The complex conductivity of soils remains poorly known despite the growing importance of this method in hydrogeophysics. In order to fill this gap of knowledge, we investigate the complex conductivity of 71 soils samples (including four peat samples) and one clean sand in the frequency range 0.1 Hz to 45 kHz. The soil samples are saturated with six different NaCl brines with conductivities (0.031, 0.53, 1.15, 5.7, 14.7, and 22 S m−1, NaCl, 25°C) in order to determine their intrinsic formation factor and surface conductivity. This data set is used to test the predictions of the dynamic Stern polarization model of porous media in terms of relationship between the quadrature conductivity and the surface conductivity. We also investigate the relationship between the normalized chargeability (the difference of in‐phase conductivity between two frequencies) and the quadrature conductivity at the geometric mean frequency. This data set confirms the relationships between the surface conductivity, the quadrature conductivity, and the normalized chargeability. The normalized chargeability depends linearly on the cation exchange capacity and specific surface area while the chargeability shows no dependence on these parameters. These new data and the dynamic Stern layer polarization model are observed to be mutually consistent. Traditionally, in hydrogeophysics, surface conductivity is neglected in the analysis of resistivity data. The relationships we have developed can be used in field conditions to avoid neglecting surface conductivity in the interpretation of DC resistivity tomograms. We also investigate the effects of temperature and saturation and, here again, the dynamic Stern layer predictions and the experimental observations are mutually consistent.

Uncertainties in the rate and magnitude of sea-level rise (SLR) complicate decision making on coastal adaptation. Large uncertainty arises from potential ice mass-loss from Antarctica that could rapidly increase SLR in the second half of this century. The implications of SLR may be existential for a lowlying country like the Netherlands and warrant exploration of high-impact low-likelihood scenarios. To deal with uncertain SLR, the Netherlands has adopted an adaptive pathways plan. This paper analyzes the implications of storylines leading to extreme SLR for the current adaptive plan in the Netherlands, focusing on flood risk, fresh water resources, and coastline management. It further discusses implications for coastal adaptation in low-lying coastal zones considering timescales of adaptation including the decisions lifetime and lead-in time for preparation and implementation. We find that as sea levels rise faster and higher, sand nourishment volumes to maintain the Dutch coast may need to be up to 20 times larger than to date in 2100, storm surge barriers will need to close at increasing frequency until closed permanently, and intensified saltwater intrusion will reduce freshwater availability while the demand is rising. The expected lifetime of investments will reduce drastically. Consequently, step-wise adaptation needs to occur at an increasing frequency or with larger increments while there is still large SLR uncertainty with the risk of under-or overinvesting. Anticipating deeply uncertain, high SLR scenarios helps to enable timely adaptation and to appreciate the value of emission reduction and monitoring of the Antarctica contribution to SLR.

No abstract

Abstract. Coastal groundwater reserves often reflect a complex evolution of marine transgressions and regressions, and are only rarely in equilibrium with current boundary conditions. Understanding and managing the present-day distribution and future development of these reserves and their hydrochemical characteristics therefore requires insight into their complex evolution history. In this paper, we construct a paleo-hydrogeological model, together with groundwater age and origin calculations, to simulate, study and evaluate the evolution of groundwater salinity in the coastal area of the Netherlands throughout the last 8.5 kyr of the Holocene. While intended as a conceptual tool, confidence in our model results is warranted by a good correspondence with a hydrochemical characterization of groundwater origin. Throughout the modeled period, coastal groundwater distribution never reached equilibrium with contemporaneous boundary conditions. This result highlights the importance of historically changing boundary conditions in shaping the present-day distribution of groundwater and its chemical composition. As such, it acts as a warning against the common use of a steady-state situation given present-day boundary conditions to initialize groundwater transport modeling in complex coastal aquifers or, more general, against explaining existing groundwater composition patterns from the currently existing flow situation. The importance of historical boundary conditions not only holds true for the effects of the large-scale marine transgression around 5 kyr BC that thoroughly reworked groundwater composition, but also for the more local effects of a temporary gaining river system still recognizable today. Model results further attest to the impact of groundwater density differences on coastal groundwater flow on millennial timescales and highlight their importance in shaping today's groundwater salinity distribution. We found free convection to drive large-scale fingered infiltration of seawater to depths of 200 m within decades after a marine transgression, displacing the originally present groundwater upwards. Subsequent infiltration of fresh meteoric water was, in contrast, hampered by the existing density gradient. We observed discontinuous aquitards to exert a significant control on infiltration patterns and the resulting evolution of groundwater salinity. Finally, adding to a long-term scientific debate on the origins of groundwater salinity in Dutch coastal aquifers, our modeling results suggest a more significant role of pre-Holocene groundwater in the present-day groundwater salinity distribution in the Netherlands than previously recognized. Though conceptual, comprehensively modeling the Holocene evolution of groundwater salinity, age and origin offered a unique view on the complex processes shaping groundwater in coastal aquifers over millennial timescales.

[1] End-member mixing models have been widely used to separate the different components of a hydrograph, but their effectiveness suffers from uncertainty in both the identification of end-members and spatiotemporal variation in end-member concentrations. In this paper, we outline a procedure, based on the generalized likelihood uncertainty estimation (GLUE) framework, to more inclusively evaluate uncertainty in mixing models than existing approaches. We apply this procedure, referred to as G-EMMA, to a yearlong chemical data set from the heavily impacted agricultural Lissertocht catchment, Netherlands, and compare its results to the ''traditional'' end-member mixing analysis (EMMA). While the traditional approach appears unable to adequately deal with the large spatial variation in one of the end-members, the G-EMMA procedure successfully identified, with varying uncertainty, contributions of five different end-members to the stream. Our results suggest that the concentration distribution of ''effective'' end-members, that is, the flux-weighted input of an end-member to the stream, can differ markedly from that inferred from sampling of water stored in the catchment. Results also show that the uncertainty arising from identifying the correct end-members may alter calculated endmember contributions by up to 30%, stressing the importance of including the identification of end-members in the uncertainty assessment.Citation: Delsman, J. R., G. H. P. Oude Essink, K. J. Beven, and P. J. Stuyfzand (2013), Uncertainty estimation of end-member mixing using generalized likelihood uncertainty estimation (GLUE), applied in a lowland catchment, Water Resour. Res., 49,[4792][4793][4794][4795][4796][4797][4798][4799][4800][4801][4802][4803][4804][4805][4806]

Seawater intrusion has often resulted in scarce fresh groundwater resources in coastal lowlands. Careful management is essential to avoid the overexploitation of these vulnerable fresh groundwater resources, requiring detailed information on their spatial occurrence. Airborne electromagnetics (EM) has proved a valuable tool for efficient mapping of ground conductivity, as a proxy for fresh groundwater resources. Stakeholders are, however, interested in groundwater salinity, necessitating a translation of ground conductivity to groundwater salinity. This paper presents a methodology to construct a high-resolution (50 × 50 × 0.5 m 3 ) 3D voxel model of groundwater chloride concentration probability, based on a large-scale (1800 km 2 , 9640 flight line kilometres) airborne EM survey in the province of Zeeland, the Netherlands. Groundwater chloride concentration was obtained by combining pedotransfer functions with detailed lithological information. The methodology includes a Monte Carlo based forward uncertainty propagation approach to quantify the inherent uncertainty in the different steps. Validation showed good correspondence both with available groundwater chloride analyses, and with ground-based hydrogeophysical measurements. Our results show the limited occurrence of fresh groundwater in Zeeland, as 75% of the area lacks fresh groundwater within 15 m below ground surface. Fresh groundwater is mainly limited to the dune area and sandy creek ridges. In addition, significant fresh groundwater resources were shown to exist below saline groundwater, where infiltration of seawater during marine transgressions was hindered by the presence of clayey aquitards. The considerable uncertainty in our results highlights the importance of applying uncertainty analysis in airborne EM surveys. Uncertainty in our results mainly originated from the inversion and the 3D interpolation, and was largest at transition zones between fresh and saline groundwater. Reporting groundwater salinity instead of ground conductivity facilitated the rapid uptake of our results by relevant stakeholders, thereby supporting the necessary management of fresh groundwater resources in the region.

The use of additional types of observational data has often been suggested to alleviate the ill-posedness inherent to parameter estimation of groundwater models and constrain model uncertainty. Disinformation in observational data caused by errors in either the observations or the chosen model structure may, however, confound the value of adding observational data in model conditioning. This paper uses the global generalized likelihood uncertainty estimation methodology to investigate the value of different observational data types (heads, fluxes, salinity, and temperature) in conditioning a groundwater flow and transport model of an extensively monitored field site in the Netherlands. We compared model conditioning using the real observations to a synthetic model experiment, to demonstrate the possible influence of disinformation in observational data in model conditioning. Results showed that the value of different conditioning targets was less evident when conditioning to real measurements than in a measurement error-only synthetic model experiment. While in the synthetic experiment, all conditioning targets clearly improved model outcomes, minor improvements or even worsening of model outcomes was observed for the real measurements. This result was caused by errors in both the model structure and the observations, resulting in disinformation in the observational data. The observed impact of disinformation in the observational data reiterates the necessity of thorough data validation and the need for accounting for both model structural and observational errors in model conditioning. It further suggests caution when translating results of synthetic modeling examples to real-world applications. Still, applying diverse conditioning data types was found to be essential to constrain uncertainty, especially in the transport of solutes in the model

No abstract