The paper analyzes the national DK-model hydrological information and prediction (HIP) system and HIP portal viewed as a ‘digital twin’ and how the introduction of real-time dynamic updating of the DK-model HIP simulations can make room for plug-in submodels with real-time boundary conditions made available from an HIP portal. The possible feedback to a national real-time risk knowledge base during extreme events (flooding and drought) is also discussed. Under climate change conditions, Denmark is likely to experience more rain in winter, more evapotranspiration in summer, intensified cloudbursts, drought, and sea level rise. These challenges were addressed as part of the Joint Governmental Digitalization Strategy 2016–2020 for better use and sharing of public data about the terrain, water, and climate to support climate adaptation, water management, and disaster risk reduction. This initiative included the development of a new web-based data portal (HIP portal) developed by the Danish Agency for Data Supply and Infrastructure (SDFI). GEUS delivered 5 terabytes of hydrological model data to the portal, with robust calibration methods and hybrid machine learning (ML) being key parts of the deliverables. This paper discusses the challenges and potentials of further developing the HIP digital twin with ‘plug-in digital twins’ for local river basins, including feedback to the national level.

A 133 yr data set from the 1055 km2 Skjern River catchment in western Denmark has been analysed with respect to precipitation, temperature, evapotranspiration and discharge. The precipitation series have been tested and corrected using the standard normal homogeneity test and subsequently corrected for undercatch. The degree of change in the climatic variables is examined using the non-parametric Mann–Kendall test. During the last 133 yr the area has experienced a significant change in precipitation of 26% and a temperature change of 1.4°C, leading to increases in river discharge of 52% and groundwater recharge of 86%. A lumped conceptual hydrological model, NAM, was calibrated on the period 1951–1980 and showed generally an excellent match between simulated and observed discharge. The capability of the hydrological model to predict climate change impact was investigated by looking at performances outside the calibration period. The results showed a reduced model fit, especially for recent time periods (after the 1980s), and not all hydrological changes could be explained. This might indicate that hydrological models cannot be expected to predict climate change impacts on discharge as accurately in the future, compared to the performance under present conditions, where they can be calibrated. The (simulated) stream discharge was subsequently analysed using high flow and drought indices based on the threshold method. The extreme signal was found to depend highly on the period chosen as reference to normal. The analysis indicated that no significant amplitude increase of the hydrograph for both wet and dry extremes could be found superimposed on the overall discharge increase.

In the latest IPCC report, worst case scenarios of climate change describe average global surface warming of up to 6°C from pre-industrial times by the year 2100. This study highlights the influence of a high-end 6 degree climate change on the hydrology of a catchment in central Denmark. A simulation from the global climate model, EC-Earth, is downscaled using the regional climate model HIRHAM5. A simple bias correction is applied for daily reference evapotranspiration and temperature, while distribution-based scaling is used for daily precipitation data. Both the 6 degree emission scenario and the less extreme RCP4.5 emission scenario are evaluated for the future period 2071−2099. The downscaled climate variables are applied to a fully distributed, physically based, coupled surface−subsurface hydrological model based on the MIKE SHE model code. The impacts on soil moisture dynamics and evapotranspiration show increasing drying-out tendencies for the future, most pronounced in the 6 degree scenario. Stream discharge and groundwater levels also show increased drying due to higher evapotranspiration. By comparing the 6 degree scenario with other emission scenarios, it is found that the most prominent changes in the water balance are caused by drying out of soils rather than precipitation effectsIn the latest IPCC report, worst case scenarios of climate change describe average global surface warming of up to 6°C from pre-industrial times by the year 2100. This study highlights the influence of a high-end 6 degree climate change on the hydrology of a catchment in central Denmark. A simulation from the global climate model, EC-Earth, is downscaled using the regional climate model HIRHAM5. A simple bias correction is applied for daily reference evapotranspiration and temperature, while distribution-based scaling is used for daily precipitation data. Both the 6 degree emission scenario and the less extreme RCP4.5 emission scenario are evaluated for the future period 2071−2099. The downscaled climate variables are applied to a fully distributed, physically based, coupled surface−subsurface hydrological model based on the MIKE SHE model code. The impacts on soil moisture dynamics and evapotranspiration show increasing drying-out tendencies for the future, most pronounced in the 6 degree scenario. Stream discharge and groundwater levels also show increased drying due to higher evapotranspiration. By comparing the 6 degree scenario with other emission scenarios, it is found that the most prominent changes in the water balance are caused by drying out of soils rather than precipitation effect