Chien-Yung Tseng

and 1 more

Aquatic vegetation alters the hydrodynamics of natural waters, such as rivers, lakes, and estuaries. Plants can generate turbulence that propagates throughout the entire water column, which affects gas transfer mechanisms at both air-water and water-sediment interfaces, driving changes of dissolved oxygen (DO), an important indicator of water quality. We conducted a series of laboratory experiments with rigid cylinder arrays to mimic vegetation using a staggered configuration in a recirculating race-track flume. Walnut shells were chosen as the sediment substrate, which interacts with DO in water. 2D planar Particle Image Velocimetry was used to characterize the flow field under various submergence ratios, highlighting the effect of vegetation on turbulence quantities. Gas transfer rates were determined by measuring the DO concentration during the re-aeration process based on the methodology proposed by the American Society of Civil Engineers. Our data provide new insight on Air-Water-Vegetation-Sediment interactions in streams as a function of submergence ratio, array density, and flow turbulence. A modified surface renewal model using turbulence production as an indicator of gas transfer efficiency is used to predict surface gas transfer rates. A delayed time of re-aeration between the bulk and the near-bed region was observed and varies with flow velocities and submergence ratios, which controls the oxygen flux from water to sediment. Future studies are required to investigate the cause of the delayed time to incorporate sediment oxygen demand in a substrate-to-surface transfer model.

Maryam Ghadiri

and 2 more

Sangamon watershed is recognized as one of the most worth noting regions for water and environmental supply planning and management purposes according to its intensively management for soybean and corn production. It is also a representative area with limited geological and hydraulic measurement data, in which sustainable ground water and environmental management is essential. To better understand the hydraulic properties of the entire watershed, a multi-fidelity Gaussian Processes (Kriging) model was applied to predict the hydraulic conductivity of the upper Sangamon watershed, using previous multi-sources of field observation data (Electrical Earth Resistivity and pumping test data). The model also provided a quantification of uncertainty of the predicted values, which helps us to make reliable suggestions for the future design of hydraulic observations. The data fidelity effect to the model was discussed by comparing multi-fidelity and single-high-fidelity Kriging results. The model predicted values suggest that the accuracy of multi-fidelity Kriging depends on the locations and the distribution of both the high- and low-fidelity data. When high-fidelity data points are sparse and far away from the low-fidelity data points, the information provided from the low-fidelity data becomes extremely important, which can greatly enhance the model performance and accuracy. This study has paved the way to a more efficient parameter estimation in under-sampled sites by effectively estimating large-scale parameter maps using small-scale measurements and by applying uncertainty quantification method to a real watershed observation case. It will also draw upon and contribute to advances in Bayesian experimental design, and will optimally result in financial savings.

Chien-Yung Tseng

and 1 more

Maryam Ghadiri

and 4 more

Enhanced water management systems depend on accurate estimation of hydraulic properties of subsurface formations. This is while hydraulic conductivity of geologic formations could vary significantly. Therefore, using information only from widely spaced boreholes will be insufficient in characterizing subsurface aquifer properties. Hence, there is a need for other sources of information to complement our hydro-geophysics understanding of a region of interest. This study presents a numerical framework where information from different measurement sources is combined to characterize the 3-dimensional random field representing the hydraulic conductivity of a watershed in a Multi-Fidelity estimation model. Coupled with this model, a Bayesian experimental design will also be presented that is used to select the best future sampling locations. This work draws upon unique capabilities of electrical resistivity tests as well as statistical inversion. It presents a Multi-Fidelity Gaussian Processes (Kriging) model to estimate the geological properties in Upper Sangamon Watershed in east central Illinois, using multi-source observation data, obtained from electrical resistivity and pumping tests. We demonstrate the accuracy of Co-Kriging that is dependent on the locations and the distribution of both the high- and low-fidelity data, and also discuss its comparison with Single-High-Fidelity Kriging results. The uncertainties and confidence in the measurements and parameter estimates are then quantified and are in turn used to design future cycles of data collection to further improve the confidence intervals.

Chien-Yung Tseng

and 2 more

Chien-Yung Tseng

and 1 more

Turbulence generated by aquatic vegetation plays a vital role in the interfacial transfer process at the air-water interface and sediment-water interface (AWI and SWI), impacting the dissolved oxygen (DO) level, a key indicator of water quality for aquatic ecosystems. We investigated the influence of vegetation, under different submergence ratios and plant densities, on the interfacial gas transfer mechanisms. We conducted laboratory experiments in a unidirectional recirculating flume with simulated rigid vegetation on a sediment bed. Two-dimensional planar Particle Image Velocimetry (2D-PIV) was used to characterize the mean flow field and turbulent quantities. Gas transfer rates at the AWI were determined by monitoring the DO concentration during the re-aeration process in water. SWI interfacial transfer fluxes were estimated by measuring the DO concentration difference between the near-surface and near-bed values. Compared to previous observations on a smooth bed without sediment, the presence of sediment enhances the bottom roughness, which generates stronger bed-shear turbulence. The experimental result shows that turbulence generated from the bed does not affect the surface transfer process directly. However, the near-bed suspended sediment provides a negative buoyancy term that reduces the transfer efficiency according to the predictions by a modified Surface Renewal model for vegetated flows. The measured interfacial transfer fluxes across the SWI show a clear dependence on the within-canopy flow velocity, indicating that bed shear turbulence and within-canopy turbulence are critical indicators of transfer efficiency at SWI in vegetated flows. A new Reynolds number dependence model using near-bed turbulent kinetic energy as an indicator is proposed to provide a universal prediction for the interfacial flux across the SWI in flows with aquatic vegetation. Our study provides critical insight for future studies on water quality management and ecosystem restoration in natural water environments such as lakes, rivers, and wetlands.