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Highlights
• Germany plans more long-distances water transfers to secure drinking water supply.
• Long-distance water transfers can unfold lock-ins that limit adaptive water governance.
• Our interdisciplinary case study shows how lock-ins emerge over different spaces and times.
• Commercialisation of water but also local protests contributed to various lock-ins.
• We therefore call for context-specific assessments of potentials and risks of LDWT.
Abstract
Germany plans to expand water transfers over long distances in the light of numerous and pressing challenges for drinking water supply. Research on inter- and intrabasin water transfers warns, however, that major investments in large-scale infrastructure systems accompanied by institutional logics and political interests often lead to a so-called lock-in. As a consequence, long-distance water transfers can limit the potential for adaptive water governance in the involved supply areas over decades with negative impacts for people and the environment. By using a case study in Germany as an example, we researched when, where and how such lock-ins around long-distance water transfers emerge. In the infrastructural development of the Elbaue-Ostharz transfer system we found various lock-ins that overlap in space and time. Some are located at the centre others at the margins of the infrastructure and commercialization of the water sector as well as hydraulic and hygienic concerns interlock with local protests in a way that the expansion of the long-distance water transfer infrastructure is presented continuously as imperative. Our findings contribute to a relational understanding of lock-ins of long-distance water transfers as contingent and diverse processes. Given the widespread occurrence of lock-ins, we argue for a context-specific assessment of potentials and risks of long-distance water transfers in times of multiple crises.
Tree water relations of mature oaks in southwest Germany under extreme drought stress in summer 2018
(2021)
Mature oak stands of different tree height at four sandy valley river sites (Quercus robur) and one south-exposed schist slope (Qu. petraea) in the middle Rhine and lower Main valley were studied from early summer 2017 (normal wet year) until the end of 2018 (extremely hot and dry year). Tree water relations (ΨPD, RWC, sap flow rates) were monitored together with soil water relations, LAI and leaf chl content. In two sandy sites with presumed continuous capillary water access from the groundwater aquifer, sap flow rates of the large trees (30 m) and estimated canopy conductance decreased to about 50% of the maximum value in the course of summer 2018, but recovered in autumn. At two other sites, with smaller trees (14–24 m) and presumed interrupted capillary water access during mid-summer 2018, sap flow rates and canopy conductance broke down completely and trees shed a large proportion of leaves in summer. In one of these sites, ΨPD decreased (reversibly) to -4 MPa, one of the lowest values reported in the literature for central Europe, and tree damage resulted not only in extreme leaf shedding, but also in susceptibility to uprooting (in 2 out of 5 measured trees) by thunderstorm gusts in autumn 2018. At the schist slope site, where oaks reached the lowest height and stand density of all sites, sap flow rates remained similar to the values found at the presumed capillary-water supplied sandy sites, indicating access to rock fissure water even at the peak of the drought period. Our findings corroborate the prediction from vegetation modelling that several Qu. robur stands in the Rhine-Main valleys will be prone to severe forest dieback in the forthcoming decades.
We investigate the applicability of the well-known multilevel Monte Carlo (MLMC) method to the class of density-driven flow problems, in particular the problem of salinisation of coastal aquifers. As a test case, we solve the uncertain Henry saltwater intrusion problem. Unknown porosity, permeability and recharge parameters are modelled by using random fields. The classical deterministic Henry problem is non-linear and time-dependent, and can easily take several hours of computing time. Uncertain settings require the solution of multiple realisations of the deterministic problem, and the total computational cost increases drastically. Instead of computing of hundreds random realisations, typically the mean value and the variance are computed. The standard methods such as the Monte Carlo or surrogate-based methods are a good choice, but they compute all stochastic realisations on the same, often, very fine mesh. They also do not balance the stochastic and discretisation errors. These facts motivated us to apply the MLMC method. We demonstrate that by solving the Henry problem on multi-level spatial and temporal meshes, the MLMC method reduces the overall computational and storage costs. To reduce the computing cost further, parallelization is performed in both physical and stochastic spaces. To solve each deterministic scenario, we run the parallel multigrid solver ug4 in a black-box fashion.