Abstract:Heat is recognized as a natural tracer to identify the exchange of water between the groundwater and surface water compartment. One-dimensional (1D) heat transport models have the ability to obtain quantitative estimates of vertical fluxes through the sediment matrix. Input to these models can come from temperatures observed in the surface water and in the bed material of rivers and lakes. The upper thermal boundary condition at the groundwater-surface water interface is affected by seasonal and diurnal temperature variations. We hypothesize that effects of these transient influences are negligible at certain times of the year, such that the vertical temperature distribution can be approximated to be at steady state. Temperature time series observed over a year in the surface water and at several depths below a river in Belgium and in sediments of an acid mine lake in Eastern Germany were simulated with a heat balance model implemented in FEMME and the water and energy model VS2DH to obtain seepage fluxes. Temperature variations throughout the year at all depths could be adequately reproduced with the transient models. Vertical temperature profiles at several measuring times during the year were also fitted with an analytical, steady-state solution for 1D heat transport and the obtained fluxes compared to the results from transient simulations. Fluxes obtained from the much simpler steady-state solution were compared well with the flux rates from transient simulations for moments between mid and late summer, as well as during the winter. During transitional seasons (fall and spring), the fluxes from the steady-state solution deviated significantly from the transient estimates with a tendency to underestimate at the beginning and to overestimate towards the end of those seasons. We conclude that fitting a simple analytical solution for 1D vertical heat transport to temperature data observed at particular well-selected times of the year can provide an inexpensive, simple method to obtain accurate point estimates of groundwater-surface water exchange in rivers and lakes.
Summary1. Macrophytes in running waters experience an often dynamic and harsh environment. To avoid breakage, plants have to reduce the experienced drag force. However, by reducing leaf area, photosynthetic production is less. Aquatic plants therefore have to find a balance between reducing drag and maintaining photosynthetic capacity. 2. In the experiments in this study, we assessed to what extent different morphological strategies (emergent vs. submerged) were able to minimize drag while maximizing leaf area. 3. From our measurements, it is clear that with increasing water velocities, emergent plant species have a drag value three to four times higher than submerged species. 4. To test the versatility of leaves, leaves were removed and their effect on drag and bending was investigated. Almost 60% of the drag is contributed by the leaves, and stems bend less when leaves are removed. 5. Because high submerged leaf area increases not only plant drag but also photosynthetic yield, a trade-off between both parameters was investigated in the function of stream velocity. Emerged species had a more favourable trade-off at low stream velocities. However, with increasing stream velocity, submerged species could reduce their drag more in comparison with blunt objects. Within these submerged species, a clear distinction was seen between those (Potamogeton natans) concentrating their leaf area on or just beneath the water surface (Stuckenia pectinata) and those with more or less evenly distributed biomass (Callitriche platycarpa and Ranunculus penicillatus). 6. These results indicate that aquatic plants with an emergent strategy are able to take better advantage of zones with reduced hydraulic forces than submerged plants. Additionally, this plant occurrence will be determined by the relationship between total plant drag and root strength.
In-stream submerged macrophytes have a complex morphology and several species are not rigid, but are flexible and reconfigure along with the major flow direction to avoid potential damage at high stream velocities. However, in numerical hydrodynamic models, they are often simplified to rigid sticks. In this study hydraulic resistance of vegetation is represented by an adapted bottom friction coefficient and is calculated using an existing two layer formulation for which the input parameters were adjusted to account for (i) the temporary reconfiguration based on an empirical relationship between deflected vegetation height and upstream depth-averaged velocity, and (ii) the complex morphology of natural, flexible, submerged macrophytes. The main advantage of this approach is that it removes the need for calibration of the vegetation resistance coefficient. The calculated hydraulic roughness is an input of the hydrodynamic model Telemac 2D, this model simulates depth-averaged stream velocities in and around individual vegetation patches. Firstly, the model was successfully validated against observed data of a laboratory flume experiment with three macrophyte species at three discharges. Secondly, the effect of reconfiguration was tested by modelling an in situ field flume experiment with, and without, the inclusion of macrophyte reconfiguration. The inclusion of reconfiguration decreased the calculated hydraulic roughness which resulted in smaller spatial variations of simulated stream velocities, as compared to the model scenario without macrophyte reconfiguration. We discuss that including macrophyte reconfiguration in numerical models input, can have significant and extensive effects on the model results of hydrodynamic variables and associated ecological and geomorphological parameters.& Veerle Verschoren
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.