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Doctoral Degrees (Environmental Hydrology)

Permanent URI for this collectionhttps://hdl.handle.net/10413/6588

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Browsing Doctoral Degrees (Environmental Hydrology) by Author "Clark, David John."

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    Development and assessment of an improved continuous simulation modelling system for design flood estimation in South Africa using the ACRU model.
    (2019) Rowe, Thomas James.; Smithers, Jeffrey Colin.; Clark, David John.
    An estimate of the risk associated with flood events is required to adequately design hydraulic structures and limit negative socio-economic impacts as a result of floods. The methods used to estimate design floods in South Africa are outdated and are in need of revision. A National Flood Studies Programme (NFSP) has recently been initiated by Smithers et al. (2016) to overhaul Design Flood Estimation (DFE) procedures in South Africa. One of the recommendations of the NFSP is development and assessment of a Continuous Simulation Modelling (CSM) approach to DFE. Consequently, the aim of this study is to further develop and assess the performance of an improved comprehensive CSM system, to consistently and reliably estimate design flood discharges in small catchments (0 - 100 km2) in South Africa using the ACRU model. In the development of the approach a strong emphasis has been placed on ease of use from a practitioner’s point of view. The aim is achieved through several specific objectives as summarised below. The first objective was to review CSM approaches applied locally and internationally for DFE, in order to identify research gaps and guide the development of an improved national CSM system for DFE in South Africa. The review culminates with a list of recommendations and steps required to develop and adopt a CSM approach for DFE in practice. The first critical step identified and required was the development of a comprehensive CSM system using the ACRU model (Schulze, 1995). This included: the structure of the system and how to implement the system, an enhanced land cover and soils classification to apply with the system and default input information and databases to use with the system. The second objective addresses the recommendations made from the literature review, where a comprehensive CSM system for DFE using the ACRU model is developed and described in detail. Based on similarities identified between the ACRU (Schulze, 1995) and SCS-SA models (Schmidt and Schulze, 1987a), as well as the fact that the SCS-SA model is relatively simple and widely applied in practice, the CSM system was adapted to be consistent with the land cover classification used in the SCS-SA model. This included the incorporation of a methodology and rules, developed by Rowe (2015), to represent land management practices and hydrological conditions within the ACRU model. The development of this comprehensive CSM system with default national scale inputs and land cover classifications contributes to new knowledge on how to package a CSM system for DFE in South Africa. The third objective focuses on the assessment and verification of the CSM system developed, using observed data. Through the verifications and assessments performed an inconsistency between daily simulated stormflow volumes and the volume of stormflow used in the daily stormflow peak discharge equation was identified. Therefore, a revision, which is more conceptually correct than the current assumption that all stormflow generated from an event contributes to the peak discharge on the day, was applied to the fraction of the simulated daily stormflow used in the peak discharge equation. This corrected the inconsistency and significantly improved the results, thereby providing an improved methodology to more accurately estimate peak discharges in the ACRU model than had hitherto been the case. Despite the improvement in the results, a general over-simulation of peak discharges was still evident. Consequently, further investigation of the ACRU stormflow peak discharge computations was performed in order to identify which approach provides the most satisfactory results (Objective 4). This included a performance assessment of both the SCS single Unit Hydrograph (UH) approach and the incremental UH approach. The performance of each approach was assessed using both estimated parameters and parameters derived from observed data. These parameters include stormflow volumes, catchment lag times, and the distribution of daily rainfall, where applicable, to each approach. Comparison of the results from the two approaches indicated that more accurate results are obtained when applying the incremental UH approach, when using both estimated or observed parameter inputs. In terms of the incremental UH approach, it was identified that the approach is more sensitive to the use of synthetic daily rainfall distributions compared to estimated lag times. Based on the results obtained new knowledge and additional research gaps related to: (i) improved estimation of the distribution of daily rainfall within the ACRU model, (ii) links between the distribution of daily rainfall and catchment lag time, and (iii) the need to further verify and possibly recalibrate CNs for South Africa were identified. The fifth objective addressed is an assessment of the impact of model configuration on the performance of the ACRU CSM system developed, in order to propose a final CSM system for DFE in South Africa. Results when using site-specific land cover and soils information are compared to those obtained when different sources of input information are used, such as the national land cover and soils maps developed for the entire country. The results when using these default national datasets were not particularly good, however recommendations are made to improve on the results. In addition, the most appropriate current databases to use with the CSM system are defined, providing users with the most appropriate default information currently available to use in the absence of site-specific information. The last objective addressed was a comparison of the performance of the final ACRU CSM system proposed in this study to that of the widely applied SCS-SA model and associated approaches, when using the same input information. Ultimately, the final ACRU CSM system proposed provides results that are superior to those from the SCS-SA model and associated approaches. In addition, several advantages of the ACRU CSM system over the traditional SCS-SA approaches were identified. Recommendations were, however, made to improve on the CSM system developed in this study and to use the results to update the SCS-SA model. New knowledge on the performance of the SCS-SA model and its associated approaches compared to that of the comprehensive CSM system developed for South Africa is therefore provided in this study.
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    Development and assessment of an integrated largescale hydrological modelling tool for water resources management in the Cauvery Catchment, India.
    (2022) Horan, Robyn.; Smithers, Jeffrey Colin.; Kjeldsen, Thomas Rodding.; Clark, David John.; Toucher, Michele Lynn.
    Economic development and population growth in southern India have resulted in rapid changes to land use, land management and water demand, significantly impacting and degrading water resources. The significant anthropogenic influences across the catchment have contributed to changes in hydrological functioning. Focussing on the highly contentious inter-state Cauvery River Catchment, this study aims to address the key scientific challenges faced within this catchment. The study was designed to develop an integrated large-scale hydrological model to improve water resource assessments in a highly heterogeneous and data-scarce region whilst considering the primary water resource challenges facing the Cauvery Catchment. The Upper Cauvery region, located in the Western Ghats, acts as the water tower of the catchment. The rainfall in the region is monsoonal, the topography is complex, and the rain gauge network is sparse, resulting in the estimation of rainfall being particularly challenging. The scarce rainfall data available in the Western Ghats region is hindering the understanding of the regional weather system, and the accepted rainfall dataset for India, Indian Meteorological Department rainfall grids, are known to have inaccurate estimations within the Western Ghats. The current knowledge of the meteorology and hydrology of the Upper Cauvery is limited. Additionally, the anthropogenic impact on local hydrological processes, such as streamflow, groundwater recharge and evapotranspiration, is poorly constrained. The current understanding of how these diverse local changes cumulatively impact water availability at the broader catchment scale is minimal. Small-scale rural water management and urban heterogeneity may strongly affect water resource availability across southern India. However, how such fine-scale factors propagate to the river catchment is largely unclear. The Global Water Availability Assessment (GWAVA) model was applied initially to the Upper Cauvery region to determine the suitability and compare model results from other modelling tools applied in the region. Two new versions of the GWAVA model were then developed. The first aimed to include small-scale runoff harvesting interventions (SSRHIs) into the model and quantify their impact on catchment water resources to address a renewed scientific interest in assessing their effectiveness in improving local water resources and the effects at a catchment scale. The second aimed to enhance the representation of groundwater and large operational dams whilst maintaining the model’s applicability to regions with low-data availability. The Indian Meteorological Department (IMD) gridded rainfall was compared to available gauges and selected remotely sensed datasets within the Upper Cauvery region. GWAVA will be utilised to assess the applicability of the remotely sensed data for a catchment rainfall estimation. GWAVA was determined to be a suitable tool to represent the Cauvery Catchment; however, the importance of an accurate spatial representation of rainfall for input into hydrological models and that comprehensive dam functionality is paramount to obtaining good results in this region was highlighted. Furthermore, the average GWAVA, VIC and SWAT ensemble provided a better predictive ability in catchments with dams than the individual models. The average ensemble offset uncertainty in input data and poor dam operation functionality within individual models. The inclusion of SSRHIs demonstrated that farm bunds appear to have a negligible effect on the average annual simulated streamflow. In contrast, tanks and check dams have a more significant and time-varying impact. The open water surface of the SSRHIs contributed to an increase in evaporation losses across the sub-catchment. The change in simulated groundwater storage with the inclusion of SSRHIs was not as significant as sub-catchmentscale literature, and field studies suggest. Including groundwater processes into GWAVA improved streamflow simulation in the headwater sub-catchments and the representation of the baseflow component such that low-flow model skill increased approximately 33-67% in the Cauvery and 66-100% in the Narmada. The existing dam routine was extended to account for large, regulated dams with two calibratable parameters. The routine improved streamflow simulation in sub-catchments downstream of major dams, where the streamflow was largely reflective of dam releases. The model performance was improved between 15 and 30% in the Cauvery and 7-30% in the Narmada when the regulated dams were considered. The model provides a more robust representation of the annual outflow volume from major dams, reducing the average bias from -17% to -1% in the Cauvery and from 14% to 3% in the Narmada. The daily dam releases were significantly improved in the Cauvery, approximately 26-164%. The improvement of the groundwater and dam routines in GWAVA proved successful in improving the overall model performance, the low-flow model skill and bias, and the inclusions allowed for improved traceability of simulated water balance components. It was found that the IMD rainfall within the high-altitude regions of the Western Ghats is underestimated, resulting in the under-simulation of streamflow in the Upper Cauvery. CHIRPS 0.25- and 0.05- degree, MSWEP and PERSIANN remotely sensed rainfall datasets were applied within this region. None of the individual rainfall datasets provided a more accurate representation of the rainfall than the commonly utilised IMD grids. However, using an ensemble of remotely sensed rainfall datasets, primarily the average ensemble, improved the accuracy of rainfall estimation in the catchment. The ‘off-the-shelf’ remotely sensed rainfall products provided a high variation in performance against the in-situ rain gauge data. The IMD grids provided the most accurate representation of rainfall compared to the individual remotely sensed rainfall datasets, despite underestimating the rainfall depths at high altitudes. In the case of the Upper Cauvery, the average ensemble provided a more accurate representation of the rainfall. An integrated large-scale hydrological model was developed to improve water resources assessments in a highly heterogeneous and data-scarce region whilst considering the major water resource challenges facing the Cauvery Catchment. The effects of runoff harvesting interventions, accounting for hard-rock aquifer groundwater processes and the impact of major dams were represented. The inclusion of these features improved the model performance throughout the Cauvery Catchment.