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.

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This paper describes the development of the first operational seasonal hydrological forecasting service for the UK, the Hydrological Outlook UK (HOUK). Since June 2013, this service has delivered monthly forecasts of streamflow and groundwater levels, with an emphasis on forecasting hydrological conditions over the next three months, accompanied by outlooks over longer time horizons. This system is based on three complementary approaches combined to produce the outlooks: (i) national-scale modelling of streamflow and groundwater levels based on dynamic seasonal rainfall forecasts, (ii) catchment-scale modelling where streamflow and groundwater level models are driven by historical meteorological forcings (i.e. the Ensemble Streamflow Prediction, ESP, approach), and (iii) a catchment-scale statistical method based on persistence and historical analogues. This paper provides the background to the Hydrological Outlook, describes the various component methods in detail and then considers the impact and usefulness of the product. As an example of a multi-method, operational seasonal hydrological forecasting system, it is hoped that this overview provides useful information and context for other forecasting initiatives around the world.ARTICLE HISTORY

River flow and quality data, including chlorophyll-a as a surrogate for river phytoplankton biomass, were collated for the River Ouse catchment in NE England, which according to established criteria is a largely unpolluted network. Against these data, a daily river quality model (QUESTOR) was setup and successfully tested. Following a review, a river quality classification scheme based on phytoplankton biomass was proposed. Based on climate change predictions the model indicated that a shift from present day oligotrophic/mesotrophic conditions to a mesotrophic/eutrophic system could occur by 2080. Management options were evaluated to mitigate against this predicted decline in quality. Reducing nutrient pollution was found to be less effective at suppressing phytoplankton growth than the less costly option of establishing riparian shading. In the Swale tributary, ongoing efforts to reduce phosphorus loads in sewage treatment works will only reduce peak (95 th percentile) phytoplankton by 11%, whereas a reduction of 44% is possible if riparian tree cover is also implemented. Likewise, in the Ure, whilst reducing nitrate loads by curtailing agriculture in the headwaters may bring about a 10% reduction, riparian shading would instead reduce levels by 47%. Such modelling studies are somewhat limited by insufficient field data but offer a potentially very valuable tool to assess the most cost-effective methods of tackling effects of eutrophication.

Abstract. Climate change increases the occurrence and severity of droughts due to increasing temperatures, altered circulation patterns, and reduced snow occurrence. While Europe has suffered from drought events in the last decade unlike ever seen since the beginning of weather recordings, harmonized long-term datasets across the continent are needed to monitor change and support predictions. Here we present soil moisture data from 66 cosmic-ray neutron sensors (CRNSs) in Europe (COSMOS-Europe for short) covering recent drought events. The CRNS sites are distributed across Europe and cover all major land use types and climate zones in Europe. The raw neutron count data from the CRNS stations were provided by 24 research institutions and processed using state-of-the-art methods. The harmonized processing included correction of the raw neutron counts and a harmonized methodology for the conversion into soil moisture based on available in situ information. In addition, the uncertainty estimate is provided with the dataset, information that is particularly useful for remote sensing and modeling applications. This paper presents the current spatiotemporal coverage of CRNS stations in Europe and describes the protocols for data processing from raw measurements to consistent soil moisture products. The data of the presented COSMOS-Europe network open up a manifold of potential applications for environmental research, such as remote sensing data validation, trend analysis, or model assimilation. The dataset could be of particular importance for the analysis of extreme climatic events at the continental scale. Due its timely relevance in the scope of climate change in the recent years, we demonstrate this potential application with a brief analysis on the spatiotemporal soil moisture variability. The dataset, entitled “Dataset of COSMOS-Europe: A European network of Cosmic-Ray Neutron Soil Moisture Sensors”, is shared via Forschungszentrum Jülich: https://doi.org/10.34731/x9s3-kr48 (Bogena and Ney, 2021).