Дисертації з теми "Rain forecasting"
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DeSordi, Steven Paul. "Utah local area model sensitivity to boundary conditions for summer rain simulations." Wright-Patterson AFB, Ohio : Dept. of the Air Force, 1996. http://stinet.dtic.mil/cgi-bin/fulcrum%5Fmain.pl?database=ft%5Fu2&searchid=0&keyfieldvalue=ADA319136&filename=%2Ffulcrum%2Fdata%2FTR%5Ffulltext%2Fdoc%2FADA319136.pdf.
Повний текст джерелаTitle from web page (viewed Oct. 30, 2003). "96-084." "August 1996." Includes bibliographical references p. [110]-112. Also available in print version.
Li, Jing. "Clustering and forecasting for rain attenuation time series data." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-219615.
Повний текст джерелаClustering is een van de unsupervised learning algorithmen om groep soortgelijke objecten in dezelfde cluster en de objecten in dezelfde cluster zijn meer vergelijkbaar met elkaar dan die in de andere clusters. Prognoser är att göra förutspårningar baserade på övergående data och effektiva artificiella intelligensmodeller för att förutspå datautveckling, som kan hjälpa till att fatta lämpliga beslut. Dataseten som används i denna avhandling är signaldämpningstidsseriedata från mikrovågsnätverket. Mikrovågsnät är kommunikationssystem för att överföra information mellan två fasta platser på jorden. De kan stödja ökade kapacitetsbehov i mobilnät och spela en viktig roll i nästa generationens trådlösa kommunikationsteknik. Men inneboende sårbarhet för slumpmässig fluktuering som nedbörd kommer att orsaka betydande nätverksförstöring. I den här avhandlingen används K-medel, Fuzzy c-medel och 2-state Hidden Markov Model för att utveckla ett steg och tvåstegs regen dämpning dataklyvningsmodeller. Prognosmodellerna är utformade utifrån k-närmaste granne-metoden och implementeras med linjär regression för att förutsäga realtidsdämpning för att hjälpa mikrovågstransportnät att mildra regnpåverkan, göra rätt beslut före tid och förbättra den allmänna prestandan.
Karlsson, Magnus Sven. "NEAREST NEIGHBOR REGRESSION ESTIMATORS IN RAINFALL-RUNOFF FORECASTING." Diss., The University of Arizona, 1985. http://hdl.handle.net/10150/282088.
Повний текст джерелаGorugantula, Srikanth V. L. "A GPS-IPW Based Methodology for Forecasting Heavy Rain Events." Thesis, Virginia Tech, 2002. http://hdl.handle.net/10919/10145.
Повний текст джерелаMaster of Science
Ryall, Gill. "An automated system for generating very-short-range forecasts of precipitation." Thesis, University of Sussex, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284079.
Повний текст джерелаPettegrew, Brian P. "On methods of precipitation efficiency estimation /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p1422951.
Повний текст джерелаMichaud, Jene Diane. "RAINFALL-RUNOFF MODELING OF FLASH FLOODS IN SEMI-ARID WATERSHEDS." Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ), 1992. http://hdl.handle.net/10150/614156.
Повний текст джерелаTsang, Fan Cheong. "Advances in flood forecasting using radar rainfalls and time-series analysis." Thesis, Lancaster University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.481184.
Повний текст джерелаCataldo, Edmund F. "Evaluation of the SSM/I rain analyses for selective storms in the ERICA project." Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA241321.
Повний текст джерелаThesis Advisor(s): Wash, Carlyle H. Second Reader: Nuss, Wendell A. "September 1990." Description based on title screen viewed on December 17, 2009. DTIC Descriptor(s): Weather forecasting, satellite meteorology, uncertainty, polarization, ships, coastal regions, light, rates, theses, radar, regression analysis, precipitation, solutions(general), rain, winter, rainfall intensity, storms, equations, cyclones, channels, corrections, temperate regions, cyclogenesis, algorithms, temperature. DTIC Identifier(s): Rainfall intensity, erica project, ssm/i(special sensor microwave/images). Author(s) subject terms: Microwave, ERICA, SSM/I, precipitation forecasting, rain. Includes bibliographical references (p. 81-82). Also available in print.
Karnieli, Arnon 1952. "Storm runoff forecasting model incorporating spatial data." Diss., The University of Arizona, 1988. http://hdl.handle.net/10150/191138.
Повний текст джерелаChapman, Matthew. "Spatial forecasting of air pollution in urban environments : a geographical information system approach." Thesis, University of Brighton, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271974.
Повний текст джерелаHanni-Wells, Michael R. "A climatology of lower tropospheric environments during freezing rain events in the south-central United States." Virtual Press, 2004. http://liblink.bsu.edu/uhtbin/catkey/1286603.
Повний текст джерелаDepartment of Geography
Hajjam, Sohrab. "Real-time flood forecasting model intercomparison and parameter updating rain gauge and weather radar data." Thesis, University of Salford, 1997. http://usir.salford.ac.uk/43019/.
Повний текст джерелаVavae, Hilia. "A simple forecasting scheme for predicting low rainfalls in Funafuti, Tuvalu." The University of Waikato, 2008. http://hdl.handle.net/10289/2435.
Повний текст джерелаDupigny-Giroux, Lesley-Ann. "Techniques for rainfall estimation and surface characterization over northern Brazil." Thesis, McGill University, 1996. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=40345.
Повний текст джерелаThe work present a more effective algorithm to estimate rainfall from both the cold and warm cloud types present. Using a decision-tree methodology, the analysis yields rainfall estimates over the 0-21 mm range. Because seasonal variations in rainfall produce differences in vegetation, soils and hydrologic responses, Principal Components Analysis was used to examine these land surface responses. Individual components and component pairings were useful in identifying variations in vegetation density, geobotanical differences and drainage characteristics. The presence of cloud cover was found to dampen the land surface information that could be extracted. Landsat Thematic Mapper (TM) imagery was then used to produce a moisture index which characterizes surface wetness in relation to other features present in a scene. The multispectral combination of TM bands 1, 4 and 6 allowed for the separation of the surface types present, in locational space. This space was defined by an open-ended triange made up of a vertical "water line", a horizontal line of equal vegetation density; and a negatively-slopping iso-moisture line. The stability of the moisture index was influenced by varying scale and seasonal conditions.
In the drought conditions that prevailed in 1991-1992, these methods provide important additions to existing drought monitoring approaches in the Brazilian northeast. Further calibration is required in order to extend their applicability to other geographical regions and time frames.
Paduru, Anirudh. "Fast Algorithm for Modeling of Rain Events in Weather Radar Imagery." ScholarWorks@UNO, 2009. http://scholarworks.uno.edu/td/1097.
Повний текст джерелаHeneker, Theresa M. "An improved engineering design flood estimation technique: removing the need to estimate initial loss /." Title page, abstract and table of contents only, 2002. http://web4.library.adelaide.edu.au/theses/09PH/09phh4989.pdf.
Повний текст джерела"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).
Dravitzki, Stacey Maree. "Precipitation in the Waikato River catchment : a thesis submitted to the Victoria University of Wellington in fulfilment of the requirements for the degree of Doctor of Philosophy in Geophysics /." ResearchArchive@Victoria e-thesis, 2009. http://researcharchive.vuw.ac.nz/handle/10063/955.
Повний текст джерелаHsu, Kuo-Lin, Soroosh Sorooshian, Xiaogang Gao, and Hoshin Vijai Gupta. "Rainfall estimation from satellite infrared imagery using artificial neural networks." Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ), 1997. http://hdl.handle.net/10150/615703.
Повний текст джерелаRodgers, William N. "Land Cover Change and its Impacts on a Flash Flood-Producing Rain Event in Eastern Kentucky." TopSCHOLAR®, 2014. http://digitalcommons.wku.edu/theses/1363.
Повний текст джерелаHsu, Kuo-lin 1961. "Rainfall estimation from satellite infrared imagery using artificial neural networks." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/191209.
Повний текст джерелаDolcine, Leslie. "Prévision quantitative à très courte échéance de la pluie : modèle global adapté à l'information radar." Grenoble 1, 1997. http://www.theses.fr/1997GRE10067.
Повний текст джерелаVilanculos, Agostinho Chuquelane Fadulo. "The use of hydrological information to improve flood management-integrated hydrological modelling of the Zambezi River basin." Thesis, Rhodes University, 2015. http://hdl.handle.net/10962/d1018915.
Повний текст джерелаRamesh, Chirania Saloni. "Forecasting Model for High-Speed Rail in the United States." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/76878.
Повний текст джерелаMaster of Science
Maier, George. "Forecasting ridership impacts of transit oriented development at MARTA rail stations." Thesis, Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54477.
Повний текст джерелаPELZ, ZACHARY L. "A STATION LEVEL ANALYSIS OF COMPETING LIGHT- RAIL ALTERNATIVES IN CINCINNATI'S EASTERN CORRIDOR." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1179851133.
Повний текст джерелаYeun-Touh, Li. "High Speed Rail Demand Adaptation and Travellers' Long-term Usage Patterns." 京都大学 (Kyoto University), 2016. http://hdl.handle.net/2433/217154.
Повний текст джерелаSamuel, Jos Martinus. "Effects of multi-scale rainfall variability on flood frequency : a comparative study of catchments in Perth, Newcastle and Darwin, Australia." University of Western Australia. School of Environmental Systems Engineering, 2008. http://theses.library.uwa.edu.au/adt-WU2009.0066.
Повний текст джерелаForooqi, A. Masood. "Ridership studies for the proposed Florida high speed rail system." FIU Digital Commons, 1990. http://digitalcommons.fiu.edu/etd/3254.
Повний текст джерелаGarcia, Jean Rodrigo 1980. "Estudo do comportamento carga VS recalque de estacas raiz carregadas a compressão." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/258763.
Повний текст джерелаDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Civil, Arquitetura e Urbanismo
Made available in DSpace on 2018-08-09T00:23:04Z (GMT). No. of bitstreams: 1 Garcia_JeanRodrigo_M.pdf: 20549074 bytes, checksum: f2026225c4a01801d604ae04aad3497a (MD5) Previous issue date: 2006
Resumo: Nesta pesquisa analisa-se o comportamento da curva carga vs recalque de estaca isolada carregada à compressão, através do emprego de métodos de previsão. Foram ensaiadas duas estacas raiz, uma com 23m de comprimento e 31cm de diâmetro, e outra com 12m de comprimento e 41cm de diâmetro, no intuito de atribuir o comportamento da interação solo-estaca, a um ou outro fator característico do elemento de fundação. Para isso, foram realizadas provas de carga do tipo lenta. O subsolo local é composto por solo proveniente de diabásio, constituído basicamente de duas camadas, a primeira de argila silto-arenosa (O a 6,5m de profundidade) e a segunda de silte argilo-arenoso (6,5-23m de profundidade), ambas as camadas são predominantes da região de Campinas (SP) e de grande parte das regiões sul e sudeste do Brasil. A prova de carga foi instrumentada de maneira a se obter os dados do mecanismo de transferência de carga e de deslocamento em profundidade. Dessa forma, obteve-se o valor da carga de ruptura, bem como, da respectiva carga admissível (Qadm),através da completa solicitação por atrito lateral e por resistência de ponta, apresentados pela interação do sistema solo-estaca, ou convencionando-se uma ruptura em função de um recalque limite ou ainda de critérios de ruptura fisica, como o método da rigidez (Décourt), Chin e outros. De maneira geral, analisa-se, de maneira critica, os métodos de previsão de recalque e de curva carga vs recalque, comparando os resultados reais com os previstos, através dos métodos teóricos e empíricos para o recalque do elemento fundação quando submetido à carga admissível estimada (Qadm)e para a curva carga vs recalque. Dessa forma, pretende-se chegar a algum entendimento sobre a interação solo-estrutura e seu modelo de transferência de carga para o solo
Abstract: In this research, the behavior of the curve load versus settlement ofloaded isolated pile to the compression is analyzed, through forecast methods. Two root piles had been assayed, one with 23m oflength and 31 cm of diameter, and the other with length of 12 m and 41 cm of diameter, in order to attribute the behavior of the interaction ground-pile to one or another characteristic factor of the foundation elemento For this, load tests of the slow type had been carrried out. The local subsoil is composed of ground of diabásio, consisting basically of two layers: the first one of silt-sandy clay (6,5m - 23m of depth) and second silt clay-sandy (6,5 - 23m of depth), both layers are predominant in the region ofCampinas (SP) and in a great part ofthe southem and southeastem regions ofBrazil. The load test was instrumented to get the data of the mechanism of transference of load and displacement in depth. Thus, the value of the rupture load was obtained, as well as the respective permissible load (Qadm),through the complete request for lateral attrition and tip resistance, presented by the interaction of the ground-pile system or stipulating a rupture related to a stress limit or still of criteria of physical rupture, as the method of the rigidity (Décourt), Chin and others. In general, the methods of forecast of settlement and curve load versus stresses are analysed in a critical way, by comparing the real results with the foreseen ones, through theoretical by empirical methods for the settlement of the foundation element when. submitted to the esteemed permissible load (Qadm) and for the curve load versus settlement. Therefore, there is the intention to come to an agreement about the groundstructure interaction and its model of load transference to the ground
Mestrado
Geotecnia
Mestre em Engenharia Civil
Tirivarombo, Sithabile. "Climate variability and climate change in water resources management of the Zambezi River basin." Thesis, Rhodes University, 2013. http://hdl.handle.net/10962/d1002955.
Повний текст джерелаWan, Been-Lih, and 萬本立. "Real-time Flood Forecasting by Considering the Rain-burst Effect." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/14111022041155049899.
Повний текст джерела國立臺灣大學
生物環境系統工程學研究所
100
In recent years, the extreme rainfall events become more and more so that result in many flood disasters that make residents’ lives and property suffered a serious threat. In order to reduce flood damage, real-time flood forecasting has become an important research topic. Research analysis was processed with flood events of Tseng-Wen Reservoir Watershed and Chi-Lan River basin. This study constituted several forecasting models of hourly stream discharge based on AR(2) model and Naïve model, and correct the problem of forecasting time lag phenomenon by considering rainfall data. The discussion of rainfall data is divided in two parts. First part is that discuss the relationship between increment of rainfall and increment of discharge. By identify the increment of rainfall (rain-burst) which can make discharge significantly increase in a short time, we can establish the function of relationship between increment of rainfall and increment of discharge and combined with AR(2) model to correct the problem of forecasting time lag phenomenon which result from rain-burst effect. Second part is that apply the concept of unit hydrograph to establish response function between rainfall difference and discharge difference by linear regression, use data of rainfall difference before prediction time to estimate discharge difference on prediction time and combined with Naïve model to forecast hourly discharge. By considering the trend of rainfall variations, significantly improve the problem of forecasting time lag phenomenon. The results of research shows that AR(2) model by considering the rain-burst effect can improve the problem of forecasting time lag phenomenon and enhance CP value by reducing the prediction error on peak time. And the performance of Naïve model which combined with response function is significantly better than other models. This result demonstrates that considering the trend of rainfall variations is very effective to improve the problem of forecasting time lag phenomenon.
Adhikary, Sajal Kumar. "Optimal Design of a Rain Gauge Network to Improve Streamflow Forecasting." Thesis, 2017. https://vuir.vu.edu.au/35054/.
Повний текст джерелаPologne, Lawrence Cai Ming. "Spatiotemporal variability and prediction of rainfall over the eastern Caribbean." Diss., 2005. http://etd.lib.fsu.edu/theses/available/etd-07112005-162948/.
Повний текст джерелаAdvisor: Dr. Ming Cai, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed Sept. 19, 2005). Document formatted into pages; contains x, 60 pages. Includes bibliographical references.
Martinez, Carlos J. "Seasonal Climatology, Variability, Characteristics, and Prediction of the Caribbean Rainfall Cycle." Thesis, 2021. https://doi.org/10.7916/d8-byp7-1b34.
Повний текст джерела"Long-range summer rainfall: forecast of Hong Kong." Chinese University of Hong Kong, 1990. http://library.cuhk.edu.hk/record=b5886567.
Повний текст джерелаThesis (M.Phil.)--Chinese University of Hong Kong, 1990.
Bibliography: leaves 92-101.
ACKNOWLEDGEMENTS
ABSTRACT
LIST OF FIGURES --- p.iii
LIST OF TABLES --- p.iv
CHAPTER
Chapter I --- INTRODUCTION --- p.1
Chapter 1.1 --- Background --- p.1
Chapter 1.2 --- Significance of the Research --- p.3
Chapter 1.3 --- Objectives of the Research --- p.5
Chapter 1.4 --- Organization of the Research --- p.5
Chapter II --- LITERATURE REVIEW --- p.7
Chapter 2.1 --- Introduction --- p.7
Chapter 2.2 --- Development of Long-Range Forecasting Technique --- p.8
Chapter 2.3 --- Available Techniques of Long-Range Forecast --- p.9
Chapter 2.3.1 --- Analogs and persistence --- p.10
Chapter 2.3.2 --- Statistical modelling --- p.12
Chapter 2.3.3 --- Atmosphere-ocean interaction --- p.17
Chapter 2.3.4 --- Cycles and time series --- p.18
Chapter 2.3.5 --- Numerical modelling --- p.19
Chapter 2.4 --- Rainfall Prediction in Hong Kong --- p.21
Chapter III --- RAINFALL OF HONG KONG --- p.24
Chapter 3.1 --- Climatic Feature --- p.24
Chapter 3.2 --- The Causes of Hong Kong Rainfall --- p.26
Chapter 3.2.1 --- Tropical cyclone --- p.26
Chapter 3.2.2 --- Trough or front --- p.28
Chapter IV --- METHODOLOGY --- p.31
Chapter 4.1 --- Introduction --- p.31
Chapter 4.2 --- Empirical Orthogonal Function (EOF) Analysis --- p.32
Chapter 4.2.1 --- What's EOF --- p.32
Chapter 4.2.2 --- Why use EOF --- p.34
Chapter 4.3 --- Discriminant Analysis --- p.36
Chapter 4.4 --- Data Base --- p.37
Chapter 4.5 --- Computation Procedures --- p.40
Chapter 4.6 --- Analysis of Forecast Capability --- p.44
Chapter V --- THE RESULT AND ANALYSIS OF PREDICTION MODEL --- p.48
Chapter 5.1 --- The result of EOF analysis --- p.48
Chapter 5.1.1 --- Extraction of eigenvectors and eigenvalues --- p.48
Chapter 5.1.2 --- Spatial and Temporal variation of eigenvector pattern --- p.52
Chapter 5.2 --- Accuracy of the prediction model --- p.53
Chapter 5.2.1 --- Introduction --- p.53
Chapter 5.2.2 --- The forecast accuracy from each month --- p.54
Chapter 5.2.2.1 --- The forecast accuracy made by October --- p.54
Chapter 5.2.2.2 --- The forecast accuracy made by November --- p.56
Chapter 5.2.2.3 --- The forecast accuracy made by December --- p.58
Chapter 5.2.2.4 --- The forecast accuracy made by January --- p.58
Chapter 5.2.2.5 --- The forecast accuracy made by February --- p.61
Chapter 5.2.2.6 --- The forecast accuracy made by March --- p.61
Chapter 5.2.2.7 --- The forecast accuracy made by April --- p.64
Chapter 5.2.3 --- Optimal length of dependent data --- p.64
Chapter 5.2.4 --- Analysis the prediction results --- p.67
Chapter 5.2.5 --- Comparison between the method used in this study with those methods adopted by ROHK --- p.69
Chapter 5.2.5.1 --- Introduction --- p.69
Chapter 5.2.5.2 --- Comparison of the forecast accuracy between two studies --- p.70
Chapter VI --- CONCLUSION --- p.73
Chapter 6.1 --- Summary of Findings --- p.73
Chapter 6.2 --- Limitations of the Research --- p.75
Chapter 6.3 --- Prospects of the Research --- p.76
APPENDICES --- p.78
LIST OF CITED REFERENCES --- p.92
LIST OF READING MATERIALS --- p.97
Dickey, Jeffrey James Elsner James B. "Improved flood prediction from basin elevation distribution." 2006. http://etd.lib.fsu.edu/theses/available/07092006-103933.
Повний текст джерелаAdvisor: James B. Elsner, Florida State University, College of Social Sciences, Dept. of Geography. Title and description from dissertation home page (Sept. 19, 2006). Document formatted into pages; contains x, 90 pages. Includes bibliographical references.
"Improved estimation of catchment rainfall for continuous simulation modelling." Thesis, 2005. http://hdl.handle.net/10413/2685.
Повний текст джерелаThesis (M.Sc.)-University of KwaZulu-Natal, 2005.
Purdie, Jennifer. "Model development for seasonal forecasting of hydro lake inflows in the Upper Waitaki Basin, New Zealand /." 2005. http://adt.waikato.ac.nz/public/adt-uow20070223.140731/index.html.
Повний текст джерелаHsu, Kuo-lin. "Rainfall estimation from satellite infrared imagery using artificial neural networks." 1996. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_e9791_1996_410_sip1_w.pdf&type=application/pdf.
Повний текст джерелаHallowes, Jason Scott. "Evaluation of a methodology to translate rainfall forecasts into runoff forecasts for South Africa." Thesis, 2002. http://hdl.handle.net/10413/4513.
Повний текст джерелаThesis (M.Sc.)-University of Natal, Pietermaritzburg, 2002.
Hajani, Evan. "Impact of climate change on design rainfall." Thesis, 2018. http://hdl.handle.net/1959.7/uws:49274.
Повний текст джерелаJayathissa, Halvithana A. G. [Verfasser]. "Combined statistical and dynamic modeling for real time forecasting of rain induced landslides in Matara district, Sri Lanka : a case study / vorgelegt von Halvithana A. G. Jayathissa." 2010. http://d-nb.info/1010181009/34.
Повний текст джерелаLi, Liang-Hann, and 李亮翰. "Establishment of the Turbidity Forecasting Model Using the ANN Method to Investigate the Impact of Heavy Rain on the Water Treatment Plant Operation-Case Study on Jhihtan Water Treatment Plant." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/05218349966423434282.
Повний текст джерела明志科技大學
環境與資源工程研究所
101
In Taiwan, turbidities of rivers are getting high due to the unstable soil intrusion into water during rainy seasons which rainfall became more frequent and more intense. This situation impacts the operation of water treatment plants, which lower the amount of water supply or even influence the downstream users. The high turbidity occurred at upstream is caused by many factors, such as collapsed slope due to rainstorm, river regulation works at upstream, sediment releasing from reservoir, etc. The high turbidity usually causes water treatment plants unable to handle it due to too much sludge produced in the settling and dewatering processes or fail to meet the effluent standards. The Jhihtan Water Treatment Plant at the upstream of Xindan River was demonstrated as an example in the study. The factors such as flow rate, rainfall and cumulative rainfalls at upper streams of the watershed are analyzed by ANOVA method to find the higher correlated factors, and using them to build an ANN model to predict the turbidity of Jhihtan water intake point. Then, discuss what influences the turbidity caused to water treatment plant's operation are, and what kind of responses the water treatment plant can take under this situation. As the result, rainfall has a higher correlation coefficient to turbidity; therefore rainfall is chosen as the input factor of the turbidity predicting model. After the training and validation processes, the model is quite useful. During the rainstorm periods, the possible turbidity data will be predicted by inputing the instant rainfall data into the turbidity model and provide them to the water treatment plants. The operators in Jhihtan Treatment Plant use this information to control the chemical dosage and intake water based on the predicted turbidity. In this study, the mass balance method is used to calculate the sludge production under high turbidity conditions. According to the Design and Operation Experience in Water Supply Facilities, 4 times of maximum daily sludge volume as designed is used to adjust the intake water. Then a diagram of intake water versus sludge production under high turbidity situations was setup which provides as a control basis to the operators in Jhihtan Treatment Plant.
Heneker, Theresa Michelle. "An improved engineering design flood estimation technique: removing the need to estimate initial loss." 2002. http://web4.library.adelaide.edu.au/theses/09PH/09phh4989.pdf.
Повний текст джерела"Rainfall derivatives for Hong Kong Disneyland." 2003. http://library.cuhk.edu.hk/record=b5891383.
Повний текст джерелаThesis (M.B.A.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (leaves 92-93).
ABSTRACT --- p.ii
TABLE OF CONTENT --- p.iii
CHAPTER
Chapter 1. --- COMPANY PROFILE --- p.1
The Walt Disney Parks --- p.1
Hong Kong Disneyland --- p.1
Location --- p.1
Park Developer & Operator --- p.2
Financing --- p.2
Infrastructure --- p.3
Schedule of Operation --- p.4
Chapter 2. --- HONG KONG DISNEYLAND BUSINESS MODEL --- p.6
Revenue Model --- p.7
Customer Base --- p.7
Pricing Strategy --- p.8
Financial Performance Variable --- p.9
Risk Management Program --- p.10
The Walt Disney Company Risk Management --- p.10
HKDL Risk Management --- p.13
Risk Management on Book Record --- p.13
Chapter 3. --- PRECIPITATION RISK EXPOSURE --- p.15
Introduction to Precipitation --- p.15
Distinguish between Weather and Climate --- p.16
Rainfall Risk Exposure --- p.16
Precipitation in Hong Kong --- p.17
Overview --- p.17
Rainstorm Warning System --- p.18
Practices on Rainy Days --- p.20
Theme Park Industry --- p.20
The Ocean Park --- p.21
Rainfall Risk Mitigation --- p.21
Chapter 4. --- WEATHER DERIVATIVES --- p.24
Evolution --- p.24
The Birth of Weather Derivatives --- p.24
Weather Risk Management Association --- p.24
Year 1999 --- p.25
Year 2000 --- p.25
Year 2001 --- p.26
Year 2002 --- p.26
Precipitation Derivatives --- p.27
Market & Market Players --- p.28
Types of Product --- p.30
Index Derivatives --- p.30
Event-Basis Derivatives --- p.32
Chapter 5. --- Hedging Against Rainfall Risk with Weather Derivatives --- p.33
Formation of Hedging Strategy --- p.34
Hedging Objectives --- p.34
Hedging Target --- p.35
Dimension of Precipitation Impacts --- p.35
Normal Revenue without Rainfall Risk --- p.40
Revenue Forecasting for Year 1 --- p.41
Specifications on the Contracts --- p.46
Chapter 6. --- General Recommendations to HKDL for hedging with all kinds of Rainfall Derivatives --- p.49
Choice of Market and Counter Parties --- p.49
Index Model Design --- p.50
Dimensions of Variables & Time Scale --- p.50
Accumulated Rainfall Index --- p.51
Methodologies of Rainfall Measurements --- p.54
Location of Rainfall Measuring Stations --- p.54
Measuring Instrument --- p.56
Historical Data Consistency --- p.58
Data Availability and Reliability --- p.59
Choice of Strike Level --- p.59
Tick Size and Maximum Payments --- p.62
Pricing Approach --- p.63
Chapter 7. --- Example of Rainfall Derivatives --- p.66
Black/Red Rainstorm Signal Call --- p.66
Specifications --- p.66
Revenue model under Different Scenario --- p.68
Chapter 8. --- Portfolio Management --- p.70
Risk Management Information System --- p.70
Issues on Book Keeping --- p.71
Chapter 9. --- CONCULSION --- p.72
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Повний текст джерелаThesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2012.
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Повний текст джерелаThesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2007.
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Повний текст джерелаLanka, Karthikeyan. "Predictability of Nonstationary Time Series using Wavelet and Empirical Mode Decomposition Based ARMA Models." Thesis, 2013. http://etd.iisc.ernet.in/2005/3363.
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