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Integrated hydrological models are usually calibrated against observations of river discharge and piezometric head in groundwater aquifers. Calibration of such models against spatially distributed observations of river water level can potentially improve their reliability and predictive skill. However, traditional river gauging stations are normally spaced too far apart to capture spatial patterns in the water surface, while spaceborne observations have limited spatial and temporal resolution. UAVs (Unmanned Aerial Vehicles) can retrieve river water level measurements, providing: i) high spatial resolution; ii) spatially continuous profiles along or across the water body; iii) flexible timing of sampling. A semi-synthetic study was conducted to analyse the value of the new UAV-borne datatype for improving hydrological models, in particular estimates of GW (Groundwater)- SW (Surface Water) interaction. Mølleåen River (Denmark) and its catchment were simulated using an integrated hydrological model (MIKE 11-MIKE SHE). Calibration against distributed surface water levels using the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm demonstrated a significant improvement in estimating spatial patterns and time series of GW-SW interaction. After water level calibration, the sharpness of the estimates of GW-SW time series improves of ca. 50% and RMSE (Root Mean Square Error) decreases by ca. 75% compared to a model calibrated against discharge only.

This paper assesses how various sources of uncertainty propagate through the uncertainty cascade from emission scenarios through climate models and hydrological models to impacts, with a particular focus on groundwater aspects from a number of coordinated studies in Denmark. Our results are similar to those from surface water studies showing that climate model uncertainty dominates the results for projections of climate change impacts on streamflow and groundwater heads. However, we found uncertainties related to geological conceptualization and hydrological model discretization to be dominant for projections of well field capture zones, while the climate model uncertainty here is of minor importance. How to reduce the uncertainties on climate change impact projections related to groundwater is discussed, with an emphasis on the potential for reducing climate model biases through the use of fully coupled climate–hydrology models.Editor D. Koutsoyiannis; Associate editor not assigned

In this study we develop and test a calibration approach on a spatially distributed groundwater–surface water catchment model (MIKE SHE) coupled to a land surface model component with particular focus on the water and energy fluxes. The model is calibrated against time series of eddy flux measurements from three sites of different land surface type (agriculture, forest and meadow) and river discharge data from the 2500 km 2 Skjern River catchment in Denmark. The approach includes initial calibrations of three one-dimensional models representing the three land surface types using the flux measurements for calibration. This step provides initial values for the subsequent modelling and calibration at catchment scale. To test the validity of the approach, two additional catchment scale distributed simulations were performed with no calibration and only calibration of the one-dimensional models, respectively. In addition, a subsequent validation period was simulated. A mean energy closure imbalance of 20% was seen for the three sites. For the distributed simulations, the energy imbalance was accounted for by two energy balance closure hypotheses ascribing the error to either energy fluxes or net radiation. In general, the distributed calibration approach improved model results substantially compared to using default values (no calibration) or calibration of the one-dimensional models only. For the distributed model simulations, the assumption regarding the energy balance closure had a substantial impact on the parameter sensitivities and on the simulated discharge and energy balance. During calibration, the simulation with corrected energy fluxes showed better performance on discharge than the simulation with corrected net radiation whereas the reverse was true for the validation period. Regarding energy fluxes, the simulation with corrected net radiation was superior in both the calibration and validation period.

Water Surface Elevation (WSE) is an important hydrometric observation, useful to calibrate hydrological models, predict floods, and assess climate change. However, the number of in-situ gauging stations is in decline worldwide. Satellite altimetry, including the recently launched satellite missions (e.g. the radar altimetry missions Cryosat 2, Jason 3, Sentinel 3A/B and the LIDAR mission ICESat-2), can determine WSE only in rivers which are more than ca. 100 m wide. WSE measurements in small streams currently remain limited to the few existing in-situ stations or to time-consuming in-situ surveys. Unmanned Aerial Systems (UAS) can acquire real-time WSE observations during periods of hydrological interest (but with flight limitations in extreme weather conditions), within short survey times and with automatic or semi-automatic flight operations. UAS-borne photogrammetry is a well-known technique that can estimate land elevation with an accuracy as high as a few cm, similarly UAS-borne LIDAR can estimate land elevation but without requiring Ground Control Points (GCPs). However, both techniques face limitations in estimating WSE: water transparency and lack of stable visual key points on the Water Surface (WS) complicate the UAS-borne photogrammetric estimates of WSE, while the LIDAR reflection from the water surface is generally not strong enough to be captured by most of the UAS-borne LIDAR systems currently available on the market. Thus, LIDAR and photogrammetry generally require extraction of the elevation of the “water-edge” points, i.e. points at the interface between land and water, for identifying the WSE. We demonstrate highly accurate WSE observations with a new radar altimetry solution, which comprises a 77 GHz radar chip with full waveform analysis and an accurate dual frequency differential Global Navigation Satellite System (GNSS) system. The radar altimetry solution shows the lowest standard deviation (σ) and RMSE on WSE estimates, ca. 1.5 cm and ca. 3 cm respectively, whilst photogrammetry and LIDAR show a σ and an RMSE at decimetre level. Radar altimetry also requires a significantly shorter survey and processing time compared to LIDAR and especially to photogrammetry.

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

In recent years research on the coupling of existing regional climate models and hydrology/land surface models has emerged. A major challenge in this emerging research field is the computational interaction between the models. In this study we present results from a full two-way coupling of the HIRHAM regional climate model over a 4000 km x 2800 km domain in 11 km resolution and the combined MIKE SHE-SWET hydrology and land surface models over the 2500 km2 Skjern river catchment. A total of 26 one-year runs were performed to assess the influence of the data transfer interval (DTI) between the two models and the internal HIRHAM model variability of ten variables. In general, the coupled model simulations exhibit less accurate performance than the uncoupled simulations which is to be expected as both models prior to this study have been individually refined or calibrated to reproduce observations. Four of six output variables from HIRHAM, precipitation, relative humidity, wind speed and air temperature, showed statistically significant improvements in RMSE with a reduced DTI as evaluated in the range of 12–120 min. For these four variables the perturbation induced HIRHAM variability was shown to correspond to 47% of the RMSE improvement when using a DTI of 120 min compared to a DTI of 12 min and the variability resulted in large ranges in simulated precipitation. Also, the DTI was shown to substantially affect computation time. The MIKE SHE energy flux and discharge output variables experienced little impact from the DTI.

Two-dimensional laboratory investigations of flow and transport in a fractured permeable medium are presented. Matrix blocks of a manufactured consolidated permeable medium were arranged together to create fractures in the spaces between the blocks. Experiments examined flow and transport in four different configurations: (1) matrix only, (2) and (3) matrix blocks containing single fractures of different mean apertures, and (4) a brickwork pattern setup simulating a tortuous multiple fracture network. The observed partitioning of flow and solute concentrations suggested mass exchange between the fractures and the matrix was occurring. An analysis of the experimental results using a discrete fracture model and a range of constant aperture models showed that this approach did not capture the correct flow mechanisms. Subsequent simulations including spatial variations of the fracture aperture were better able to describe the experimental observations and to show that these variations cause mass exchange between the fracture and matrix.

An experimental study of the migration of denser-than-water nonaqueous-phase organic contaminants through heterogeneous porous media was carried out. The purpose of the study was to observe the flow and record the migration of the contaminant to gain a fundamental insight into the way aquifer heterogeneities influence the movement and subsequent distribution of immiscible contaminants after a spill. In addition, the experiments were designed to gather quantitative data to validate multiphase flow models. The experimental results demonstrate the importance of layering in the soil in determining the flow and entrapment behavior of dense nonaqueous-phase contaminants. The findings are of use for model conceptualization and developing field characterization strategies in aquifer remediation.

Roskilde University (Denmark) hosted a November 2015 workshop, Environmental Risk—Assessing and Managing Multiple Risks in a Changing World. This Focus article presents the consensus recommendations of 30 attendees from 9 countries regarding implementation of a common currency (ecosystem services) for holistic environmental risk assessment and management; improvements to risk assessment and management in a complex, human-modified, and changing world; appropriate development of protection goals in a 2-stage process; dealing with societal issues; risk-management information needs; conducting risk assessment of risk management; and development of adaptive and flexible regulatory systems. The authors encourage both cross-disciplinary and interdisciplinary approaches to address their 10 recommendations: 1) adopt ecosystem services as a common currency for risk assessment and management; 2) consider cumulative stressors (chemical and nonchemical) and determine which dominate to best manage and restore ecosystem services; 3) fully integrate risk managers and communities of interest into the risk-assessment process; 4) fully integrate risk assessors and communities of interest into the risk-management process; 5) consider socioeconomics and increased transparency in both risk assessment and risk management; 6) recognize the ethical rights of humans and ecosystems to an adequate level of protection; 7) determine relevant reference conditions and the proper ecological context for assessments in human-modified systems; 8) assess risks and benefits to humans and the ecosystem and consider unintended consequences of management actions; 9) avoid excessive conservatism or possible underprotection resulting from sole reliance on binary, numerical benchmarks; and 10) develop adaptive risk-management and regulatory goals based on ranges of uncertainty. © 2016 SETAC Funding: Roskilde University and their Environmental Risk Research Initiative. S. Loureiro acknowledges the financial support of CESAM (UID/AMB/50017), to FCT/MEC through national funds, and the cofunding by FEDER (POCI-01-0145-FEDER-007638), within the PT2020 Partnership Agreement and Compete 2020.