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Many 3D hydrostratigraphic models of the subsurface are interpreted as deterministic models, where an experienced modeler combines relevant geophysical and geological information with background geological knowledge. Depending on the quality of the information from the input data, the interpretation phase will typically be accompanied by an estimated qualitative interpretation uncertainty. Given the qualitative nature of uncertainty, it is difficult to propagate the uncertainty to groundwater models. In this study, a stochastic-simulation-based methodology to characterize interpretation uncertainty within a manual-interpretation-based layer model is applied in a groundwater modeling setting. Three scenarios with different levels of interpretation uncertainty are generated, and three locations representing different geological structures are analyzed in the models. The impact of interpretation uncertainty on predictions of capture zone area and median travel time is compared to the impact of parameter uncertainty in the groundwater model. The main result is that in areas with thick and large aquifers and low geological uncertainty, the impact of interpretation uncertainty is negligible compared to the hydrogeological parameterization, while it may introduce a significant contribution in areas with thinner and smaller aquifers with high geologic uncertainty. The influence of the interpretation uncertainties is thus dependent on the geological setting as well as the confidence of the interpreter. In areas with thick aquifers, this study confirms existing evidence that if the conceptual model is well defined, interpretation uncertainties within the conceptual model have limited impact on groundwater model predictions.

Droughts are a natural hazard with far-reaching consequences and recent studies and climate projections show that more drought is expected in the future. Previous studies have investigated the projected changes in drought occurrence in a Danish context. This study sought to enhance an existing hydrological model for the Ahlergaarde catchment in Denmark by calibrating it toward drought situations. An objective function containing only the 10% lowest streamflow values was incorporated in the calibration of the distributed MIKE SHE model. The calibrated model (calib2) showed improved performance on the discharge for most discharge stations across most performance evaluation criteria compared to the previous model (calib1). By calculating weekly drought indices (SDI, SGDI, SMDI) and comparing the model simulations with the observations, we also found an improved performance of calib2 for discharge. However, results showed reduced performance on groundwater head as well as SGDI, due to the reduced weighting in the calibration scheme. Additionally, the future changes in drought occurrence were evaluated by drought indices for three chosen climate models (wet, medium, and dry) in the far future (2071-2100) for RCP8.5. Results from the dry model showed an increase in total streamflow drought weeks in the future, with the largest increase in summer droughts and a reduction in winter droughts. Both the medium and wet models showed a considerable reduction across seasons and severity levels for SDI with minor exceptions. The SGDI showed large reductions for all three climate models. The uncertainties regarding these results are not quantified and more research is needed to assess the consequences of the changing drought patterns.

Dette kapitel gennemgår Danmarks performance på verdensmål 11 for bæredygtig udvikling: Bæredygtige byer og lokalsamfund. Over halvdelen af verdens befolkning bor i byer, og antallet af byboere forventes at vokse med 2,5 milliarder i de kommende 30 år. Frem mod år 2100 forventes det globale byareal at blive fordoblet i forhold til 2010. Byområderne vil sprede sig over naturområder og vil have massive miljømæssige konsekvenser, hvis ikke væksten begræn-ses og styres. Allerede i dag knytter 70 % af klodens samlede CO2-udledning sig til byerne. Byerne står for en lang række af de sociale problemer, verdensmålene omfatter. De proble-mer, vi skal løse i efterstræbelsen af en bæredygtig fremtid, skal i vidt omfang ske i byerne.

Accurate large-scale soil moisture (SM) maps are crucial for catchment-scale hydrological models used for water resource management and warning systems for droughts, floods, and wildfires. SM can be mapped by mobile cosmic-ray neutron (CRN) systems of moderated detectors at homogeneous landscapes of similar soil and vegetation. In this study, we present a new approach for mobile CRN detection to perform to its full potential, where CRN measurements can also be converted to SM at heterogeneous landscapes. The approach is based solely on thermal and epithermal neutron datasets obtained from mobile dual-spectra CRN detection, combined with theoretical developments using a particle transport model. For each measurement point, the land cover type is identified using the thermal-to-epithermal (T/E) ratio, and the relevant neutron-count-to-soil-moisture conversion function is estimated from CRN stations located at the main land cover types in the catchment. With this approach, the requirement of collecting 100+ soil samples for each point along the survey route is omitted. We use this T/E-dependent approach to obtain SM maps from 12 CRN surveys and compare it with a simple approach where only the conversion function from the agricultural site is used. SM by the simple approach is comparable to the estimates of the agricultural stations of a capacitance sensor network, while the estimates of the T/E-dependent approach also compare well with the heathland and forest stations. With accurate SM estimates for all landcover types, the average error is reduced from 0.089 to 0.038 when comparing CRN SM with space-borne Soil Moisture Active Passive Mission estimates.

Introduction: The risk of traumatic injury in football has been suggested to be affected by field conditions. This study, therefore, aimed to investigate whether near surface water content of the football field, influenced the risk of traumatic injuries during a youth football tournament. Methods: At Dana Cup, an annual international youth football tournament in Denmark, all injuries were registered and classified at the on-site emergency department over 7 years. The incidence rate of traumatic injury was computed. Meteorological data and soil characteristics were used to simulate near surface water content of the playing fields. The incidence rate ratio (IRR) between water content and injury incidence rate was analyzed using a multivariate Poisson regression, controlling for tournament stage and demographical parameters. Results: About 2704 injuries were recorded corresponding to a risk time of 284 905 player hours. An inverse relation between water contents and the incidence rate of traumatic injury was found (IRR = 0.24 95% CI 0.1–0.7, p = 0.01). The incidence rate of traumatic injury increased with advancing tournament stage, that is, for the finals (IRR = 4.30 95% CI 2.8–6.6, p < 0.001). Also we found an interaction between dry fields and the final stage of tournament, further exacerbating this effect. Conclusions: Our data suggest that the incidence rate of traumatic injury is increased with drier field conditions and advanced tournament stages.

Soil moisture estimates at high spatial and temporal resolution are of great value for optimizing water and agricultural management. To fill the gap between local ground observations and coarse spatial resolution remote sensing products, we use Soil Moisture Active Passive (SMAP) and Sentinel-1 data together with a unique data set of ground-based soil moisture estimates by cosmic ray neutron sensors (CRNS) and capacitance probes to test the possibility of downscaling soil moisture to the sub-kilometre resolution. For a high-latitude study area within a highly heterogeneous landscape and diverse land use in Denmark, we first show that SMAP soil moisture and Sentinel-1 backscatter time series correlate well with in situ CRNS observations. Sentinel-1 backscatter in both VV and VH polarizations shows a strong correlation with CRNS soil moisture at higher spatial resolutions (20-400 m) and exhibits distinct and meaningful signals at different land cover types. Satisfactory statistical correlations with CRNS soil moisture time series and capacitance probes are obtained using the SMAP Sentinel-1 downscaling algorithm. Accounting for different land use in the downscaling algorithm additionally improved the spatial distribution. However, the downscaling algorithm investigated here does not fully account for the vegetation dependency at sub-kilometre resolution. The study suggests that future research focussing on further modifying the downscaling algorithm could improve representative soil moisture patterns at a fine scale since backscatter signals are clearly informative.

The effects of partial deforestation in a small, forested headwater catchment were examined over a 10-year period using actual evapotranspiration (AET), soil water content (SWC) and discharge (Q). In the immediate period after deforestation, the fluxes and states were observed to respond significantly, and over the next six years the effects attenuated. A MIKE SHE model was setup and calibrated using the most current data, to predict the spatiotemporal variation of states and fluxes in the system both before and after partial deforestation. The model could predict the general dynamics of the system to a satisfactory level, but overestimated AET which in turn resulted in an underestimation of Q. The SWC was reasonably predicted in selected points, but the spatial distribution could not be accurately determined with the calibration scheme and conceptual setup. The MIKE SHE model could predict the change in direction, but not the magnitude of fluxes and states in response to partial deforestation. This study evaluated the capabilities ofMIKESHEand found that the conceptual setup, aswell as underlying assumptions in the Kristensen and Jensen model responsible for calculating AET were insufficient for these particular climate and soil conditions.

The eddy covariance method estimates the energy flux of latent heat for evapotranspiration. However, imbalance between the land surface energy output and input is a well-known fact. Energy balance closure is most commonly not achieved, and therefore the eddy covariance method potentially underestimates actual evapotranspiration. Notwithstanding, the method is one of the most established measurement techniques for estimating evapotranspiration. Here, evapotranspiration from eddy covariance (ETEC) is cross-checked with evapotranspiration calculated as the residual of the water balance (ETwb). The water balance closure using ETEC is simultaneously validated. Over a 6-yr period, all major terms of the water balance are measured including precipitation, recharge from percolation lysimeters, and soil moisture content from a cosmic-ray neutron sensor, a capacitance sensor network, and time domain reflectometry (TDR), respectively. In addition, we estimate their respective uncertainties. The study demonstrates that both monthly and yearly ETEC and ETwb compare well and that the water balance is closed when ETEC is used. Concurrently, incoming available energy (net radiation minus ground heat flux) on average exceeds the turbulent energy fluxes (latent heat flux and sensible heat flux) by 31%, exposing the energy–surface imbalance. Consequently, the imbalance in the energy balance using the eddy covariance method must, to a lesser degree, be caused by errors in the latent heat estimates but can mainly be attributed to errors in the other energy flux components.

One of the major challenges in hydrological data assimilation applications is the presence of bias in both models and observations. The present study uses the ensemble transform Kalman filtering (ETKF) method and an observational bias estimation technique to estimate groundwater hydraulic heads. The study was carried out in a relatively complex, groundwater dominated, catchment in Denmark using the MIKE SHE model code. The method is implemented and evaluated using synthetic data and subsequently tested against real observations. The results from the synthetic experiments show that the bias-aware filter outperforms the standard filter, with improved state estimate and correct bias estimate. The assimilation using real observations further demonstrates the robustness of bias-aware ETKF, and the potential improvements using integrated hydrological modelling. Furthermore, the experiments with assimilating over different depths show that the state estimates depend on correlation across layers.

This study utilized an existing model, constructed for integrated distributed regional hydrological modelling for the municipality of Kolding, to construct a smaller model for an urban catchment at the city of Kolding. The aim of the study was to examine modelling methods for urban catchments using the distributed integrated hydrological model code MIKE SHE. A model with a discretization of 10x10 meters was set up for the catchment. The model aimed to incorporate urban elements such as sewers and land use classes in order to simulate the urban water cycle accurately. The model was calibrated and validated against point observations on hydraulic head, surface water bodies, groundwater infiltrating to sewer pipes, and yearly sewer flow to the local wastewater treatment plant. The model was calibrated to obtain the status of a high-fidelity model suited for highly detailed analysis of terrain-near groundwater. The model was further used to simulate the hydrological effects of artificial infiltration through soakwells and complete sewer renovation. This study illustrated that considerable amounts of observations are needed to better constrain the inverse problem related to calibrating urban models. The results underlined that spatial heterogeneity is highly important due to the complex urban landscape altering hydrological fluxes. The scenario simulations illustrated that special care should be taken when allowing for infiltration solutions and renovation of sewers as the effect can be rising groundwater table and an increase in infiltration of groundwater to the sewer system. It is furthermore important to underline that the findings of this study concludes that there is a significant need for measurement campaigns and further modelling studies to develop the best methodology for urban hydrological modelling., This study utilized an existing model, constructed for integrated distributed regional hydrological modelling for the municipality of Kolding, to construct a smaller model for an urban catchment at the city of Kolding. The aim of the study was to examine modelling methods for urban catchments using the distributed integrated hydrological model code MIKE SHE. A model with a discretization of 10x10 meters was set up for the catchment. The model aimed to incorporate urban elements such as sewers and land use classes in order to simulate the urban water cycle accurately. The model was calibrated and validated against point observations on hydraulic head, surface water bodies, groundwater infiltrating to sewer pipes, and yearly sewer flow to the local wastewater treatment plant. The model was calibrated to obtain the status of a high-fidelity model suited for highly detailed analysis of terrain-near groundwater. The model was further used to simulate the hydrological effects of artificial infiltration through soakwells and complete sewer renovation. This study illustrated that considerable amounts of observations are needed to better constrain the inverse problem related to calibrating urban models. The results underlined that spatial heterogeneity is highly important due to the complex urban landscape altering hydrological fluxes. The scenario simulations illustrated that special care should be taken when allowing for infiltration solutions and renovation of sewers as the effect can be rising groundwater table and an increase in infiltration of groundwater to the sewer system. It is furthermore important to underline that the findings of this study concludes that there is a significant need for measurement campaigns and further modelling studies to develop the best methodology for urban hydrological modelling.

Cosmic-ray neutron intensity is inversely correlated to all hydrogen present in the upper decimeters of the subsurface and the first few hectometers of the atmosphere above the ground surface. This correlation forms the base of the cosmic-ray neutron soil moisture estimation method. The method is, however, complicated by the fact that several hydrogen pools other than soil moisture affect the neutron intensity. In order to improve the cosmic-ray neutron soil moisture estimation method and explore the potential for additional applications, knowledge about the environmental effect on cosmic-ray neutron intensity is essential (e.g., the effect of vegetation, litter layer and soil type). In this study the environmental effect is examined by performing a sensitivity analysis using neutron transport modeling. We use a neutron transport model with various representations of the forest and different parameters describing the subsurface to match measured height profiles and time series of thermal and epithermal neutron intensities at a field site in Denmark. Overall, modeled thermal and epithermal neutron intensities are in satisfactory agreement with measurements; however, the choice of forest canopy conceptualization is found to be significant. Modeling results show that the effect of canopy interception, soil chemistry and dry bulk density of litter and mineral soil on neutron intensity is small. On the other hand, the neutron intensity decreases significantly with added litter-layer thickness, especially for epithermal neutron energies. Forest biomass also has a significant influence on the neutron intensity height profiles at the examined field site, altering both the shape of the profiles and the ground-level thermal-to-epithermal neutron ratio. This ratio increases with increasing amounts of biomass, and was confirmed by measurements from three sites representing agricultural, heathland and forest land cover. A much smaller effect of canopy interception on the grou

Stationarity has traditionally been a requirement of geostatistical simulations. A common way to deal with non-stationarity is to divide the system into stationary sub-regions and subsequently merge the realizations for each region. Recently, the so-called partition approach that has the flexibility to model non-stationary systems directly was developed for multiple-point statistics simulation (MPS). The objective of this study is to apply the MPS partition method with conventional borehole logs and high-resolution airborne electromagnetic (AEM) data, for simulation of a real-world non-stationary geological system characterized by a network of connected buried valleys that incise deeply into layered Miocene sediments (case study in Denmark). The results show that, based on fragmented information of the formation boundaries, the MPS partition method is able to simulate a non-stationary system including valley structures embedded in a layered Miocene sequence in a single run. Besides, statistical information retrieved from the AEM data improved the simulation of the geology significantly, especially for the deep-seated buried valley sediments where borehole information is sparse.

Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes on hydrology for a 486 km2 catchment in Denmark and to evaluate the sensitivity of the results to the choice of hydrological model. Three hydrological models, NAM, SWAT and MIKE SHE, were constructed and calibrated using similar methods. Each model was forced with results from four climate models and four land use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice remained the dominant factor for mean discharge, low and high flows as well as hydraulic head at the end of the century.

This report investigates the phenomenon of compound flooding. The combined effect of river flow with tide and surge, and the frequencies of which such events occur, resulting with extreme water levels in tidal rivers and estuaries, increasing potential risk to society. To investigate this phenomenon the location of Odense has been selected as a case study. Due to the EU Floods Directive (Directive 2007/60/EF) call for all EU member states to be prepared for extreme flood risk, a reaction to events in Central Europe during the period of 1998-2002, the Danish State selected Odense Fjord as one of ten areas at risk of extreme flooding conditions (2011). A quality check of observational data at the locality took place and conditions of the variables investigated. Statistical methods and numerical modelling techniques using software created by DHI are then utilized to define and simulate the relationships between the hydrological variables. Initially an extreme value analysis takes place using the DHI’s EVA tool feature, to investigate the extremity and return frequency of singular extremes, and then furthered by a joint probability analysis. Where the dependence between the variables is explored and potential return frequencies of extremity in different return combinations calculated. A coupled MIKE-11-MIKE-SHE numerical model is then investigated, with calibration of the Manning Number taking place to simulate peak flow conditions. Scaled events based from the EVA return analysis are then produced and simulated, to assess variable dynamics and illustrate risk of flooding from hypothetical flood events. An alternative numerical coupling of a MIKE-11-MIKE-21-MIKE-FLOOD has also taken place. The Aim of this is to display alternative numerical options, while helping to emphasise uncertainty within modelling, techniques and relationships of variables. A climatic factor has also been emulated to highlight the relevant climatic change consequences and significance.

Three-dimensional (3D) crosshole electrical resistivity tomography (ERT) was used to monitor a pilot CO2 injection experiment at Vrøgum, western Denmark. The purpose was to evaluate the effectiveness of the ERT method for detection of small electrical conductivity (EC) changes during the first 2 days of CO2 injection in a shallow siliciclastic aquifer and to study the early-time behavior of a controlled small gaseous CO2 release. 45 kg of CO2 was injected over a 50-h period at 9.85 m depth. ERT data were collected using horizontal bipole-bipole (HBB) and vertical bipole-bipole (VBB) arrays. The combined HBB and VBB data sets were inverted using a difference inversion algorithm for cancellation of coherent noises and enhanced resolution of small changes. ERT detected the small bulk EC changes (<10%) from conductive dissolved CO2 and resistive gaseous CO2. The primary factors that control the migration of a CO2 plume consist of buoyancy of gaseous CO2, local heterogeneity, groundwater flow and external pressure exerted by the injector. The CO2 plume at the Vrøgum site migrated mostly upward due to buoyancy and it also skewed toward northeastern region by overcoming local groundwater flow. The conductive eastern part is more porous and becomes the preferential pathway for the CO2 plume, which was trapped within the slightly more porous glacial sand layer between 5 m and 10 m depths. The gaseous and dissolved CO2 plumes are collocated and grow in tandem for the first 24 h and their opposite effects resulted in a small bulk EC increase. After raising the injection rate from 10 g/min to 20 g/min at the 24-h mark, the CO2 plume grew quickly. The bulk EC changes from ERT agreed partially with water sample EC and GPR data. The apparent disagreement between high CO2 gas saturation and prevailing positive bulk EC changes may be caused by limited and variable ERT resolution, low ERT sensitivity to resistive anomalies and uncalibrated CO2 gas saturation. ERT data show a broad