Modelling Surface Water-Groundwater Exchange: Evaluating Model Uncertainty from the Catchment to Bedform-Scale

My dissertation focuses on evaluating model uncertainties when numerically simulating surface water-groundwater (sw-gw) interactions at different scales. To do so, I mainly use HydroGeoSphere, a physically-based distributed finite element model that fully couples variably saturated subsurface flow with surface water flow. I evaluate three predominant model uncertainty types at three different scales of sw-gw interaction. For each of these investigations, I selected a corresponding study site. Firstly, I evaluate structural (conceptual) uncertainty from delineating baseflow contribution areas to gaining stream reaches, or stream capture zones, at the catchment-scale. I investigate how the delineated stream capture zone (in the Alder Creek watershed) can differ due to the chosen model code and delineation method (Chow et al. 2016). The results indicate that different models can calibrate acceptably well to the same data and produce very similar distributions of hydraulic head, but can produce different capture zones. The stream capture zone is highly sensitive to the post-processing particle tracking algorithm. Reverse transport is an alternative and more reliable approach that accounts for local-scale parameter uncertainty and provides probability intervals for the stream capture zone. The two methods can be combined to enhance the overall confidence in the delineated stream capture zone. Secondly, I evaluate parameter uncertainty when simulating meander-scale hyporheic exchange by conducting a model-based sensitivity (bathymetry) and uncertainty (subsurface K-distribution) analysis. I select the Steinlach River Test Site for demonstration. I conduct a sensitivity analysis to determine the aspects of river bathymetry that have the greatest influence on the predictive biases (Chow et al. 2018). Results indicate that simulating hyporheic exchange with a high-resolution detailed bathymetry using a 3D fully coupled sw-gw model leads to nested multi-scale hyporheic exchange systems. A poorly resolved bathymetry will underestimate the small-scale hyporheic exchange, biasing the simulated hyporheic exchange towards larger scales, thus leading to overestimates of hyporheic exchange residence times. The detailed river slope alone is not enough to accurately simulate the locations and magnitudes of losing and gaining river reaches. Thus, local bedforms in terms of bathymetric highs and lows within the river are required. Incorporating local bedforms will likely capture the nested nature of hyporheic exchange, leading to more physically meaningful simulations of hyporheic exchange fluxes and transit times. Additionally, I conduct an uncertainty analysis to evaluate the trade-offs between intrinsic (irreducible) and epistemic (reducible) model errors when choosing between homogeneous and highly complex subsurface parameter structures (Chow et al. 2019). Results indicate that, if the parameter structure is too simple, it will be limited by intrinsic model errors. By increasing subsurface complexity through the addition of zones or heterogeneity, we can begin to exchange intrinsic for epistemic errors. Thus, choosing the appropriate level of detail to represent the subsurface parameter distributions depends on the acceptable range of intrinsic structural errors for the given modelling objectives and the available site data. Thirdly, I evaluate data uncertainty at the bedform-scale in a fractured rock setting by modelling a conservative tracer experiment at the Eramosa Bedrock River Site. I use a stochastic discrete fracture network framework to represent the subsurface fractured bedrock connectivity, and in doing so produce a probabilistic distribution of the potential hyporheic exchange extents and residence times. The results indicate that the coincidence of fractures and hydraulic gradients determine the spatial extents of bedform-scale hyporheic exchange. Furthermore, hyporheic exchange residence times in bedrock rivers at the bedform-scale are potentially orders of magnitude longer when compared to fluvial rivers (i.e., months to years vs. minutes to hours). In the age of highly-parameterized integrated hydrological models, there is an increasing need to understand whether we are getting the right forecasts for the right reasons. Modelling is only a single tool in the scientific toolbox that works best when combined with others, e.g., field and laboratory experiments. The next generation of integrated hydrological modellers will face evermore challenging objectives, which to achieve will require multi-disciplinary teams. Regardless of the origins of your knowledge-base, it is important to always approach numerical models with a healthy level of skepticism. Ultimately, scientists should approach models with a relentless fearlessness to falsify them, which is an absolute necessity if we wish to continually push the envelope of scientific knowledge

Delineating Base Flow Contribution Areas for Streams: A Model Comparison

This study extends the methodology for the delineation of capture zones to base flow contribution areas for stream reaches under the assumption of constant average annual base flow in the stream. The methodology is applied to the Alder Creek watershed in southwestern Ontario, using three different numerical models. The three numerical models chosen for this research were Visual Modflow, Watflow and HydroGeoSphere. Capture zones were delineated for three different stream segments with reverse particle tracking and reverse transport. The modelling results showed that capture zones delineated for streams are sensitive to the discretization scheme and the different processes considered (i.e. unsaturated zone, surface flow). It is impossible to predict the size, shape and direction of the capture zones delineated based on the model selected. Also, capture zones for different stream segments will reach steady-state at different times. In addition, capture zones are highly sensitive to differences in hydraulic conductivity due to calibration. It was found that finite element based integrated groundwater - surface water models such as HydroGeoSphere are advantageous for the delineation of capture zones for streams. Capture zones created for streams are subject to greater uncertainty than capture zones created for extraction wells. This is because the hydraulic gradients for natural features are very small compared to those for wells. Therefore, numerical and calibration errors can be the same order of magnitude as the gradients that are being modelled. Because of this greater uncertainty, it is recommended that particle tracking and reverse transport always be used together when delineating capture zones for stream reaches. It is uncertain which probability contour to choose when the capture zone is delineated by reverse transport alone. The reverse particle tracks help choose the appropriate probability contour to represent the stream capture zone

The Urban Deployment Model: A Toolset for the Simulation and Performance Characterization of Radiation Detector Deployments in Urban Environments

Static and mobile radiation detectors can be deployed in urban environments for a range of nuclear security applications, including radiological source search-and-tracking scenarios. Modeling detector performance for such applications is challenging, as it does not depend solely on the detector capabilities themselves. Many factors must be taken into consideration, including specific source and background signatures, the topology and constraints of the deployment environment, the presence of nuisance sources, and whether detectors are mobile or static. When considering the simultaneous deployment of multiple, heterogeneous detectors, assessment of the system-wide performance requires the simulation of the individual detectors, and a system-level analysis of the detection performance. In radiological source search-and-tracking scenarios, performance is mostly dominated by the probability of encounter, which depends on the specifics of a given deployment, e.g., static vs. mobile detectors or a combination of both modalities, the number of detectors deployed, the dynamic vs. static setting of false alarm rates, and individual vs. networked operation. The Urban Deployment Model (UDM) toolset was specifically developed to cover the gap in the available generic frameworks for the simulation of radiation detector deployments at city scales. UDM provides a unified and modular framework to support the simulation and performance characterization of heterogeneous detector deployments in urban environments. This paper presents the key components along the UDM workflow

Plasma, tissue and urinary levels of aloin in rats after the administration of pure aloin

Aloin is a physiologically active anthraquinone present in aloe. There are two isomers of aloin, aloin A and aloin B, occurring as a mixture of diastereomers. The objective of this study was to determine the bioavailability and tissue distribution of aloin. Rats were gavaged with 11.8g/kg aloin, and the levels of aloin and its conjugates were measured in plasma, tissues, and urine. Plasma aloin level showed a peak at 1hr after the administration and the concentration was 59.07±10.5 ng/ml. The 24 h cumulated urinary aloin was 0.03% of the initial dose. These results suggest that aloin is absorbed and reaches a peak plasma level within 1-1.5 h after the administration and a significant portion is possibly metabolized or is excreted in feces. These results can apply to the determination of the adequate intake level of aloe and aloe products to achieve the desired biological effect, and to interprete in vitro study results

Is groundwater running out in the Western Cape, South Africa? Evaluating GRACE data to assess groundwater storage during droughts

Study region: The Western Cape (WC), South Africa. Study focus: The WC has become increasingly dependent on groundwater in recent years due to repeated droughts. A framework to monitor the regional groundwater levels is urgently required to sustainably manage the WC’s water resources, since the region has inconsistent or unavailable monitoring data. Therefore, this study aims to understand how Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data can be used to monitor groundwater storage variations (ΔGWS) in the WC. In-situ ΔGWS time-series from twelve aquifers in the WC were compared to GRACE and GLDAS data. New hydrological insights for the region: GRACE terrestrial water storage anomalies (ΔTWS) showed moderate positive correlation (r = 0.69) with in-situ ΔGWS from the Adelaide Subgroup Aquifer (ASA), an unconfined aquifer with large areal extent and large ΔGWS. The Table Mountain Group Upper Aquifer Unit (TMG UAU) and Cape Flats Aquifer (CFA) also showed significant positive correlations with GLDAS ΔGWS of 0.83 and 0.73, respectively. Our results suggest that ΔGWS in the ASA can be monitored using GRACE ΔTWS, while GLDAS ΔGWS data can be used to monitor ΔGWS in the unconfined TMG UAU and CFA. GRACE and GLDAS data may be suitable to monitor groundwater availability in other water- and data-scarce regions of Africa