Evaluation of CADISSE a regional storage capacity model

In this paper the validity of CADISSE, a regional storage capacity model developed to assess the sensitivity of catchment hydrology to climate variability, is examined. In CADISSE, catchment discharge sensitivity is expressed as the ratio of present maximum reservoir storage to catchment storage capacity. Present maximum storage should be interpreted as the maximum amount of water stored in a catchment at present. Catchment storage capacity is defined as the absolute amount of water that can be stored, given the catchment's dimensions and lithological characteristics. With CADISSE, catchment sensitivity can be quantified regionally using limited discharge data and topographic information. Furthermore, storage capacities can be assessed. CADISSE was successfully applied to 15 catchments in the Upper Loire Basin. However, successful application does not necessarily mean that the variables (present maximum storage and storage capacity) represent real world values. Therefore, a two‐step evaluation procedure is presented in this paper. To evaluate CADISSE, (1) the accurate assessment of regionally determined storage capacity, and (2) the importance of present maximum storage for catchment discharge sensitivity is examined with a daily discharge model by comparing observed and simulated catchment storage behaviour for dry and wet periods. The evaluation was carried out using the probability distributed daily discharge model, PDM, and a weather generator for three catchments with different storage capacities and storage behaviour. Results indicate that catchment storage capacity can be correctly quantified with CADISSE and that differences in storage behaviour are indeed important for analyses of catchment sensitivity. Hence, CADISSE has great potential as it can be used to identify flood‐ and drought‐prone catchments under present and future conditions. Copyright © 1999 John Wiley & Sons, Ltd.     

Extreme storm surge modelling in the North Sea

This study shows that storm surge model performance in the North Sea is mostly unaffected by the application of temporal variations of surface drag due to changes in sea state provided the choice of a suitable constant Charnock parameter in the sea-state-independent case. Including essential meteorological features on smaller scales and minimising interpolation errors by increasing forcing data resolution are shown to be more important for the improvement of model performance particularly at the high tail of the probability distribution. This is found in a modelling study using WAQUA/DCSMv5 by evaluating the influence of a realistic air-sea momentum transfer parameterization and comparing it to the influence of changes in the spatial and temporal resolution of the applied forcing fields in an effort to support the improvement of impact and climate analysis studies. Particular attention is given to the representation of extreme water levels over the past decades based on the example of the Netherlands. For this, WAQUA/DCSMv5 is forced with ERA-Interim reanalysis data. Model results are obtained from a set of different forcing fields, which either (i) include a wave-state-dependent Charnock parameter or (ii) apply a constant Charnock parameter (α _{C h} =?0.032) tuned for young sea states in the North Sea, but differ in their spatial and/or temporal resolution. Increasing forcing field resolution from roughly 79 to 12 km through dynamically downscaling can reduce the modelled low bias, depending on coastal station, by up to 0.25 m for the modelled extreme water levels with a 1-year return period and between 0.1 m and 0.5 m for extreme surge heights.     

Quantifying relations between surface runoff and aridity after wildfire

Post‐wildfire runoff and erosion are major concerns in fire‐prone landscapes around the world, but these hydro‐geomorphic responses have been found to be highly variable and difficult to predict. Some variations have been observed to be associated with landscape aridity, which in turn can influence soil hydraulic properties. However, to date there has been no attempt to systematically evaluate the apparent relations between aridity and post‐wildfire runoff. In this study, five sites in a wildfire burnt area were instrumented with rainfall‐runoff plots across an aridity index (AI) gradient. Surface runoff and effective rainfall were measured over 10 months to allow investigation of short‐ (peak runoff) and longer‐term (runoff ratio) runoff characteristics over the recovery period. The results show a systematic and strong relation between aridity and post‐wildfire runoff. The average runoff ratio at the driest AI site (33.6%) was two orders of magnitude higher than at the wettest AI site (0.3%). Peak runoff also increased with AI, with up to a thousand‐fold difference observed during one event between the driest and wettest sites. The relation between AI, peak 15‐min runoff (Q₁₅) and peak 15‐min rainfall intensity (I₁₅) (both in mm h^‐1) could be quantified by the equation: Q₁₅ = 0.1086I₁₅ × AI ^2.691 (0.65<AI<1.80, 0<I₁₅<45) (adjusted r² = 0.84). The runoff ratios remained higher at drier AI sites (AI 1.24 and 1.80) throughout the monitoring period, suggesting higher AI also lengthens the window of disturbance after wildfire. The strong quantifiable link which this study has determined between AI and post‐wildfire surface runoff could greatly improve our capacity to predict the magnitude and location of hydro‐geomorphic processes such as flash floods and debris flows following wildfire, and may help explain aridity‐related patterns of soil properties in complex upland landscapes. Copyright © 2018 John Wiley & Sons, Ltd.     

Why and when it is useful to publish and share inconclusive results and failures: reply to “Reporting negative results to stimulate experimental hydrology”*

We thank van Emmerik et al. for their discussion of our opinion paper. We do not fully agree that publication of negative results will be very effective in promoting experimental hydrology. Instead, we think that experimental hydrology is considered to be more risky than modelling studies because of difficulties in publishing inconclusive results and the potential for failure.     

Analysis of nonlinear associations between prenatal methylmercury exposure from fish consumption and neurodevelopmental outcomes in the Seychelles Main Cohort at 17 years

The Seychelles Child Development Study has been examining the relationship between prenatal methylmercury (MeHg) exposure from consuming fish during pregnancy and child development. This study re-analyzes seven outcomes in the 17 year Main Cohort data to determine if there are nonlinear or non-homogeneous (subgroup) associations that were not identified in the linear analysis. We adopted two statistical approaches. First, we carried out an additive nonlinear analysis assuming homogeneous prenatal MeHg-outcome relationships to explore overall associations. Second, we applied the regression tree to the Woodcock–Johnson Calculation subtest (it was significantly associated in earlier analyses) and identified 4 clusters based on covariates. Then we used additive models to assess the prenatal MeHg association in each of the four clusters for all seven outcomes. This approach assumes nonlinear associations in each cluster and non-homogeneous associations between clusters. The additive nonlinear analysis yielded prenatal MeHg curves similar to the linear analysis. For the regression tree analysis, the curves relating prenatal MeHg to outcomes between the 4 clusters differed and some crossed at higher prenatal MeHg levels, suggesting non-homogeneity in the upper range of exposure. Additionally, some of the curves suggested a possible non-linear relationship within the range of exposure we studied. This non-linear analysis supports the findings from the linear analysis. It shows little evidence to support an adverse association of prenatal MeHg exposure through maternal consumption of fish contaminated with natural background levels. However, the tree analysis suggests that the prenatal exposure/outcome relationship may not be homogeneous across all individuals and that some subpopulations may have an adverse association in the upper range of the exposures studied. More robust data in the higher levels of exposure in this cohort are needed to confirm this finding.     

High-resolution optical dating of Late Holocene storm surge deposits – a showcase from Schokland (Noordoostpolder,the Netherlands)

Storm surges have a major impact on land use and human habitation in coastal regions. Our knowledge of this impact can be improved by correlating long-term historical storm records with sedimentary evidence of storm surges, but so far few studies have applied such an approach. Here we apply, for the first time, state-of-the-art optically stimulating luminescence (OSL) methods to obtain high-resolution age information on a sequence of Late Holocene storm surge deposits. By combining this chronological framework of storm surges with other reconstruction methods, we investigate the storm surge impact on the former island Schokland, located in a former inlet of the North Sea (central Netherlands).During the Late Holocene, Schokland transformed from a peat area that gradually inundated (~800 CE) via an island in a marginal marine environment (~1600 CE) to a land-locked island in the reclaimed Province of Flevoland (1942 CE). These transitions are recorded in the sediment archive of the island, consisting of silty clay with sandy intervals deposited during storm surges. A series of ten quartz OSL ages, obtained using best-practice methods to deal with incomplete resetting of the OSL signal and dose rate heterogeneity, reveal two periods of storm surge deposition, around 1600 CE and between 1742 and 1822 CE. Historical sources indicate that major storm surges hit Schokland during these periods. Laboratory analyses (thermogravimetry, grain-size, foraminifera, bivalves and ostracods) corroborates the existence of the two sets of storm surge deposits within the clay sequence. Our study sets a benchmark for obtaining robust depositional age constraints from storm surge sediments, and demonstrates the great potential of modern OSL methods to contribute to improved assessment of storm surge risk. © 2018 John Wiley & Sons, Ltd.     

Does Pumping Volume Affect the Concentration of Micropollutants in Groundwater Samples?

Information on concentrations of micropollutants (such as pharmaceuticals, pesticides, and industrial chemicals) in most highly dynamic riverbank filtration (RBF) systems is lacking, in contrast to data on standard chemical parameters. Sampling protocols have thus far been based on the stabilization of standard chemical parameters in relatively pristine environments. To determine whether groundwater samples for micropollutant analysis can be taken at a similar pumping volume as samples for testing standard chemical parameters in both environments, three groundwater monitoring wells in an RBF system were sampled at two points in time (after pumping of 3 well volumes and after pumping of 15 well volumes). Micropollutant concentrations were not significantly different between the two sampling points; therefore, appropriate samples can be drawn after pumping 3 well volumes. For a specific microbiological parameter (leucin incorporation), a statistically significant difference was found.