Relevant bibliographies by topics / Hydrology Victoria Data processing

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Hydrology Victoria Data processing'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Hydrology Victoria Data processing"

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Hagai, M. "An Investigation of Kagera River Basin Land Cover Dynamics for Sustainability of Lake Victoria Water Regime." Journal of Sustainable Development 12, no. 4 (2019): 166. http://dx.doi.org/10.5539/jsd.v12n4p166.

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This paper is reporting on an investigation done to assess land cover dynamics in KRB(Kagera River Basin) (KRB) over a period of 21 years i.e.1990-2011 using Remote Sensing, Hydrology and GIS techniques as a basis for initiating policy interventions for sustainability of Lake Victoria water regime.The extent of land cover changes in the KRB have not been quantified with the view of assessing the extent of exploitation of the natural resources.The assessment is important firstly for identification of causative factors and secondly as a mechanism for formulating necessary policies and remedial measures to that effect.Specifically, Landsat 5, Landsat 7 and ETM+ (2000) satellite images were used.Eight Land Cover classes were identified namely, Forests, Woodland, Bushland, Cultivated Land, Swamps, Grassland, Bareland and Urban areas.Hydrographical data were used to assess changes in quantity of water flowing from the KRB into Lake Victoria and relating it with land cover changes in KRB at in the period of study. Spatial data processing, analysis and interpretation were carried out in ERDAS Imagine and ArcGIS software environments; while water quantity data and other non spatial data were processed and analyzed in Microsoft Excel application 2007. 
 
 The study revealed a significant decline of vegetation cover and water quantity discharged from Kagera River to Lake Victoria over the study period. This contravenes the global efforts of ecological sustainability, which urge avoidance of depletion of natural resources for maintenance for ecological balance. These results are in early warning to the Management of Lake Victoria for its potential failure towards achieving the Millennium Development Goal on responsible consumption and protection of natural resources in proximity with Lake Victoria. The Management of Lake Victoria in collaboration with other relevant authorities should thus, take remedial measures to control further depletion of vegetation cover in KRB for sustainability of Lake Victoria and its ecosystem.
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Tran, H. D., N. Muttil, and B. J. C. Perera. "Enhancing accuracy of autoregressive time series forecasting with input selection and wavelet transformation." Journal of Hydroinformatics 18, no. 5 (2016): 791–802. http://dx.doi.org/10.2166/hydro.2016.145.

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Autoregressive time series forecasting is common in different areas within water resources, which include hydrology, ecology, and the environment. Simple forecasting models such as linear regression have the advantage of fast runtime, which is attractive for real-time forecasting. However, their forecasting performance might not be acceptable when a non-linear relationship exists between model inputs and output, which necessitates the use of more sophisticated forecasting models such as artificial neural networks. This study investigates the performance and potential of a hybrid pre-processing technique to enhance the forecasting accuracy of two commonly used neural network models (feed-forward and layered recurrent neural network models) and a multiple linear regression model. The hybrid technique is a combination of significant input variable selection (using partial linear correlation) for reducing the dimensionality of the input data and input data transformation using discrete wavelet transform for decomposing the input time series into low and high frequency components. Two case study forecasting applications, namely, monthly inflow forecasting for a lake in Victoria (Australia) and weekly algal bloom predictions at a bay in Hong Kong were used to assess the forecasting ability of the models when used in conjunction with the hybrid technique. Results demonstrated that the hybrid technique can significantly improve the forecasting performance of all the models used.
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Faure, D., and P. Auchet. "Real time weather radar data processing for urban hydrology in Nancy." Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere 24, no. 8 (1999): 909–14. http://dx.doi.org/10.1016/s1464-1909(99)00102-1.

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Thorndahl, Søren, Thomas Einfalt, Patrick Willems, et al. "Weather radar rainfall data in urban hydrology." Hydrology and Earth System Sciences 21, no. 3 (2017): 1359–80. http://dx.doi.org/10.5194/hess-21-1359-2017.

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Abstract. Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value to the aforementioned emerging fields in current and future applications, but also to the analysis of integrated water systems.
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E, Băutu. "Osimin - A meteorological data platform for processing SIMIN data built on open source software." Scientific Bulletin of Naval Academy XIX, no. 1 (2018): 555–60. http://dx.doi.org/10.21279/1454-864x-18-i1-083.

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In 2003, the Romanian National Institute of Meteorology and Hydrology inaugurated National Integrated Meteorological System (SIMIN), consisting of a network of stations and instruments for measurement and detection of hydro and meteorological data, a specialized communication network, a forecasting network, and a dissemination network. With a setup cost of $55 million and a national priority role, SIMIN (implemented by Lockheed Martin) is relatively black boxed even today, using proprietary technology and software. Few institutions have direct access to the data it provides. In this paper, we present the design of a web-based software application built on open source software that allows easy access to and processing of data available in SIMIN.
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Einfalt, T., K. Arnbjerg-Nielsen, and S. Spies. "An enquiry into rainfall data measurement and processing for model use in urban hydrology." Water Science and Technology 45, no. 2 (2002): 147–52. http://dx.doi.org/10.2166/wst.2002.0040.

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Rain data are collected all over the world because water is of paramount importance to all human life. WMO has provided standards for collection and standardized data processing of daily rainfall measurements. Currently no such standards are available for gauges with a resolution suitable for urban hydrology, where the resolution in time must not exceed a few minutes. The Group on Urban Rainfall under the International Water Association has made a comparison of national standards by means of a survey of 77 questions sent to 44 countries. The paper discusses the first results of the answers of the survey. Currently tipping bucket gauges are the dominating method of obtaining high resolution rain data, but the numbers of weighing gauges and radar measurements are rapidly growing. It is necessary to try to increase the awareness of documentation of current standards and to agree on standards for measurements and data processing on an international level in the future.
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Nur, Achmad Surian, and M. Azhari Noor. "HYDROLOGICAL ASPECT OF BATANG ALAI WEIR WATERSHED DUE TO LAND USE CHANGES INTO MINING AREAS." CERUCUK 4, no. 1 (2021): 61. http://dx.doi.org/10.20527/crc.v4i1.3579.

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The policy of the Ministry of Energy and Mineral Resources that provides permits for mining production activities for PT. MCM in the Batang Alai River area has an impact on the hydrology of the area. This study will discuss the changes in land use in the Batang Alai River area, Batang Alai Timur District, Hulu Sungai Tengah to the aspects of high flow and low flow hydrology. The research method used is manual calculation with rational methods for high flow hydrology and calculations using the ArcSWAT 2012.10.1.18 for low flow hydrology. The data needed in the processing are rainfall data, DEM data, daily discharge data, climatology data, land use data, land use change data, and Batang Alai watershed data. The results of the study were that the ratio of peak discharge of land use was changed to the mining area and land use was not converted into a mining area for high flow hydrology calculations. There is an increase in plan flood discharge in the Batang Alai River if there is a change in land use into a mining area, the design flood discharge always increases in each period. Whereas for low flow hydrology is the comparison between the daily use of land use converted into a mining area and land use is not converted into a mining area, then the daily discharge results are calculated for the availability of water. The results of low-flow hydrological modeling are categorized as good and have high influence based on the Nash-Sutcliffe efficiency value grouping and the coefficient of determination, and water availability decreases if land use is converted into a mining area.
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Riley, Merilyn. "Population Prevalence Rates of Birth Defects: A Data Management and Epidemiological Perspective." Health Information Management 34, no. 3 (2005): 94–99. http://dx.doi.org/10.1177/183335830503400307.

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The Victorian Birth Defects Register (VBDR) is a population-based surveillance system with a primary function of monitoring trends in birth defects. This paper outlines the processes undertaken in Victoria, Australia, to obtain population prevalence rates of birth defects and investigates the effect on the prevalence rates of variations in collection and processing tasks. It includes all birth defects that were notified to the VBDR by 31 December 2004. The overall prevalence rate of birth defects in Victoria for 2003 was 4.0%, with an overall accuracy rate of 88%. However, this proportion varied according to what birth defects were included, the age by which birth defects were diagnosed, changes to sources of ascertainment, inclusion of terminations of pregnancy, or reporting by cases rate (infants affected) or birth defect rate (individual birth defects). Taking all of these factors into consideration, we are confident that 4.0% is an accurate population prevalence rate of birth defects in Victoria for 2003.
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Abbas, Ather, Laurie Boithias, Yakov Pachepsky, Kyunghyun Kim, Jong Ahn Chun, and Kyung Hwa Cho. "AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods." Geoscientific Model Development 15, no. 7 (2022): 3021–39. http://dx.doi.org/10.5194/gmd-15-3021-2022.

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Abstract. Machine learning has shown great promise for simulating hydrological phenomena. However, the development of machine-learning-based hydrological models requires advanced skills from diverse fields, such as programming and hydrological modeling. Additionally, data pre-processing and post-processing when training and testing machine learning models are a time-intensive process. In this study, we developed a python-based framework that simplifies the process of building and training machine-learning-based hydrological models and automates the process of pre-processing hydrological data and post-processing model results. Pre-processing utilities assist in incorporating domain knowledge of hydrology in the machine learning model, such as the distribution of weather data into hydrologic response units (HRUs) based on different HRU discretization definitions. The post-processing utilities help in interpreting the model's results from a hydrological point of view. This framework will help increase the application of machine-learning-based modeling approaches in hydrological sciences.
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Pollino, Carmel A., Pat Feehan, Michael R. Grace, and Barry T. Hart. "Fish communities and habitat changes in the highly modified Goulburn Catchment, Victoria, Australia." Marine and Freshwater Research 55, no. 8 (2004): 769. http://dx.doi.org/10.1071/mf03180.

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Evidence for the decline in native fish communities in the lowland Goulburn Catchment has been based primarily on studies investigating changes to environmental conditions as a result of river regulation. The present study aggregates historical fisheries data to spatially compare native fish communities in different parts of the catchment. Multivariate analyses demonstrate that distinctly different community compositions are found in different parts of the catchment. Eildon Dam, a deep release reservoir, has drastically altered the hydrology and water quality of the upper Goulburn River, and ordination analyses show that this has created both physical and artificial barriers to movement of native fish into the main channel. Concurrently, fisheries data from the upper main channel show the community is highly divergent compared to the remaining catchment. Further downstream, Goulburn Weir creates a barrier to fish movement between Lake Nagambie and the lower Goulburn Catchment, and alters the natural hydrological regime. Similarity Percentage analyses demonstrate that these stressors have facilitated the establishment of alien species, which dominate fish abundance in the upper and lower main channels. The current study emphasises the need to explore alternatives for improving management strategies to rehabilitate fish communities throughout the Goulburn Catchment.
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Dissertations / Theses on the topic "Hydrology Victoria Data processing"

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De, Marchi Carlo. "Probabilistic Estimation of Precipitation Combining Geostationary and TRMM Satellite Data." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14068.

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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.
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Pfaff, Thomas [Verfasser], and András [Akademischer Betreuer] Bárdossy. "Processing and analysis of weather radar data for use in hydrology / Thomas Pfaff. Betreuer: András Bárdossy." Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2013. http://d-nb.info/1033714135/34.

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Fernando, Dweepika Achela Kumarihamy. "On the application of artificial neural networks and genetic algorithms in hydro-meteorological modelling." Thesis, Hong Kong : University of Hong Kong, 1997. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18618546.

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Yan, Hongxiang. "From Drought Monitoring to Forecasting: a Combined Dynamical-Statistical Modeling Framework." PDXScholar, 2016. http://pdxscholar.library.pdx.edu/open_access_etds/3292.

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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.
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Tatnall, Arthur, and mikewood@deakin edu au. "A curriculum history of business computing in Victorian Tertiary Institutions from 1960-1985." Deakin University, 1993. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20051201.145413.

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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.
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Gustafson, Nathaniel Lee. "A Confidence-Prioritization Approach to Data Processing in Noisy Data Sets and Resulting Estimation Models for Predicting Streamflow Diel Signals in the Pacific Northwest." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3294.

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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.
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Viljoen, Sarel Johannes. "Creation of a hydrological modelling environment to assist in the decision making of water-related activities." Thesis, Bloemfontein : Central University of Technology, Free State, 2007. http://hdl.handle.net/11462/96.

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Thesis (M. Tech.) -- Central University of Technology, Free State, 2007<br>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.
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Tiwari, Prava. "Updating the web-based geographic information system of the Water Resources Institute." CSUSB ScholarWorks, 2008. https://scholarworks.lib.csusb.edu/etd-project/3407.

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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.
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Bollaert, M. J. "Development of a geographic data model for hydrological modelling." Thesis, 2006. http://hdl.handle.net/10413/434.

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Kime, Dylan B. "The development and assessment of a prototype water accounting system for South Africa using the ACRU2000 and MIKE BASIN models." Thesis, 2010. http://hdl.handle.net/10413/4963.

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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.<br>Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2010.
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Books on the topic "Hydrology Victoria Data processing"

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Xing, Cai, and Yeh T. C, eds. Quantitative information fusion for hydrological sciences. Springer, 2008.

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McCuen, Richard H. Microcomputer applications in statistical hydrology. Prentice Hall, 1993.

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P, Singh V., and Fiorentino M. 1955-, eds. Geographical information systems in hydrology. Kluwer Academic Publishers, 1996.

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Roald, Lars. FRIENDS in hydrology. International Association of Hydrological Sciences, 1989.

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Hoggan, Daniel H. Computer-assisted floodplain hydrology and hydraulics. 2nd ed. McGraw-Hill, 1997.

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Computer-assisted floodplain hydrology and hydraulics. McGraw-Hill, 1989.

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1967-, Gasmelseid Tagelsir Mohamed, ed. Handbook of research on hydroinformatics: Technologies, theories and applications. Information Science Reference, 2010.

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Stochastic subsurface hydrology. Prentice-Hall, 1993.

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Computational hydraulics and hydrology: An illustrated dictionary. CRC Press, 2004.

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Emergence, evolution, intelligence: Hydroinformatics : a study of distributed and decentralised computing using intelligent agents. A.A. Balkema, 1996.

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Book chapters on the topic "Hydrology Victoria Data processing"

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Şen, Zekâi. "Hydrology." In Earth Systems Data Processing and Visualization Using MATLAB. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-01542-8_3.

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Jensen, J. R. "Processing Remotely Sensed Data: Hardware and Software Considerations." In Remote Sensing in Hydrology and Water Management. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59583-7_3.

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Algazi, V. Ralph. "Digital Processing of Satellite Data: Information Extraction and Potential Applications to Hydrology." In Precipitation Analysis for Hydrologic Modeling. American Geophysical Union, 2013. http://dx.doi.org/10.1029/sp004p0001.

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Banhatti, Aniruddha Gopal, and Paresh Chandra Deka. "Effects of Data Pre-processing on the Prediction Accuracy of Artificial Neural Network Model in Hydrological Time Series." In Urban Hydrology, Watershed Management and Socio-Economic Aspects. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40195-9_21.

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"Data Processing in Hydrology." In Handbook of Engineering Hydrology (Three-Volume Set). CRC Press, 2018. http://dx.doi.org/10.1201/b16695-9.

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"Data Processing in Hydrology." In Handbook of Engineering Hydrology. CRC Press, 2014. http://dx.doi.org/10.1201/b15625-8.

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Paracha, Zahir Javed, and Akhtar Kalam. "Intelligent Techniques for the Analysis of Power Quality Data in Electrical Power Distribution System." In Handbook of Research on Industrial Informatics and Manufacturing Intelligence. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0294-6.ch024.

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This chapter is about the intelligent techniques for the analysis of power quality problems in electrical power distribution system. The problems related with electrical power industry are becoming more widespread, complex, and diversified. The behaviour of power distribution systems can be monitored effectively using artificial intelligence techniques and methodologies. There is a need of understanding the power system operations from power utility perspectives and application of computational intelligence methods to solve the problems of the power industry. The real power quality (PQ) data is taken from a power utility in Victoria Australia. Principal Component Analysis Technique (PCAT) is used to reduce the large number of PQ data attributes of the power distribution system. After the pre-processing of PQ data using PCAT, intelligent computational techniques will be used for the analysis of power quality data. Neural network techniques will be employed to estimate the values of PQ parameters of the power distribution system. The Feed Forward Back Propagation (FFBP) neural network and Recurrent Neural Networks (RNN) are used for intelligent estimation of PQ data. The results obtained through these intelligent techniques are compared with the real data of power utility in Victoria, Australia for stability, reliability and enhanced power systems performance.
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Sikder, Iftikhar U., and Santosh K. Misra. "Agent-Based Semantic Interoperability of Geo-Services." In Methodological Advancements in Intelligent Information Technologies. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-970-0.ch007.

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This chapter proposes a multi-agent based framework that allows multiple data sources and models to be semantically integrated for spatial modeling in business processing. The authros introduce a multiagent system (OSIRIS – Ontology-based Spatial Information and Resource Integration Services) to semantically interoperate complex spatial services and integrate them in a meaningful composition. The advantage of using multi-agent collaboration in OSIRIS is that it obviates the need for end-user analysts to be able to decompose a problem domain to subproblems or to map different models according to what they actually mean. The authors also illustrate a multi-agent interaction scenario for collaborative modeling of spatial applications using the proposed custom feature of OSIRIS using Description Logics. The system illustrates an application of domain ontology of urban environmental hydrology and evaluation of decision maker’s consequences of land use changes. In e-government context, the proposed OSIRIS framework works as semantic layer for one stop geospatial portal.
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Conference papers on the topic "Hydrology Victoria Data processing"

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Al-Jabri, Y., and M. Urosevic. "The Applicability of Vibroseis Sources For the Land Seismic Time-Lapse Surveys;CO2 Sequestration Field, Otway Basin, Victoria, Australia." In EAGE Vibroseis Workshop - Vibroseis acquisition and processing half century later, new developments in data quality and productivity. European Association of Geoscientists & Engineers, 2008. http://dx.doi.org/10.3997/2214-4609.20147525.

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Bernatowicz, Anna, and Adam Lyszkowicz. "Present State of Lake Studies from Satellite Altimetry – a Case Study in Poland." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.164.

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Satellite radar altimetry is a successful technique for monitoring elevations of continental surface water. The surface water level is measured within a terrestrial reference frame with a repeatability varying from 10 to 35 days depending on the orbit cycle of the satellite. With several decades of technique refinement; current data processing can be fairly simple or complex depending on the mission and the tracking methods. Data acquisition is not affected by weather conditions; but the technique can have a number of limitations. However; the technique is sufficiently advanced to have allowed a number of inland water case studies. Focusing on the large lakes; the links between lake evolution and the local climate cycle on seasonal to interannual timescales can be explored; and water storage balance for water management also can be brought into focus. This article reviews present day lake level monitoring and the case study of the Łebsko lake in Poland. First the basic principle of satellite altimetry, current altimetry missions, hydrology application and lake and reservoir altimetry measurements in web sites are shortly describe. Next the investigation of the surface of the Łebsko lake in Poland was carried out. From our study reveals that altimetry could provide a promising future for true global lake studies with height and width observation of all targets with centimeter accuracy.
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