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Groundwater-dominated catchments are often critical for nationally important water resources. Many conceptual rainfall–runoff models tend to degrade in their model performance in groundwater-dominated catchments, as they are rarely designed to simulate spatial groundwater behaviours or interactions with surface waters. Intercatchment groundwater flow is one such neglected variable. Efforts have been made to incorporate this process into existing models, but there is a need for improving our perceptual models of groundwater–surface water interactions prior to any model modifications. In this study, national meteorological, hydrological, hydrogeological, geological and artificial influence (characterising abstractions and return flows) datasets are used to infer a perceptual model of intercatchment groundwater flow (IGF) and how it varies across the river Thames, United Kingdom (UK). We characterise the water balance, presence of gaining/losing river reaches and intra-annual dynamics in 80 subcatchments of the river Thames, taking advantage of its wealth of data, densely gauged river network and geological variability. We show the prevalence of non-conservative river reaches across the study area, with heterogeneity both between, and within, geological units, giving rise to a complex distribution of recharge and discharge points along the river network. We infer where non-conservative reaches can be attributed to IGF and where other processes (e.g. surface water abstractions) are the likely cause. Through analysis of recorded reach length water balance data and hydrogeological perceptualisation, we conclude that outcrops of carbonate fractured aquifers (Chalk and Jurassic limestone) show evidence of IGF both from headwater to downstream reaches, and out-of-catchment via spring lines. We found variability across the study area, with more seasonality and variability in river catchments on Jurassic limestone outcrops compared to Chalk and Lower Greensand outcrops. Our results demonstrate the need for local investigation and hydrogeological perceptualisation within regional analysis, which we show to be achievable given relatively simple geological interpretation and data requirements. We support the inclusion of IGF fluxes within existing models to enable calibration improvements in groundwater-dominated catchments, but with geologically specific characteristics, and (when perceptually appropriate) connectivity between catchments. [ABSTRACT FROM AUTHOR]

Water resource management (WRM) practices, such as groundwater and surface water abstractions and effluent discharges, may impact baseflow. Here the CAMELS-GB large-sample hydrology dataset is used to assess the impacts of such practices on Baseflow Index (BFI) using statistical models of 429 catchments from Great Britain. Two complementary modelling schemes, multiple linear regression (LR) and machine learning (random forests, RF), are used to investigate the relationship between BFI and two sets of covariates (natural covariates only and a combined set of natural and WRM covariates). The LR and RF models show good agreement between explanatory covariates. In all models, the extent of fractured aquifers, clay soils, non-aquifers, and crop cover in catchments, catchment topography, and aridity are significant or important natural covariates in explaining BFI. When WRM terms are included, groundwater abstraction is significant or the most important WRM covariate in both modelling schemes, and effluent discharge to rivers is also identified as significant or influential, although natural covariates still provide the main explanatory power of the models. Surface water abstraction is a significant covariate in the LR model but of only minor importance in the RF model. Reservoir storage covariates are not significant or are unimportant in both the LR and RF models for this large-sample analysis. Inclusion of WRM terms improves the performance of some models in specific catchments. The LR models of high BFI catchments with relatively high levels of groundwater abstraction show the greatest improvements, and there is some evidence of improvement in LR models of catchments with moderate to high effluent discharges. However, there is no evidence that the inclusion of the WRM covariates improves the performance of LR models for catchments with high surface water abstraction or that they improve the performance of the RF models. These observations are discussed within a conceptual framework for baseflow generation that incorporates WRM practices. A wide range of schemes and measures are used to manage water resources in the UK. These include conjunctive-use and low-flow alleviation schemes and hands-off flow measures. Systematic information on such schemes is currently unavailable in CAMELS-GB, and their specific effects on BFI cannot be constrained by the current study. Given the significance or importance of WRM terms in the models, it is recommended that information on WRM, particularly groundwater abstraction, should be included where possible in future large-sample hydrological datasets and in the analysis and prediction of BFI and other measures of baseflow. [ABSTRACT FROM AUTHOR]

There is a no lack of significant open questions in the field of hydrology. How will hydrological connectivity between freshwater bodies be altered by future human alterations to the hydrological cycle? Where does water go when it rains? Or what is the future space–time variability of flood and drought events? However, the answers to these questions will vary with location due to the specific and often poorly understood local boundary conditions and system properties that control the functional behaviour of a catchment or any other hydrologic control volume. We suggest that an open, shared and evolving perceptual model of a region's hydrology is critical to tailor our science questions, as it would be for any other study domain from the plot to the continental scale. In this opinion piece, we begin to discuss the elements of and point out some knowledge gaps in the perceptual model of the terrestrial water cycle of Great Britain. We discuss six major knowledge gaps and propose four key ways to reduce them. While the specific knowledge gaps in our perceptual model do not necessarily transfer to other places, we believe that the development of such perceptual models should be at the core of the debate for all hydrologic communities, and we encourage others to have a similar debate for their hydrologic domain. [ABSTRACT FROM AUTHOR]

An understanding of multi-annual behaviour in streamflow allows for better estimation of the risks associated with hydrological extremes. This can enable improved preparedness for streamflow-dependant services, such as freshwater ecology, drinking water supply and agriculture. Recently, efforts have focused on detecting relationships between long-term hydrological behaviour and oscillatory climate systems (such as the North Atlantic Oscillation – NAO). For instance, the approximate 7 year periodicity of the NAO has been detected in groundwater-level records in the North Atlantic region, providing potential improvements to the preparedness for future water resource extremes due to their repetitive, periodic nature. However, the extent to which these 7-year, NAO-like signals are propagated to streamflow, and the catchment processes that modulate this propagation, are currently unknown. Here, we show statistically significant evidence that these 7-year periodicities are present in streamflow (and associated catchment rainfall), by applying multi-resolution analysis to a large data set of streamflow and associated catchment rainfall across the UK. Our results provide new evidence for spatial patterns of NAO periodicities in UK rainfall, with areas of greatest NAO signal found in southwest England, south Wales, Northern Ireland and central Scotland, and show that NAO-like periodicities account for a greater proportion of streamflow variability in these areas. Furthermore, we find that catchments with greater subsurface pathway contribution, as characterised by the baseflow index (BFI), generally show increased NAO-like signal strength and that subsurface response times (as characterised by groundwater response time – GRT), of between 4 and 8 years, show a greater signal presence. Our results provide a foundation of understanding for the screening and use of streamflow teleconnections for improving the practice and policy of long-term streamflow resource management. [ABSTRACT FROM AUTHOR]

Groundwater use affects groundwater storage continuously as the removal of water changes both short-term and long-term groundwater level variation. This has implications for groundwater droughts, i.e. a below-normal groundwater level. The impact of groundwater use on groundwater droughts, however, remains unknown. Hence, the aim of this study is to investigate the impact of groundwater use on groundwater droughts in the absence of actual abstraction data. We present a methodological framework that consists of two approaches. The first approach compared groundwater droughts at monitoring sites that are potentially influenced by abstraction to groundwater droughts at sites that are known to be near natural. Observed groundwater droughts were compared in terms of drought occurrence, duration, and magnitude. The second approach investigated long-term trends in groundwater levels in all monitoring wells. This framework was applied to a case study of the UK, using four regional water management units in which groundwater levels are monitored and abstractions are licensed. Results show two asymmetric responses in groundwater drought characteristics due to groundwater use. The first response is an increase in shorter drought events and is found in three water management units where long-term annual average groundwater abstractions are smaller than recharge. The second response, observed in one water management unit where groundwater abstractions temporarily exceeded recharge, is a lengthening and intensification of groundwater droughts. Analysis of long-term (1984–2014) trends in groundwater levels shows mixed but generally positive trends, while trends in precipitation and potential evapotranspiration are not significant. The overall rising groundwater levels are consistent with changes in water use regulations and with a general reduction in abstractions during the period of investigation. We summarised our results in a conceptual typology that illustrates the asymmetric impact of groundwater use on groundwater drought occurrence, duration, and magnitude. The long-term balance between groundwater abstraction and recharge plays an important role in this asymmetric impact, which highlights the relation between short-term and long-term sustainable groundwater use. [ABSTRACT FROM AUTHOR]

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 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. [ABSTRACT FROM AUTHOR]

Benchmarking model performance across large samples of catchments is useful to guide model selection and future model development. Given uncertainties in the observational data we use to drive and evaluate hydrological models, and uncertainties in the structure and parameterisation of models we use to produce hydrological simulations and predictions, it is essential that model evaluation is undertaken within an uncertainty analysis framework. Here, we benchmark the capability of several lumped hydrological models across Great Britain by focusing on daily flow and peak flow simulation. Four hydrological model structures from the Framework for Understanding Structural Errors (FUSE) were applied to over 1000 catchments in England, Wales and Scotland. Model performance was then evaluated using standard performance metrics for daily flows and novel performance metrics for peak flows considering parameter uncertainty. Our results show that lumped hydrological models were able to produce adequate simulations across most of Great Britain, with each model producing simulations exceeding a 0.5 Nash–Sutcliffe efficiency for at least 80 % of catchments. All four models showed a similar spatial pattern of performance, producing better simulations in the wetter catchments to the west and poor model performance in central Scotland and south-eastern England. Poor model performance was often linked to the catchment water balance, with models unable to capture the catchment hydrology where the water balance did not close. Overall, performance was similar between model structures, but different models performed better for different catchment characteristics and metrics, as well as for assessing daily or peak flows, leading to the ensemble of model structures outperforming any single structure, thus demonstrating the value of using multi-model structures across a large sample of different catchment behaviours. This research evaluates what conceptual lumped models can achieve as a performance benchmark and provides interesting insights into where and why these simple models may fail. The large number of river catchments included in this study makes it an appropriate benchmark for any future developments of a national model of Great Britain. [ABSTRACT FROM AUTHOR]

Predicting the next major drought is of paramount interest to water managers globally. Estimating the onset of groundwater drought is of particular importance, as groundwater resources are often assumed to be more resilient when surface water resources begin to fail. A potential source of long-term forecasting is offered by possible periodic controls on groundwater level via teleconnections with oscillatory ocean–atmosphere systems. However, relationships between large-scale climate systems and regional to local-scale rainfall, evapotranspiration (ET) and groundwater are often complex and non-linear so that the influence of long-term climate cycles on groundwater drought remains poorly understood. Furthermore, it is currently unknown whether the absolute contribution of multi-annual climate variability to total groundwater storage is significant. This study assesses the extent to which multi-annual variability in groundwater can be used to indicate the timing of groundwater droughts in the UK. Continuous wavelet transforms show how repeating teleconnection-driven 7-year and 16–32-year cycles in the majority of groundwater sites from all the UK's major aquifers can systematically control the recurrence of groundwater drought; and we provide evidence that these periodic modes are driven by teleconnections. Wavelet reconstructions demonstrate that multi-annual periodicities of the North Atlantic Oscillation, known to drive North Atlantic meteorology, comprise up to 40 % of the total groundwater storage variability. Furthermore, the majority of UK recorded droughts in recent history coincide with a minimum phase in the 7-year NAO-driven cycles in groundwater level, providing insight into drought occurrences on a multi-annual timescale. Long-range groundwater drought forecasts via climate teleconnections present transformational opportunities to drought prediction and its management across the North Atlantic region. [ABSTRACT FROM AUTHOR]

Here we present the first empirical evidence for changes in groundwater drought associated with anthropogenic warming in the absence of long-term changes in precipitation. Analysing standardised indices of monthly groundwater levels, precipitation and temperature, using two unique groundwater level data sets from the Chalk aquifer, UK, for the period 1891 to 2015, we show that precipitation deficits are the main control on groundwater drought formation and propagation. However, long-term changes in groundwater drought are shown to be associated with anthropogenic warming over the study period. These include increases in the frequency and intensity of individual groundwater drought months, and increases in the frequency, magnitude and intensity of episodes of groundwater drought, as well as an increasing tendency for both longer episodes of groundwater drought and for an increase in droughts of less than 1 year in duration. We also identify a transition from a coincidence of episodes of groundwater drought with precipitation droughts at the end of the 19th century, to an increasing coincidence with both precipitation droughts and with hot periods in the early 21st century. In the absence of long-term changes in precipitation deficits, we infer that the changing nature of groundwater droughts is due to changes in evapotranspiration (ET) associated with anthropogenic warming. We note that although the water tables are relatively deep at the two study sites, a thick capillary fringe of at least 30 m in the Chalk means that ET should not be limited by precipitation at either site. ET may be supported by groundwater through major episodes of groundwater drought and, hence, long-term changes in ET associated with anthropogenic warming may drive long-term changes in groundwater drought phenomena in the Chalk aquifer. Given the extent of shallow groundwater globally, anthropogenic warming may widely effect changes to groundwater drought characteristics in temperate environments. [ABSTRACT FROM AUTHOR]

We examine the evidence for climate-change impacts on groundwater levels provided by studies of the historical observational record, and future climate-change impact modelling. To date no evidence has been found for systematic changes in groundwater drought frequency or intensity in the UK, but some evidence of multi-annual to decadal coherence of groundwater levels and large-scale climate indices has been found, which should be considered when trying to identify any trends. We analyse trends in long groundwater level time-series monitored in seven observation boreholes in the Chalk aquifer, and identify statistically significant declines at four of these sites, but do not attempt to attribute these to a change in a stimulus. The evidence for the impacts of future climate change on UK groundwater recharge and levels is limited. The number of studies that have been undertaken is small and different approaches have been adopted to quantify impacts. Furthermore, these studies have generally focused on relatively small regions and reported local findings. Consequently, it has been difficult to compare them between locations. We undertake some additional analysis of the probabilistic outputs of the one recent impact study that has produced coherent multi-site projections of changes in groundwater levels. These results suggest reductions in annual and average summer levels, and increases in average winter levels, by the 2050s under a high greenhouse gas emissions scenario, at most of the sites modelled, when expressed by the median of the ensemble of simulations. It is concluded, however, that local hydrogeological conditions can be an important control on the simulated response to a future climate projection. [ABSTRACT FROM AUTHOR]

Climate change is expected to modify rainfall, temperature and catchment hydrological responses across the world, and adapting to these water-related changes is a pressing challenge. This paper reviews the impact of anthropogenic climate change on water in the UK and looks at projections of future change. The natural variability of the UK climate makes change hard to detect; only historical increases in air temperature can be attributed to anthropogenic climate forcing, but over the last 50 years more winter rainfall has been falling in intense events. Future changes in rainfall and evapotranspiration could lead to changed flow regimes and impacts on water quality, aquatic ecosystems and water availability. Summer flows may decrease on average, but floods may become larger and more frequent. River and lake water quality may decline as a result of higher water temperatures, lower river flows and increased algal blooms in summer, and because of higher flows in the winter. In communicating this important work, researchers should pay particular attention to explaining confidence and uncertainty clearly. Much of the relevant research is either global or highly localized: decision-makers would benefit from more studies that address water and climate change at a spatial and temporal scale appropriate for the decisions they make. [ABSTRACT FROM AUTHOR]

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Summary: This study introduces new approaches to improve the statistical robustness of techniques for quantifying the fractal scaling of groundwater levels, and uses these techniques to investigate scaling of groundwater levels from a consolidated permeable carbonate aquifer. Six groundwater level time series and an associated river stage time series from the unconfined Chalk aquifer (a dual-porosity, fractured limestone aquifer) in the Pang–Lambourn catchment, UK, have been analysed. Surrogate data of time series with known scaling properties have been used to estimate the probability distribution of the spectral and geometric scaling exponents determined by detrended fluctuation analysis (DFA) and power spectral density (PSD) respectively; robust regression techniques have been used to improve estimates of the scaling exponents; and robust non-parametric techniques have been used to correlate scaling exponents with features of the boreholes and catchments. Strong statistical support has been found for temporal scaling of groundwater levels over a wide range of time scales, however, bootstrap estimates of the scaling exponents indicate a much larger range of exponents than found by previous studies, suggesting that the uncertainty in existing estimates of scaling exponents may be too small. There is robust evidence that geometrical scaling properties at each borehole can be related to the depth of the observation boreholes and distance of those boreholes from the river in the catchment, but no such correlations were found for the spectral scaling exponents. The results build on the body of evidence that groundwater levels, as with many hydrogeological phenomena, may be well modelled with mathematical concepts from statistical mechanics that do not attempt to capture every detail of these highly heterogeneous and complex systems. [ABSTRACT FROM AUTHOR]

• In catchments <300 km2 geology controls daily- to multi-year streamflow variability. • Catchments >300 km2 variability mostly from mixing upstream- and downstream-flow. • JULES land surface model performs poorly in small, high-permeability catchments. • Diverting some rainfall as bypass flow to bedrock improves JULES simulated flow. Geological factors controlling daily- to multi-year discharge variability in 48 sub-catchments spanning 10–1000 km2 in the Thames Basin were investigated using cross-spectral analysis. The analyses represent a 'transfer function approach' applied to daily observed streamflow (output) versus catchment-wide precipitation (input) for data spanning 1990–2014. Catchments dominated by high-permeability bedrock have significant attenuation of high-frequency precipitation variability and large delays at all frequencies with streamflow dominated by baseflow (high lag1 autocorrelation and high Base Flow Index, BFI). Catchments dominated by low-permeability rocks have little high-frequency attenuation and small delays and consequently 'flashy' behaviour. For all sub-catchments >300 km2 in the Thames Basin, attenuation of the highest frequency precipitation variability caused by mixing of flow from upstream plus groundwater flow (representing 'older' variability) with direct surface flow ('younger' variability) constitutes real-world moving averaging as indicated by a roll-off in power at the highest frequencies. The success of the JULES land surface model in simulating discharge (i.e. surface and sub-surface runoff routed between grid boxes) is also linked to the underlying geology. Larger catchments (>300 km2) are modelled well because routing between numerous grid boxes leads to moving averaging that is a good analogue for the observations. Modelling was least successful (e.g. lowest Kling-Gupta Efficiency) for small catchments (<300 km2) dominated by high-permeability bedrock - with far too little attenuation of high-frequency precipitation variability and insufficient delays at all frequencies. Experimentally switching the soil saturated hydraulic conductivity to that of the underlying bedrock for grid boxes dominated by aquifers significantly improves modelled discharge variability in small sub-catchments - confirming the importance of bedrock permeability in modelling. For small catchments in data-sparse regions, knowledge of the relative proportions of different hydrogeological units (aquifers, aquitards) potentially could be used to predict and model discharge variability as characterised by BFI and lag1 autocorrelation. [ABSTRACT FROM AUTHOR]

In order to determine objectively the fractal behaviour of a time series, and to facilitate potential future attempts to assess model performance by incorporating fractal behaviour, a multi-order robust detrended fluctuation analysis (r-DFAn) procedure is developed herein. The r-DFAn procedure allows for robust and automated quantification of mono-fractal behaviour. The fractal behaviour is quantified with three parts: a global scaling exponent, crossovers, and local scaling exponents. The robustness of the r-DFAn procedure is established by the systematic use of robust regression, piecewise linear regression, Analysis of Covariance (ANCOVA) and Multiple Comparison Procedure to determine statistically significant scaling exponents and optimum crossover locations. The MATLAB code implementing the r-DFAn procedure has also been open sourced to enable reproducible results. r-DFAn will be illustrated on a synthetic signal after which is used to analyse high-resolution hydrologic data; although the r-DFAn procedure is not limited to hydrological or geophysical time series. The hydrological data are 4 year-long datasets (January 2012 to January 2016) of 1-min groundwater level, river stage, groundwater and river temperature, and 15-min precipitation and air temperature, at Wallingford, UK. The datasets are analysed in both time and fractal domains. The study area is a shallow riparian aquifer in hydraulic connection to River Thames, which traverses the site. The unusually high resolution datasets, along with the responsive nature of the aquifer, enable detailed examination of the various data and their interconnections in both time- and fractal-domains. [ABSTRACT FROM AUTHOR]

Data underpin our knowledge and understanding of the hydrological system; they are used to drive, test and evaluate hydrological models and advance our understanding of hydrological processes and dynamics. With the increasing availability of observational datasets, the integration of information from many catchments for data and modelling analyses is becoming increasingly common. The production of new, open source, datasets for large samples of catchments is vital to advance knowledge on hydrological processes, to underpin common frameworks for model evaluation across complex domains, and to ensure hydrological research is reusable and reproducible through the use of common datasets and code. However, the availability of open source, large-sample catchment datasets is notably sparse. In this study, we present the first large sample, open-source, hydro-meteorological catchment dataset for Great Britain, CAMELS-GB (Catchment Attributes and MEteorology for Large-sample Studies). CAMELS-GB integrates a wealth of different spatial and time-varying datasets formulated from national, continental and global products based on observational, satellite and derived products. The dataset consists of hydro-meteorological timeseries, catchment attributes and catchment boundaries for >800 catchments that cover a wide range of climatic, hydrological, landscape and human management characteristics across Great Britain. Daily timeseries covering 1970-2015 are provided for a range of hydro-meteorological data (including rainfall, potential evapotranspiration, temperature, radiation, humidity and flow) and cover several major hydrological episodes (i.e. nationally important drought and flood periods). A comprehensive set of summary attributes are quantified describing a range of catchment characteristics including topography, climate, hydrology, land cover, soils and (hydro)-geology. Importantly, we also derive human impact attributes (including abstraction returns, percentage urban and gauge distance from reservoir), as well as attributes describing the quality of the flow data (including discharge uncertainty estimates and out of bank flow). This ensures users can identify, for example, human impacted catchments when evaluating models or analysing data. The dataset and code used to derive the data will be made open source and provided with comprehensive metadata to allow its use in a wide range of hydro-meteorological data and environmental modelling analyses. These data are part of a wider international initiative to generate multi-national, large-sample datasets to facilitate reproducible and reusable hydrological research. [ABSTRACT FROM AUTHOR]

Groundwater teleconnections is a growing area of research seeking to detect and understand relationships between wide-scale ocean-atmosphere oscillations and groundwater response. Such relationships can yield important predictive information on groundwater variability and extremes for future years or decades. However, due to the complex non-linear relationships between large-scale climate systems and regional to local-scale rainfall, ET and groundwater; detecting wide-scale evidence of such groundwater teleconnections, and their influence on drought and groundwater flooding, has been difficult. Here, we present the biggest groundwater teleconnection study to date, using an improved wavelet-based methodology to (1) quantify the strength of annual to multi-annual cyclical behaviour in monthly groundwater levels in 60 UK reference boreholes; (2) Analyse rainfall and ET to assess the contribution of teleconnections for these periodicities, and (3) evaluate how indicative these cycles are of groundwater extremes in the UK. Our results are the first to quantify the relative strength of seasonal and extra-seasonal variance in monthly groundwater levels, indicating that ~7-year cycles in Chalk (limestone) and sandstone groundwater levels are often comparable to seasonality in defining total groundwater level variability. We demonstrate that the ~7 year periodicity in groundwater results from a rainfall-based teleconnection with the North Atlantic Oscillation; documenting a clear alignment with every major recorded instance of groundwater drought (and recent instances of groundwater flooding) in the UK. An understanding that the severity of groundwater drought, and to some extent flooding, is enhanced on a 7-year cycle, produced through a teleconnection, provides significant opportunity for forecasting of future groundwater extremes. This understanding will becoming increasingly critical given the expected increased pressure on groundwater resources as a result of climate change, particularly in the UK and Europe. [ABSTRACT FROM AUTHOR]