Abstract. Over recent decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes to an unprecedented extent. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g. irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential for increased water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of largescale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs have incorporated human impacts on the hydrological cycle, yet the representation of human activities in hydrological models remains challenging. In this paper we provide a synthesis of progress in the development and application of human impact modelling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human-water interface in hydrological models.

Large-scale hydrological drought studies have demonstrated spatial and temporal patterns in observed trends and considerable difference exists among global hydrological models in their ability to reproduce these patterns. A controlled modeling experiment has been set up to systematically explore the role of climate and physical catchment structure (soils and groundwater systems) to better understand underlying drought-generating mechanisms. Daily climate data (1958–2001) of 1495 grid cells across the world were selected that represent Köppen-Geiger major climate types. These data were fed into a hydrological model. Nine realizations of physical catchment structure were defined for each grid cell, i.e. three soils with different soil moisture supply capacity and three groundwater systems (quickly-, intermediary- and slowly-responding). Hydrological drought characteristics (number, duration and standardized deficit volume) were identified from time series of daily discharge. Summary statistics showed that the equatorial and temperate climate types (A- and C-climates) had about twice as many drought events as the arid and polar types (B- and E-climates) and the duration of more extreme droughts were about half the length. Soils were found to have a minor effect on hydrological drought characteristics, whereas groundwater systems had major impact. Groundwater systems strongly controlled the hydrological drought characteristics of all climate types, but particularly those of the wetter A-, C- and D-climates because of higher recharge. The median number of drought for quickly-responding groundwater systems was about three times higher than for slowly-responding systems, which substantially affected the duration, particularly of the more extreme drought events. Bivariate probability distributions of drought duration and standardized deficit for combinations of Köppen-Geiger climate, soil and groundwater system showed that responsiveness of groundwater systems is as important as climate for hydrological drought development. This urges for an improvement of subsurface modules in global hydrological models to be more useful for water resources assessments. A foreseen higher spatial resolution would enable a better hydrogeological parameterization and inclusion of lateral flow

We analysed gross primary productivity (GPP), total ecosystem respiration (TER) and the resulting net ecosystem exchange (NEE) of carbon dioxide (CO 2 ) by the terrestrial biosphere during the summer of 2018 through observed changes across the Integrated Carbon Observation System (ICOS) network, through biosphere and inverse modelling, and through remote sensing. Highly correlated yet independently-derived reductions in productivity from sun-induced fluorescence, vegetative near-infrared reflectance, and GPP simulated by the Simple Biosphere model version 4 (SiB4) suggest a 130–340 TgC GPP reduction in July–August–September (JAS) of 2018. This occurs over an area of 1.6 × 10 6 km 2 with anomalously low precipitation in northwestern and central Europe. In this drought-affected area, reduced GPP, TER, NEE and soil moisture at ICOS ecosystem sites are reproduced satisfactorily by the SiB4 model. We found that, in contrast to the preceding 5 years, low soil moisture is the main stress factor across the affected area. SiB4’s NEE reduction by 57 TgC for JAS coincides with anomalously high atmospheric CO 2 observations in 2018, and this is closely matched by the NEE anomaly derived by CarbonTracker Europe (52 to 83 TgC). Increased NEE during the spring (May–June) of 2018 (SiB4 −52 TgC; CTE −46 to −55 TgC) largely offset this loss, as ecosystems took advantage of favourable growth conditions. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.

Traditional, mainstream definitions of drought describe it as deficit in water-related variables or water-dependent activities (e.g., precipitation, soil moisture, surface and groundwater storage, and irrigation) due to natural variabilities that are out of the control of local decision-makers. Here, we argue that within coupled human-water systems, drought must be defined and understood as a process as opposed to a product to help better frame and describe the complex and interrelated dynamics of both natural and human-induced changes that define anthropogenic drought as a compound multidimensional and multiscale phenomenon, governed by the combination of natural water variability, climate change, human decisions and activities, and altered micro-climate conditions due to changes in land and water management. This definition considers the full spectrum of dynamic feedbacks and processes (e.g., land-atmosphere interactions and water and energy balance) within human-nature systems that drive the development of anthropogenic drought. This process magnifies the water supply demand gap and can lead to water bankruptcy, which will become more rampant around the globe in the coming decades due to continuously growing water demands under compounding effects of climate change and global environmental degradation. This challenge has de facto implications for both short-term and long-term water resources planning and management, water governance, and policymaking. Herein, after a brief overview of the anthropogenic drought concept and its examples, we discuss existing research gaps and opportunities for better understanding, modeling, and management of this phenomenon.Plain Language Summary This article reviews research and progress on the notion of anthropogenic drought broadly defined as drought events caused or intensified by human activities. Most commonly used drought definitions are based on deficit in hydrologic/meteorologic drivers such as precipitation and runoff. Within coupled human-water systems, however, drought must be defined and understood as the complex and interrelated dynamics of both natural and human-induced changes. This anthropogenic drought definition considers the full spectrum of dynamic feedbacks and processes (e.g., land-atmosphere interactions and water and energy balance) within human-nature systems. Ideally, anthropogenic drought and the corresponding human interactions should be incorporated in models that include land-atmosphere interactions, water balance, and energy balance. In this article, we review AGHAKOUCHAK ET AL.

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Hydrological forecasts with a high temporal and spatial resolution are required to provide the level of information needed by end users. So far high-resolution multimodel seasonal hydrological forecasts have been unavailable due to 1) lack of availability of high-resolution meteorological seasonal forecasts, requiring temporal and spatial downscaling; 2) a mismatch between the provided seasonal forecast information and the user needs; and 3) lack of consistency between the hydrological model outputs to generate multimodel seasonal hydrological forecasts. As part of the End-to-End Demonstrator for Improved Decision Making in the Water Sector in Europe (EDgE) project commissioned by the Copernicus Climate Change Service (ECMWF), this study provides a unique dataset of seasonal hydrological forecasts derived from four general circulation models [CanCM4, GFDL Forecast-Oriented Low Ocean Resolution version of CM2.5 (GFDL-FLOR), ECMWF Season Forecast System 4 (ECMWF-S4), and Météo-France LFPW] in combination with four hydrological models [mesoscale hydrologic model (mHM), Noah-MP, PCRaster Global Water Balance (PCR-GLOBWB), and VIC]. The forecasts are provided at daily resolution, 6-month lead time, and 5-km spatial resolution over the historical period from 1993 to 2012. Consistency in hydrological model parameterization ensures an increased consistency in the hydrological forecasts. Results show that skillful discharge forecasts can be made throughout Europe up to 3 months in advance, with predictability up to 6 months for northern Europe resulting from the improved predictability of the spring snowmelt. The new system provides an unprecedented ensemble of seasonal hydrological forecasts with significant skill over Europe to support water management. This study highlights the potential advantages of multimodel based forecasting system in providing skillful hydrological forecasts.

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