Understanding the complex dynamics of water flow within a catchment is fundamental to effective water resource management. This understanding involves robust knowledge of the catchment's hydrological and physiographical features. It requires a profound grasp of the spatiotemporal variability in a catchment's climatic and hydrological patterns. Within this context, this thesis started with a comprehensive review of the historical and current literature on diurnal fluctuations in groundwater. The review touched upon several different aspects of the phenomenon, ranging from discussing the mechanisms of the origin of these signals, their role in the catchment's water balance, their link with groundwater and with the transpiration activities of the vegetation, and in the end, the importance of studying these catchments in revealing characteristics of a catchment. Potential gaps in the analysis of diurnal fluctuations are identified by exploring the literature., which motivated the compilation of this thesis. Firstly, the relationship between diurnal fluctuation and the potential evapotranspiration of riparian plants is investigated in relation to its effect on catchment reservoir storage. A novel method of estimating evapotranspiration (ET) rates is devised by establishing a relationship between diurnal streamflow changes and the catchment's riparian source area. The method reasonably estimated riparian evapotranspiration (ET) and linked the riparian area's dynamics with the diurnal patterns in stream flow by assuming a linear relationship between saturated riparian reservoirs and outflow. This analysis provided a much-needed understanding of the behaviour of the diurnal signals in a catchment and its relationship with the physical features of the catchment. Further, this analysis deeply studied the concept of time delay associated with the transpiration activities of riparian plants and catchments' response regarding diurnal fluctuation. Additionally, the seasonal evolution of ET estimates and the time lag revealed the tight coupling between stream response and active vegetation zones, with more significant and rapid fluctuation in colder months than warmer ones. In conclusion, the method provided an elaborate understanding of the complex interplay between riparian zones, groundwater dynamics, and streamflow patterns, contributing to a more profound understanding of catchment hydrology. Another significant thesis objective was to develop advanced automated techniques for detecting and analysing diurnal fluctuations to provide fast and reliable observations of diurnal fluctuations from a large dataset. Manually identifying this scarce phenomenon in an extensive multi-year dataset is time-consuming and one of the biggest reasons for minimal, large-sample studies concerning diurnal streamflow fluctuations. This is addressed by forming an automated process of diurnal fluctuation extraction with the application of the wavelet transform. The capabilities of both types of wavelet transformation, the discrete wavelet transform (DWT) and continuous wavelet transform (CWT) are tested to reveal time-frequency information of diurnal signals. A detailed workflow is developed to choose the best wavelet for detrending a streamflow series to obtain diurnal fluctuation. The detrending performance of the DWT process is compared against the traditional time-based detrending methods like the moving average. It confirms the superiority of wavelet transform in optimal detrending of observed streamflow data series. The CWT presented many different plots and revealed exciting features in the diurnal patterns in streamflow. The CWT information is then used to develop an algorithm for extracting diurnal episodes from extensive streamflow records. The extraction process captured an adequate number of diurnal episodes, which matched well with the manual identifications. Overall, the automated technique addressed the limitations posed by manual identification and contributed significantly to the advancement of time-frequency dynamics of diurnal fluctuations. Finally, with the knowledge of diurnal fluctuation gained in the first research objective and with the capabilities of the wavelet transform, a large sample study is carried out using streamflow records from different New Zealand catchments. Various dataset sources from streamflow records, snow cover maps, and digital elevation rasters are used to calculate different catchment characteristics. The analysis showed that characteristics like catchment shape and size strongly correlate with diurnal amplitude. The diurnal lag also showed patterns of change with the catchment parameters. It is revealed that the correlation between catchment size and diurnal amplitude becomes weaker in larger catchments due to the diverse and heterogeneous nature of environmental processes within these regions. This research significantly contributes to a deeper understanding of the temporal patterns of streamflow, providing valuable insights for hydrological modeling and water resource management. By integrating field observations, advanced analytical methods, and regional context, this work advances the understanding of diurnal streamflow dynamics.