Dissertations / Theses on the topic 'Hydrology Victoria Data processing'

Environmental satellites represent an economic and easily accessible monitoring means for a plethora of environmental variables, the most important of which is arguably precipitation. While precipitation can also be measured by conventional rain gages and radar, in most world regions, satellites provide the only reliable and sustainable monitoring system. This thesis presents a methodology for estimating precipitation using information from the satellite-borne precipitation radar of the Tropical Rainfall Measurement Mission (TRMM). The methodology combines the precise, but infrequent, TRMM data with the infrared (IR) and visible (VIS) images continuously produced by geostationary satellites to provide precipitation estimates at a variety of temporal and spatial scales. The method is based on detecting IR patterns associated with convective storms and characterizing their evolution phases. Precipitation rates are then estimated for each phase based on IR, VIS, and terrain information. This approach improves the integration of TRMM precipitation rates and IR/VIS data by differentiating major storms from smaller events and noise, and by separating the distinct precipitation regimes associated with each storm phase. Further, the methodology explicitly quantifies the uncertainty of the precipitation estimates by computing their full probability distributions instead of just single optimal values. Temporal and spatial autocorrelation of precipitation are fully accounted for by using spatially optimal estimator methods (kriging), allowing to correctly assess precipitation uncertainty over different spatial and temporal scales. This approach is tested in the Lake Victoria basin over the period 1996-1998 against precipitation data from more than one hundred rain gages representing a variety of precipitation regimes. The precipitation estimates were shown to exhibit much lower bias and better correlation with ground data than commonly used methods. Furthermore, the approach reliably reproduced the variability of precipitation over a range of temporal and spatial scales.

Drought is the most costly hazard among all natural disasters. Despite the significant improvements in drought modeling over the last decade, accurate provisions of drought conditions in a timely manner is still one of the major research challenges. In order to improve the current drought monitoring and forecasting skills, this study presents a hybrid system with a combination of remotely sensed data assimilation based on particle filtering and a probabilistic drought forecasting model. Besides the proposed drought monitoring system through land data assimilation, another novel aspect of this dissertation is to seek the use of data assimilation to quantify land initial condition uncertainty rather than relying entirely on the hydrologic model or the land surface model to generate a single deterministic initial condition. Monthly to seasonal drought forecasting products are generated using the updated initial conditions. The computational complexity of the distributed data assimilation system required a modular parallel particle filtering framework which was developed and allowed for a large ensemble size in particle filtering implementation. The application of the proposed system is demonstrated with two case studies at the regional (Columbia River Basin) and the Conterminous United States. Results from both synthetic and real case studies suggest that the land data assimilation system significantly improves drought monitoring and forecasting skills. These results also show how sensitive the seasonal drought forecasting skill is to the initial conditions, which can lead to better facilitation of the state/federal drought preparation and response actions.

Fifty years ago there were no stored-program electronic computers in the world. Even thirty years ago a computer was something that few organisations could afford, and few people could use. Suddenly, in the 1960s and 70s, everything changed and computers began to become accessible. Today* the need for education in Business Computing is generally acknowledged, with each of Victoria's seven universities offering courses of this type. What happened to promote the extremely rapid adoption of such courses is the subject of this thesis. I will argue that although Computer Science began in Australia's universities of the 1950s, courses in Business Computing commenced in the 1960s due to the requirement of the Commonwealth Government for computing professionals to fulfil its growing administrative needs. The Commonwealth developed Programmer-in-Training courses were later devolved to the new Colleges of Advanced Education. The movement of several key figures from the Commonwealth Public Service to take up positions in Victorian CAEs was significant, and the courses they subsequently developed became the model for many future courses in Business Computing. The reluctance of the universities to become involved in what they saw as little more than vocational training, opened the way for the CAEs to develop this curriculum area.

Streams in small watersheds are often known to exhibit diel fluctuations, in which streamflow oscillates on a 24-hour cycle. Streamflow diel fluctuations, which we investigate in this study, are an informative indicator of environmental processes. However, in Environmental Data sets, as well as many others, there is a range of noise associated with individual data points. Some points are extracted under relatively clear and defined conditions, while others may include a range of known or unknown confounding factors, which may decrease those points' validity. These points may or may not remain useful for training, depending on how much uncertainty they contain. We submit that in situations where some variability exists in the clarity or 'Confidence' associated with individual data points – Notably environmental data – an approach that factors this confidence into account during the training phase is beneficial. We propose a methodological framework for assigning confidence to individual data records and augmenting training with that information. We then exercise this methodology on two separate datasets: A simulated data set, and a real-world, Environmental Science data set with a focus on streamflow diel signals. The simulated data set provides integral understanding of the nature of the data involved, and the Environmental Science data set provides a real-world case study of an application of this methodology against noisy data. Both studies' results indicate that applying and utilizing confidence in training increases performance and assists in the Data Mining Process.

Thesis (M. Tech.) -- Central University of Technology, Free State, 2007
In South Africa, water is a scarce resource and it has become very important to manage this resource effectively. The State developed a regulating framework, under the hospice of the Minister of Water Affairs and Forestry, which protects the country‟s water resources from over-exploitation by ensuring that it is protected, used, developed, conserved, and managed, in a sustainable and equitable manner. The laws and policies governing the use of water resources are contained in the National Water Act (South Africa, 1998), the National Water Policy (South Africa, 1997a), the National Water Resource Strategy, and the Water Services Act (South Africa, 1997b). In addition some water-related functions were transferred to Catchment Management Agencies and Water Users‟ Associations, and it is their task to ensure that the strategies, laws and policies are implemented. Effective water management can only be performed by making use of hydroinformatics which assists with simulations and estimations. As a result input data will be collected, added to a Relational Database Management System and output results generated. A Geographic Information System with the support of a geodatabase will allow users to store spatial and temporal data. The research project investigated different water-related data models (ArcHydro, Hydstra, GML, HYMOS, and WinHSPF), as well as hydrological modelling frameworks (BASINS, OMS, OpenMI, SPATSIM, and TIME) to determine whether they were adequate to assist with the decision making of water-related activities. It was found that these data models and hydrological modelling frameworks did not allow users to add new datasets to their existing data structures and in many cases only had a limited set of functions. For these reasons it was decided to develop a comprehensive, modifiable, geodatabase that will function in a modelling environment which will allow users to save their data in a centralised database. Additionally the functionality provided by other data models and modelling frameworks may be linked and used in the new modelling environment. A methodology that has been followed was to first establish the objectives of the research project, gather the necessary data, investigate various data models and hydrological modelling frameworks, determine the requirements for the modelling environment, design and create the modelling environment, design and create the geodatabase, and finally selecting the study area which will provide the research project with the necessary data. The following findings were made concerning the research project: firstly, that ArcHydro will be used as example data model to assist in designing the geodatabase. Secondly, that UML will be used as a development tool to assist with the development of the geodatabase. Thirdly, that the geodatabase will be generated from the XML schema and be made available to ArcCatalog. Fourthly, that data from different users/providers (Hydstra, Stats SA, Weather Bureau, Department of Water Affairs and Forestry, etc.) be inserted into the geodatabase. Fifthly, that any other hydrological modelling framework may make use of the data stored in the geodatabase. Finally, ArcGIS was selected as GIS application and Microsoft Access as a storage area.

The main scope of this project is to rebuild and deploy web applications that will help share historical artifacts related to the Santa Ana watershed. This project is designed to give a consistent user interface and add extra tools to enhance the functionality of existing applications at the Water Resources Institute (WRI) at California State University San Bernardino (CSUSB). The purpose of this project is to migrate all applications to a single server and update the applications using ArcGIS Server 9.2. Also to give a consistent look to the applications and to make them user friendly.

South African water management areas could find themselves without enough water for its users due to new methods of performing water allocation as stipulated in the National Water Act of 1998. A water accounting system would address the need for accurate metering, monitoring and auditing of South Africa’s water resources to ensure that users are complying with their allocations. Such a system should be able to provide information such as comparisons between the simulated and observed flow of water at a point, comparisons between the amount of water allocated to a user and the actual water used by that user, and the source and destination of water at a point. This document contains a literature review, an explanation of the methods used to develop a prototype water accounting system and a discussion of the results from testing the system. A literature review was undertaken which covered topics in water resources planning, water resources operations, local legislation for water allocation and new technologies which could be applied to aid the management of water resources in South Africa. The results from the literature review indicated real time water accounting systems can give effect to water allocation rules. The water accounting system is comprised of two simulation models and a database. The models used for the study were the ACRU2000 model and the MIKE BASIN model. These models require data as well as a means to automate the transfer of data between the models and thus a database was developed. The database was developed in Microsoft Access and, in addition to the construction of a number of tables required to house the data, a database dashboard was made to control the functions of the database. An assessment of the ACRU2000 and MIKE BASIN models was performed in order to determine if they are suitable for use as water accounting tools. ACRU2000 was used for its process based, daily rainfall-runoff modelling capabilities. Due to the process based modelling capabilities of ACRU2000, forecasts of rainfall can be used as input to the simulations. Hot starting is the storing of internal model state variables at a particular time and the use of these variables in a different simulation to start the model up again. It was expected that, due to long simulation run times for ACRU2000, it would be beneficial to enable ACRU2000 to be hot started and an attempt to hot start ACRU2000 is presented. This would have allowed for significantly decreased simulation run times as the model can be warmed up for two years and thereafter hot started to run only for one day at a time. An assessment of the MIKE BASIN network allocation model to be used as a water accounting system was performed by attempting to meet the project objectives through building a fictional water supply network. The network is composed of a small catchment containing six runoff generating regions, a reservoir and ten water users. Three network allocation scenarios were constructed in order to fully test the rule sets and allocation capabilities currently available in the MIKE BASIN model. The study has shown that the tools and models used are capable of forming a rudimentary water accounting system. This is encouraging as it shows that there is the potential to improve the water resources management in South Africa using tools that already exist.
Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2010.

The budgeting of water fluxes in the soil is an extremely complex problem, and is compounded by subsurface controls and environmental forces which modify the soil water dynamics. Of the controlling factors, the underlying geology and the soil media are vital components and are often misinterpreted. The geology and soil media components have been neglected mostly because of the difficulty in monitoring the dominant processes that are linked to the water balance in the subsurface. Until recently, hydrometry has been the dominant method of measuring and monitoring the subsurface water balance. Hydrometric measurements have included water content measurement by Time Domain Reflectometry (TDR), soil water potential measurements through tensiometry and groundwater water level monitoring. Hydrometry is still the preferred method of monitoring soil water dynamics, but measurements are generally localised and lateral accumulations and fluxes of water are difficult to interpret. Using geophysical methods and instrumentation to define soil water dynamics could have numerous advantages over conventional hydrometric methods. Among the geophysical techniques dedicated to image the near surface, Electrical Resistivity Tomography (ERT) surveying has been increasingly used for environmental, engineering and geological purposes during the last decade. The aim of this study is to determine if ERT observations could yield the accuracy required to define vertical and lateral soil water dynamics. The ERT instrumentation uses an electrical current that is inserted into the subsurface through various electrode arrangements and a resulting resistance is determined at the take-out electrodes. With the aid of a modelling package these resistance values are reproduced into a pseudosection of underlying resistivity distribution which is influenced by the moisture conditions of the subsurface medium. This geophysical method is primarily used for geological studies but by doing repeated surveys with the same electrode positioning, moisture fluctuation monitoring could be realised. Use of the ERT technique is at the forefront of soil water dynamics monitoring. The main objective of this study is to propose that the ERT instrumentation could be a more efficient and more informative method of studying soil water dynamics than the traditional soil water dynamics monitoring equipment, particularly to define lateral fluxes and accumulation of subsurface water. The study site is a well instrumented transect in the Nkuhlu Exclosures in the Kruger National Park, South Africa, where ongoing soil water dynamics are monitored. The project aims to compare the ERT data to fiR data on a daily basis, over a period of three weeks, during the rain season, monitoring event based wetting and the subsequent drying phases of the soils in a 2-dimensional section. The project and its fmdings are shown to be valuable to the hydrological interpretation of the subsurface water balance. The application is shown to be particularly important to ecohydrology, in the monitoring of soil water dynamics in a 2-dimensional transect and understanding how the natural cycles of water distribution and plant uptake are linked together. The study demonstrates that ERT can be used to observe changes in the water storage and lateral fluxes within a transect which supports varying vegetation and ecologies. The linking of water fluxes in the hydrology cycle to uptakes and controls in the ecosystem has been developed into the research focus known as ecohydrology The use of the ERT instrument can only benefit this research focus in the future. The study demonstrates that ERT instrumentation can be used to provide valuable understanding of subsurface water dynamics and in turn the effects on ecohydrology.
Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2006.

A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2017
The main problem to be investigated is how short duration data records can be augmented using existing data from nearby catchments with data with long periods of record. The purpose of the investigation is to establish a method of improving hydrological data using data from a gauged catchment to improve data from an ungauged catchment. The investigation is undertaken using rainfall data for catchments in Lesotho. Marginal distributions describing the annual maximum rainfall for the catchments, and a joint distribution of pairs of catchments were established. The parameters of these distributions were estimated using the Bayesian – Markov Chain Monte Carlo approach, and using both the single-site (univariate) estimation and the two-site (bivariate) estimations. The results of the analyses show that for catchments with data with short periods of record, the precision of the estimated location and scale parameters improved when the estimates were carried out using the two-site (bivariate) method. Rainfall events predicted using bivariate analyses parameters were generally higher than the univariate analyses parameters. From the results, it can be concluded that the two-site approach can be used to improve the precision of the rainfall predictions for catchments with data with short periods of record. This method can be used in practice by hydrologists and design engineers to enhance available data for use in designs and assessments.
CK2018

Streamflow data are critical for water resource investigations, and their development projects. However, the scarcity of such data, particularly measured streamflow through streamflow gauges, constitutes a serious impediment to the successful implementation of development projects. In the absence of such measured streamflow data, streamflow estimation using measured meteorological data represents a viable alternative. Nevertheless, this alternative is not always possible due to the unavailability of required meteorological data. In the face of such data limitations, many have advocated the use of remote sensing (RS) data to estimate streamflow. The aim of this study was to generate daily streamflow time series data using remote sensing data through catchment process modelling and statistical modelling.

"May 2002" Includes list of papers published during this study Errata slip inserted inside back cover of v. 1 Includes bibliographical references (leaves 331-357) V. 1. [Text} -- v. 2. Appendices Develops an alternative design flood estimation methodology. Establishing a relationship between catchment characteristics and the rainfall excess frequency duration proportions enables the definition of these proportions for generic catchment types, increasing the potential for translation to catchments with limited data but similar hydrographic properties, thereby improving design process.

Policy makers, water managers, farmers and many other sectors of the society in southern Africa are confronting increasingly complex decisions as a result of the marked day-to-day, intra-seasonal and inter-annual variability of climate. Hence, forecasts of hydro-climatic variables with lead times of days to seasons ahead are becoming increasingly important to them in making more informed risk-based management decisions. With improved representations of atmospheric processes and advances in computer technology, a major improvement has been made by institutions such as the South African Weather Service, the University of Pretoria and the University of Cape Town in forecasting southern Africa’s weather at short lead times and its various climatic statistics for longer time ranges. In spite of these improvements, the operational utility of weather and climate forecasts, especially in agricultural and water management decision making, is still limited. This is so mainly because of a lack of reliability in their accuracy and the fact that they are not suited directly to the requirements of agrohydrological models with respect to their spatial and temporal scales and formats. As a result, the need has arisen to develop a GIS based framework in which the “translation” of weather and climate forecasts into more tangible agrohydrological forecasts such as streamflows, reservoir levels or crop yields is facilitated for enhanced economic, environmental and societal decision making over southern Africa in general, and in selected catchments in particular. This study focuses on the development of such a framework. As a precursor to describing and evaluating this framework, however, one important objective was to review the potential impacts of climate variability on water resources and agriculture, as well as assessing current approaches to managing climate variability and minimising risks from a hydrological perspective. With the aim of understanding the broad range of forecasting systems, the review was extended to the current state of hydro-climatic forecasting techniques and their potential applications in order to reduce vulnerability in the management of water resources and agricultural systems. This was followed by a brief review of some challenges and approaches to maximising benefits from these hydro-climatic forecasts. A GIS based framework has been developed to serve as an aid to process all the computations required to translate near real time rainfall fields estimated by remotely sensed tools, as well as daily rainfall forecasts with a range of lead times provided by Numerical Weather Prediction (NWP) models into daily quantitative values which are suitable for application with hydrological or crop models. Another major component of the framework was the development of two methodologies, viz. the Historical Sequence Method and the Ensemble Re-ordering Based Method for the translation of a triplet of categorical monthly and seasonal rainfall forecasts (i.e. Above, Near and Below Normal) into daily quantitative values, as such a triplet of probabilities cannot be applied in its original published form into hydrological/crop models which operate on a daily time step. The outputs of various near real time observations, of weather and climate models, as well as of downscaling methodologies were evaluated against observations in the Mgeni catchment in KwaZulu-Natal, South Africa, both in terms of rainfall characteristics as well as of streamflows simulated with the daily time step ACRU model. A comparative study of rainfall derived from daily reporting raingauges, ground based radars, satellites and merged fields indicated that the raingauge and merged rainfall fields displayed relatively realistic results and they may be used to simulate the “now state” of a catchment at the beginning of a forecast period. The performance of three NWP models, viz. the C-CAM, UM and NCEP-MRF, were found to vary from one event to another. However, the C-CAM model showed a general tendency of under-estimation whereas the UM and NCEP-MRF models suffered from significant over-estimation of the summer rainfall over the Mgeni catchment. Ensembles of simulated streamflows with the ACRU model using ensembles of rainfalls derived from both the Historical Sequence Method and the Ensemble Re-ordering Based Method showed reasonably good results for most of the selected months and seasons for which they were tested, which indicates that the two methods of transforming categorical seasonal forecasts into ensembles of daily quantitative rainfall values are useful for various agrohydrological applications in South Africa and possibly elsewhere. The use of the Ensemble Re-ordering Based Method was also found to be quite effective in generating the transitional probabilities of rain days and dry days as well as the persistence of dry and wet spells within forecast cycles, all of which are important in the evaluation and forecasting of streamflows and crop yields, as well as droughts and floods. Finally, future areas of research which could facilitate the practical implementation of the framework were identified.
Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2007.

Indiana University-Purdue University Indianapolis (IUPUI)
The primary objective of this research involves mapping out and validating the existence of sub surface drainage tiles in a given cropland using Remote Sensing and GIS methodologies. The process is dependent on soil edge differentiation found in lighter versus darker IR reflectance values from tiled vs. untiled soils patches. Data is collected from various sources and a primary classifier is created using secondary field variables such as soil type, topography and land Use and land cover (LULC). The classifier mask reduces computational time and allows application of various filtering algorithms for detection of edges. The filtered image allows an efficient feature recognition platform allowing the tile drains to be better identified. User defined methods and natural vision based methodologies are also developed or adopted as novel techniques for edge detection. The generated results are validated with field data sets which were established using Ground Penetration Radar (GPR) studies. Overlay efficiency is calculated for each methodology along with omission and commission errors. This comparison yields adaptable and efficient edge detection techniques which can be used for similar areas allowing further development of the tile detection process.

Finally, the newly integrated model was firstly applied to analyze the relationship of land use and hydrologic regimes based on the land use maps in 1980 and 2000. Then the newly integrated model was applied to simulate the potential impacts of land use change on hydrologic regimes in the East River Basin under a series of hypothetical scenarios. The results show that ET has a positive relationship with Leaf Area Index (LAI) while runoff has a negative relationship with LAI in the same climatic zone, which can be elaborated by surface energy balance and water balance equation. Specifically, on an annual basis, ET of forest scenarios is larger than that of grassland or cropland scenarios. On the contrary, runoff of forest scenarios is less than that of grassland or cropland scenarios. On a monthly basis, for most of the scenarios, particularly the grassland and cropland scenarios, the most significant changes occurred in the rainy season. The results indicate that deforestation would cause increase of runoff and decrease of ET on an annual basis in the East River Basin. On a monthly basis, deforestation would cause significant decrease of ET and increase of runoff in the rainy season in the East River Basin.
In order to effectively simulate hydrologic impact of LUCC, an integrated model of ESEBS and distributed monthly water balance model has been developed in this study. The model is capable of considering basin terrain and the spatial distribution of precipitation and soil moisture. Particularly, the model is unique in accounting for spatial and temporal variations of vegetation cover and ET, which provides a powerful tool for studying the hydrologic impacts of LUCC. The model was applied to simulate the monthly runoff for the period of 1980-1994 for model calibration and for the period of 1995-2000 for validation. The calibration and validation results show that the newly integrated model is suitable for simulating monthly runoff and studying hydrologic impacts ofLUCC in the East River Basin.
Land use/cover change (LUCC) has significantly altered the hydrologic system in the East River (Dongjiang) Basin. Quantitative modeling of hydrologic impacts of LUCC is of great importance for water supply, drought monitoring and integrated water resources management. An integrated eco-hydrologic modeling system of Distributed Monthly Water Balance Model (DMWBM), Surface Energy Balance System (SEBS) was developed with aid of GIS/RS to quantify LUCC, to conduct physically-based ET (evapotranspiration) mapping and to predict hydrologic impacts of LUCC.
The physically-remote-sensing-based Surface Energy Balance System (SEBS) was employed to estimate areal actual ET for a large area rather than traditional point measurements . The SEBS was enhanced for application in complex vegetated area. Then the inter-comparison with complimentary ET model and distributed monthly water balance model was made to validate the enhanced SEBS (ESEBS). The application and test of ESEBS show that it has a good accuracy both monthly and annually and can be effectively applied in the East River Basin. The results of ET mapping based on ESEBS demonstrate that actual ET in the East River Basin decreases significantly in the last two decades, which is probably caused by decrease of sunshine duration.
These results are not definitive statements as to what will happen to runoff, ET and soil moisture regimes in the East River Basin, but rather offer an insight into the plausible changes in basin hydrology due to land use change. The integrated model developed in this study and these results have significant implications for integrated water resources management and sustainable development in the East River Basin.
To begin with, in order to evaluate LUCC, understand implications of LUCC and provide boundary condition for the integrated eco-hydrologic modeling, firstly the long-term vegetation dynamics was investigated based on Normalized Difference Vegetation Index (NDVI) data, and then LUCC was analyzed with post-classification methods and finally LUCC prediction was conducted based on Markov chain model. The results demonstrate that the vegetation activities decreased significantly in summer over the years. Moreover, there were significant changes in land use/cover over the past two decades. Particularly there was a sharp increase of urban and built-up area and a significant decrease of grassland and cropland. All these indicate that human activities are intensive in the East River Basin and provide valuable information for constructing scenarios for studying hydrologic impacts of LUCC.
Wang, Kai.
"December 2010."
Adviser: Yongqin Chen.
Source: Dissertation Abstracts International, Volume: 73-04, Section: A, page: .
Thesis (Ph.D.)--Chinese University of Hong Kong, 2011.
Includes bibliographical references (leaves 203-227).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstract also in Chinese.