Mobilisation or dilution? Nitrate response of karst springs to high rainfall events

peer-reviewedNitrate (NO3−) contamination of groundwater associated with agronomic activity is of major concern in many countries. Where agriculture, thin free draining soils and karst aquifers coincide, groundwater is highly vulnerable to nitrate contamination. As residence times and denitrification potential in such systems are typically low, nitrate can discharge to surface waters unabated. However, such systems also react quickest to agricultural management changes that aim to improve water quality. In response to storm events, nitrate concentrations can alter significantly, i.e. rapidly decreasing or increasing concentrations. The current study examines the response of a specific karst spring situated on a grassland farm in South Ireland to rainfall events utilising high-resolution nitrate and discharge data together with on-farm borehole groundwater fluctuation data. Specifically, the objectives of the study are to formulate a scientific hypothesis of possible scenarios relating to nitrate responses during storm events, and to verify this hypothesis using additional case studies from the literature. This elucidates the controlling key factors that lead to mobilisation and/or dilution of nitrate concentrations during storm events. These were land use, hydrological condition and karstification, which in combination can lead to differential responses of mobilised and/or diluted nitrate concentrations. Furthermore, the results indicate that nitrate response in karst is strongly dependent on nutrient source, whether mobilisation and/or dilution occur and on the pathway taken. This will have consequences for the delivery of nitrate to a surface water receptor. The current study improves our understanding of nitrate responses in karst systems and therefore can guide environmental modellers, policy makers and drinking water managers with respect to the regulations of the European Union (EU) Water Framework Directive (WFD). In future, more research should focus on the high-resolution monitoring of karst aquifers to capture the high variability of hydrochemical processes, which occur at time intervals of hours to days.Teagasc Walsh Fellowship Programm

A model ensemble generator to explore structural uncertainty in karst systems with unmapped conduits

Karst aquifers are characterized by high-conductivity conduits embedded in a low-conductivity fractured matrix, resulting in extreme heterogeneity and variable groundwater flow behavior. The conduit network controls groundwater flow, but is often unmapped, making it difficult to apply numerical models to predict system behavior. This paper presents a multi-model ensemble method to represent structural and conceptual uncertainty inherent in simulation of systems with limited spatial information, and to guide data collection. The study tests the new method by applying it to a well-mapped, geologically complex long-term study site: the Gottesacker alpine karst system (Austria/Germany). The ensemble generation process, linking existing tools, consists of three steps: creating 3D geologic models using GemPy (a Python package), generating multiple conduit networks constrained by the geology using the Stochastic Karst Simulator (a MATLAB script), and, finally, running multiple flow simulations through each network using the Storm Water Management Model (C-based software) to reject nonbehavioral models based on the fit of the simulated spring discharge to the observed discharge. This approach captures a diversity of plausible system configurations and behaviors using minimal initial data. The ensemble can then be used to explore the importance of hydraulic flow parameters, and to guide additional data collection. For the ensemble generated in this study, the network structure was more determinant of flow behavior than the hydraulic parameters, but multiple different structures yielded similar fits to the observed flow behavior. This suggests that while modeling multiple network structures is important, additional types of data are needed to discriminate between networks

The stochastic simulation of karst conduit network structure using anisotropic fast marching, and its application to a geologically complex alpine karst system

Anisotropic fast-marching algorithms are computationally efficient tools for generating realistic maps of karst conduit networks, constrained by both the spatial extent and the orientation of karstifiable geologic units. Existing models to generate conduit network maps are limited either by high computational requirements (for chemistry-based models) or by their inability to incorporate the effects of elevation and orientation gradients (for isotropic fast-marching models). The new anisotropic fast-marching approach described here provides a significant improvement, though it imitates rather than reproduces actual speleogenetic processes. It can rapidly generate a stochastic ensemble of plausible networks from basic geologic information, which can also be used as input to karst-appropriate flow models. This paper introduces an open-source, easy-to-use implementation through the Python package pyKasso, then describes its application to a well-mapped geologically complex long-term study site: the Gottesacker alpine karst system (Germany/Austria). Groundwater flow in this system is exceptionally well understood from speleological investigations and tracer tests. Conduit formation primarily occurs at the base of the karst aquifer, following plunging synclines. Although previous attempts to reproduce the conduit network at this site yielded implausible network maps, pyKasso quickly generated networks faithful to the known conduit system. However, the model was only able to generate these realistic networks when the inlet-outlet connections of the system were correctly assigned, highlighting the importance of pairing modeling efforts with field tracer tests. Therefore, a model ensemble method is also presented, to optimize field efforts by identifying the most informative tracer tests to perform

Intergenerational family caregiving in welfare policy context

Definition Intergenerational family caregiving refers to exchanges up and down family lines aimed at nurturing the needs of others. Caregiving is more than a task; it involves emotional and relationship work

Timing preferences for women's family life transitions: Intergenerational transmission among migrants and Dutch

This study examines the transmission of preferences regarding the timing of family-life transitions of women among migrant and native Dutch families. We study how and to what extent parental preferences, migrant origin, and family characteristics affect the child’s timing preferences. We use parent and child data (N ¼ 1,290) from the Netherlands Kinship Panel Study (2002, 2003) and the Social Position and Provisions Ethnic Minorities Survey (2002). Regression analyses reveal that parental timing preferences regarding family-life transitions are strongly associated with the timing preferences of their children. Analyses also show that these preferences strongly vary by migrant origin, educational level, and religious involvement.The process of intergenerational transmission, however, is found to be very similar among migrants and Dutch