAR includes a secondary grid of distance to the nearest operational rain gauge. This may be used as an indicator of the quality of the estimates. When this distance is greater than 100 km, the estimates are not calculated due to high uncertainty.CEH-GEAR is available from doi:10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e and is free of charge for commercial and non-commercial use subject to licensing terms and conditions.

IntroductionOver the last 20-40 years major progress has been made in characterizing the hydrochemical functioning of catchments based on extensive, high-quality monitoring programmes. These data are vital for addressing issues, such as long-term responses of streams to external pressures, to assess the environmental impact. This is critical, for example, in relation to the issue of acidic deposition ( 3818 INVITED COMMENTARYRaw data and data edited to remove likely errors are provided on the CEH Information Gateway, and it is for the user to make informed judgements concerning analysis and interpretation. For the future, a universal standard will need to be developed and applied in the context of changing methodologies, which determine detection limits and sensitivity. However, informed judgement can only come with the provision of raw data as it is impossible to go back to the original values once the data have been censored and subsequently stored. This article not only flags the database but also includes references to published work and comments on new findings. While we recognize the importance of making data as freely available as possible, this is performed in relation to the institutional copyright for the data and recognition of previously published work. These are critical performance indicators that give value and endorsement to ensure the long-term continuation of major environmental monitoring programmes. We point out the logistical challenge of bringing the information together. This is important to recognize the amount of time that may be needed. We urge ongoing and future research to put data management systems in place that are robust, requiring minimum retrospective modification to cope with the potential loss of background knowledge that may occur when staff leave or research priorities change.