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Schirmer, Mario
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Schirmer, Mario
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- PublicationAccès libreQuasi-Online Groundwater Model Optimization Under Constraints of Geological Consistency Based on Iterative Importance Sampling(2020-4)
; ; - PublicationAccès libreTopsoil structure stability in a restored floodplain: Impacts of fluctuatingwater levels, soil parameters and ecosystem engineers(2017-6)
; ; ; ; Ecosystem services provided byfloodplains are strongly controlled by the structural stability of soils. The developmentof a stable structure infloodplain soils is affected by a complex and poorly understood interplay of hydrological,physico-chemical and biological processes. This paper aims at analysing relations betweenfluctuating groundwaterlevels, soil physico-chemical and biological parameters on soil structure stability in a restoredfloodplain. Water levelfluctuations in the soil are modelled using a numerical surface-water–groundwaterflow model and correlated tosoil physico-chemical parameters and abundances of plants and earthworms. Causal relations and multiple interactionsbetween the investigated parameters are tested through structural equation modelling (SEM). Fluctuating water levelsin the soil did not directly affect the topsoil structure stability, but indirectly through affecting plant roots and soil pa-rameters that in turn determine topsoil structure stability. These relations remain significant for mean annual days ofcomplete and partial (N25%) water saturation. Ecosystem functioning of a restoredfloodplain might already be affectedby thefluctuation of groundwater levels alone, and not only through completeflooding by surface water during afloodperiod. Surprisingly, abundances of earthworms did notshow any relation to other variables in the SEM. Thesefindingsemphasise that earthworms have efficiently adapted to periodic stress and harsh environmental conditions. Variabilityof the topsoil structure stability is thus stronger driven by the influence offluctuating water levels on plants than by theabundance of earthworms. This knowledge about the functional network of soil engineering organisms, soil parametersandfluctuating water levels and how they affect soil structural stability is of fundamental importance to define man-agement strategies of near-natural or restoredfloodplains in the future. - PublicationAccès libreAn integrated spatial snap-shot monitoring method for identifying seasonal changes and spatial changes in surface water quality(2016-8)
; Integrated catchment-scale management approaches in large catchments are often hindered due to the poor understanding of the spatially and seasonally variable pathways of pollutants. High-frequency monitoring of water quality at random locations in a catchment is resource intensive and challenging. A simplified catchment-scale monitoring approach is developed in this study, for the preliminary identification of water quality changes – Integrated spatial snap-shot monitoring (ISSM). This multi-parameter monitoring approach is applied using the isotopes of water (δ18O-H2O and δD) and nitrate (δ15N-NO3− and δ18O-NO3−) together with the fluxes of nitrate and other solutes, which are used as chemical markers. This method involves selection of few sampling stations, which are identified as the hotspots of water quality changes within the catchment. The study was conducted in the peri-alpine Thur catchment in Switzerland, with two snap-shot campaigns (representative of two widely varying hydrological conditions), in summer 2012 (low flow) and spring 2013 (high flow). Significant spatial (varying with elevation) and seasonal changes in the sources of water were observed between the two seasons. A spatial variation of the sources of nitrate and the solute loads was observed, in tandem with the land use changes in the Thur catchment. There is a seasonal shift in the sources of nitrate, it varies from a strong treated waste water signature during the low flow season to a mixture of other sources (like soil nitrogen derived from agriculture), in the high flow season. This demonstrates the influence of other sources that override the influence of waste water treatment plants (WWTPs) during high flow in the Thur River and its tributaries. This method is expected to be a cost-effective alternative, providing snap-shots, that can help in the preliminary identification of the pathways of solutes and their seasonal/spatial changes in catchments. - PublicationAccès librePerchloroethene source delineation using carbon-chlorine isotopic analysis: field investigations of isotopic signature variability / Perchlorethen-Quellendifferenzierung mittels Kohlenstoff-Chlor-(2015-12)
; ; - PublicationAccès libre
- PublicationAccès libreNew Methods to Estimate 2D Water Level Distributions of Dynamic Rivers(2013-1-10)
; - PublicationAccès libreAssessing the effect of different river water level interpolation schemes on modeled groundwater residence times
; Obtaining a quantitative understanding of river–groundwater interactions is of high practical relevance, for instance within the context of riverbank filtration and river restoration. Modeling interactions between river and groundwater requires knowledge of the river’s spatiotemporal water level distribution. The dynamic nature of riverbed morphology in restored river reaches might result in complex river water level distributions, including disconnected river branches, nonlinear longitudinal water level profiles and morphologically induced lateral water level gradients. Recently, two new methods were proposed to accurately and efficiently capture 2D water level distributions of dynamic rivers. In this study, we assessed the predictive capability of these methods with respect to simulated groundwater residence times. Both methods were used to generate surface water level distributions of a 1.2 km long partly restored river reach of the Thur River in northeastern Switzerland. We then assigned these water level distributions as boundary conditions to a 3D steady-state groundwater flow and transport model. When applying either of the new methods, the calibration-constrained groundwater flow field accurately predicted the spatial distribution of groundwater residence times; deviations were within a range of 30% when compared to residence times obtained using a reference method. We further tested the sensitivity of the simulated groundwater residence times to a simplified river water level distribution. The negligence of lateral river water level gradients of 20–30 cm on a length of 200 m caused errors of 40–80% in the calibration-constrained groundwater residence time distribution compared to results that included lateral water level gradients. The additional assumption of a linear water level distribution in longitudinal river direction led to deviations from the complete river water level distribution of up to 50 cm, which caused wide-spread errors in simulated groundwater residence times of 200–500%. For an accurate simulation of groundwater residence times, it is therefore imperative that the longitudinal water level distribution is correctly captured and described. Based on the confirmed predictive capability of the new methods to estimate 2D river water level distributions, we can recommend their application to future studies that model dynamic river–groundwater systems. - PublicationAccès libreNew Methods to Estimate 2D Water Level Distributions of Dynamic Rivers
; River restoration measures are becoming increasingly popular and are leading to dynamic river bed morphologies that in turn result in complex water level distributions in a river. Disconnected river branches, nonlinear longitudinal water level profiles and morphologically induced lateral water level gradients can evolve rapidly. The modeling of such river-groundwater systems is of high practical relevance in order to assess the impact of restoration measures on the exchange flux between a river and groundwater or on the residence times between a river and a pumping well. However, the model input includes a proper definition of the river boundary condition, which requires a detailed spatial and temporal river water level distribution. In this study, we present two new methods to estimate river water level distributions that are based directly on measured data. Comparing generated time series of water levels with those obtained by a hydraulic model as a reference, the new methods proved to offer an accurate and faster alternative with a simpler implementation