http://theses.ncl.ac.uk/jspui/handle/10443/4094 Wed, 06 May 2026 18:28:02 GMT 2026-05-06T18:28:02Z http://theses.ncl.ac.uk/jspui/handle/10443/6759 Title: Improving estimation of spatial precipitation in a mountain region Authors: Shotton, Ronald Keith Abstract: Due to its importance for water resources, as well as flood and drought planning, an improved understanding of spatial precipitation patterns in mountain regions is needed. Precipitation gauge networks are sparse and traditional methods of interpolation yield inadequate precipitation fields for sparsely gauged mountain catchments. This work builds on a new method, Random Mixing, to generate multiple random spatial daily precipitation fields, conditioned on gauge observations. The Random Mixing algorithm has so far been tested on larger, densely gauged catchments. This project adapts the approach for a sparsely gauged, small 9.4 km2 mountain catchment, Marmot Creek Research Basin (MCRB) in Alberta, Canada. Three modifications have been made to the Random Mixing method in developing the new technique, which is referred to as RM-mountain: (1) improving spatial covariance, (2) introducing elevation dependence and (3) evaluating seasonal effects. Addition of each modification in turn increases the spatial variance of precipitation values across simulated fields. Leave-one-out cross-validation was used, and results compared with outputs from four deterministic spatial interpolation techniques. The best fit precipitation time series simulated by the RM-mountain generated ensemble members demonstrated improved precipitation estimates compared to the four deterministic techniques. Precipitation totals across the MCRB catchment generated by RM-mountain are higher than those from the other methods tested. Due to its random nature, RM-mountain enables generation of precipitation within the catchment on days when the gauges are dry. In contrast, deterministic spatial interpolation methods yield zero precipitation across the entire catchment on days with zero observed precipitation. Inclusion of modifications 1-3 in RM-mountain noticeably increased the likelihood of simulating more realistic precipitation values within the generated ensemble. To optimise selection of the most plausible fields, ensemble hydrological simulations were run, using a modified spatially-distributed version of the HBV conceptual model, and the physically-based Cold Regions Hydrological Model (CRHM), with a 200-member ensemble of time series spatial precipitation fields generated on a 50 m x 50 m regular model grid. Optimisation involved the use of Nash-Sutcliffe Efficiency (NSE) and bias metrics, to identify a best constructed time series that most closely simulates the observed streamflows. The improvement in streamflow bias with HBV was from -20.94 to 0.14; with CRHM, bias was 2 improved slightly from 2.04 to 1.88. Increases in NSE values were from 0.76 to 0.96 with HBV and from 0.54 to 0.74 with CRHM. Some noticeable differences between catchment responses with HBV and CRHM were observed, relating to the complexity of the models, i.e., the relative simplicity of the conceptual HBV model in contrast to the more complex physically-based CRHM. Notable examples of these differences were snowmelt earlier in the year and much less variation in the streamflow ensemble with HBV. A much greater variety of streamflow hydrographs in the CRHM-generated ensemble were due to CRHM’s much higher sensitivity to differences in observed meteorological input data, particularly wind speed. This work demonstrates that modifying a random method, by adapting how it randomly samples from observed precipitation at a small number of gauges, includes elevation gradients and seasonal variation, improves estimation of spatiotemporal precipitation patterns for a small mountain catchment and improves hydrological simulations. The new method has the potential to be used to enhance precipitation datasets to improve water resource and flood modelling in other sparsely gauged mountain regions. Description: PhD Thesis Wed, 01 Jan 2025 00:00:00 GMT http://theses.ncl.ac.uk/jspui/handle/10443/6759 2025-01-01T00:00:00Z http://theses.ncl.ac.uk/jspui/handle/10443/6746 Title: A novel transition metal dichalcogenide – reduced graphene oxide electrocatalyst family for hydrogen evolution reaction Authors: Jiang, Jianan Abstract: The global energy crisis underscores the critical need for sustainable hydrogen production via efficient electrocatalysts. This study presents a novel family of transition metal dichalcogenide-reduced graphene oxide (MoS2-rGO) hybrids and doped variants (V, W, Co) for the hydrogen evolution reaction (HER). Using orthogonal experimental design (L9(33)), we optimized synthesis parameters (rGO content, heating temperature, duration) to develop a MoS2-rGO composite with 0.8 wt% rGO, synthesized at 200°C for 24 h. This optimized catalyst achieved superior HER performance in acidic media (0.5 M H2SO4), exhibiting a low overpotential (η10 = -0.34 Vs RHE) and Tafel slope (98.2 mV/dec), significantly outperforming undoped MoS2 (η10 > 0.40 Vs RHE, Tafel slope 113.0 mV/dec). While Pt/C remains the benchmark catalyst with ultra-low overpotential (~0.05 V vs. RHE) and a Tafel slope of ~30 mV/dec, its high cost and scarcity hinder widespread application. In contrast, our MoS2-rGO catalysts offer a noble-metal-free alternative with enhanced conductivity and stability, facilitated by rGO integration. XRD and Raman spectroscopy confirmed structural improvements, while vanadium doping increased active site exposure, tungsten doping introduced sulfur vacancies to optimize hydrogen adsorption energy, and cobalt doping altered electronic structures. Systematic characterization via XRD, XPS, BET, UV-vis, Raman spectroscopy, SEM and electrochemical techniques elucidated the structural and electronic contributions of each component. The synergistic effects of rGO and dopants were highlighted, with the Co0.05W0.05S2/rGO heterostructure showing promising HER activity. This work establishes a rational framework for designing noble-metal-free HER catalysts, emphasizing the interplay between defect engineering, interfacial interactions, and scalable synthesis strategies. The integration of orthogonal optimization with multi-technique characterization provides a robust pathway for advancing green hydrogen technologies. Description: Ph. D. Thesis. Wed, 01 Jan 2025 00:00:00 GMT http://theses.ncl.ac.uk/jspui/handle/10443/6746 2025-01-01T00:00:00Z http://theses.ncl.ac.uk/jspui/handle/10443/6742 Title: The development of four dimensional electrical resistivity tomography for laboratory-scale imaging of soil moisture dynamics Authors: Thaman, Narryn I J Abstract: This study considers the combination of a novel geophysical monitoring system and geotechnical point sensors for use in controlled laboratory conditions to visualise soil moisture dynamics in different engineered soils. The geophysical monitoring system, referred to here as PRIME (Proactive Infrastructure Monitoring and Evaluation system), uses electrical resistivity tomography (ERT) technology to non-invasively image subsurface moisture-driven processes. The PRIME system and point sensor arrays have been developed for near real-time data acquisition of transient soil moisture conditions in a suite of soil column experiments. This research aims to provide new tools and approaches to further our understanding of soil moisture movement to better assess shallow geotechnical assets by addressing the challenges associated with designing integrated geophysical-geotechnical laboratory-scale monitoring experiments. A total of nine soil column experiments were carried out in this research. Soil moisture content, grain size and density were changed throughout the study to gauge the proficiency of time-lapse ERT for various soils. Nine soil column experiments were conducted to evaluate the effectiveness of time-lapse ERT in various soil compositions, assessing changes in moisture content, grain size, and density. One of the main challenges associated with integrating ERT in a soil column setup is the prevalence of artefacts in the time-lapse imaging. These artefacts, presenting as high or low electrical resistivity contrasts, can be a common feature in ERT surveys and are known to reduce the accuracy of the inversion. This study takes steps to reduce the tendency of artefacts in the results by systematically identifying the source of such modelling errors and adapting the 4D ERT integrated soil column design accordingly. Alongside plotting the electrical resistivity of transient soil moisture conditions in the column experiments, petrophysical relationships derived from the ERT soil columns focus on understanding the link between soil moisture content, electrical resistivity, and suction. These relationships are crucial for improving the interpretation of time-lapse ERT data and enhancing the accuracy of soil moisture monitoring in laboratory and field applications. Findings demonstrate the potential of integrating ERT with geotechnical monitoring systems to advance understanding of soil moisture movement, with applications in geotechnical asset management and environmental engineering. Description: PhD Thesis Wed, 01 Jan 2025 00:00:00 GMT http://theses.ncl.ac.uk/jspui/handle/10443/6742 2025-01-01T00:00:00Z http://theses.ncl.ac.uk/jspui/handle/10443/6738 Title: Investigation of Frequency Domain Reflectometry as a Degradation Monitoring Technique for Lithium-Ion Batteries Authors: Asiedu-Asante, Ama Baduba Abstract: Frequency Domain Reflectometry (FDR) is an impedance-based diagnostic technique traditionally used in power systems to assess impedance changes in power cables. Recently, FDR has been applied to battery systems to measure high-frequency impedance, which is valuable for understanding battery performance in power line communication networks and assessing electromagnetic compatibility (EMC). Previous studies have highlighted FDR's ability to detect high-frequency processes like skin effect and ionic shunt effect, and its sensitivity to factors such as charging current, state of charge (SoC), and temperature. However, its potential for monitoring battery State of Health (SoH) has not been thoroughly explored. This thesis investigates the use of FDR as a non-invasive, tool for monitoring SoH of lithium ion batteries. The study involved two main stages of analysis. First, FDR was used to measure the impedance of 19 commercial coin cells (LIR 2032) across a frequency range of 300 kHz to 1 GHz. These cells were aged to varying SoH levels through controlled cyclic aging, and their SoH was benchmarked using Electrochemical Impedance Spectroscopy (EIS). The FDR impedance measurements were then compared to health indicators like battery capacity and internal resistance to evaluate FDR's sensitivity and accuracy in detecting aging-induced changes. The second stage involved a statistical evaluation of FDR's effectiveness in data driven detection and prediction models, using techniques such as principal component analysis, multivariate statistical process control, and partial least squares regression. The findings show that while FDR can detect changes in battery impedance related to aging, it has limitations in sensitivity to slower degradation processes and accuracy at lower impedance values. FDR demonstrated potential for single-cell SoH tracking but was less effective for multi-cell detection and capacity prediction compared to EIS. Despite these limitations, FDR could complement other health indicators in a multi-metric battery monitoring system, provided that careful setup design and calibration are employed. Description: PhD Thesis Wed, 01 Jan 2025 00:00:00 GMT http://theses.ncl.ac.uk/jspui/handle/10443/6738 2025-01-01T00:00:00Z