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Статті в журналах з теми "Multivariate rainfall analysis"
Nam, Woo-Sung, Tae-Soon Kim, Ju-Young Shin, and Jun-Haeng Heo. "Regional Rainfall Frequency Analysis by Multivariate Techniques." Journal of Korea Water Resources Association 41, no. 5 (May 25, 2008): 517–25. http://dx.doi.org/10.3741/jkwra.2008.41.5.517.
Повний текст джерелаLiu, Chenglin, Yuwen Zhou, Jun Sui, and Chuanhao Wu. "Multivariate frequency analysis of urban rainfall characteristics using three-dimensional copulas." Water Science and Technology 2017, no. 1 (March 7, 2018): 206–18. http://dx.doi.org/10.2166/wst.2018.103.
Повний текст джерелаFontanazza, C. M., G. Freni, G. La Loggia, and V. Notaro. "Uncertainty evaluation of design rainfall for urban flood risk analysis." Water Science and Technology 63, no. 11 (June 1, 2011): 2641–50. http://dx.doi.org/10.2166/wst.2011.169.
Повний текст джерелаMrad, D., S. Dairi, S. Boukhari, and Y. Djebbar. "Applied multivariate analysis on annual rainfall in the northeast of Algeria." Journal of Water and Climate Change 11, no. 4 (May 15, 2019): 1165–76. http://dx.doi.org/10.2166/wcc.2019.272.
Повний текст джерелаJiang, Xinyu, Lijiao Yang, and Hirokazu Tatano. "Assessing Spatial Flood Risk from Multiple Flood Sources in a Small River Basin: A Method Based on Multivariate Design Rainfall." Water 11, no. 5 (May 17, 2019): 1031. http://dx.doi.org/10.3390/w11051031.
Повний текст джерелаGaitan, S., and J. A. E. ten Veldhuis. "Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks." Proceedings of the International Association of Hydrological Sciences 370 (June 11, 2015): 9–14. http://dx.doi.org/10.5194/piahs-370-9-2015.
Повний текст джерелаAraújo, Winicius Santos, Francisco Assis Saviano Souza, José Ivaldo Barbosa de Brito, and Lourivaldo Mota Lima. "Estudo Pluvial no Nordeste do Brasil Utilizando Análise Multivariada (Rain Study in Northeast Brazil Using Multivariate Analysis)." Revista Brasileira de Geografia Física 5, no. 3 (November 5, 2012): 448. http://dx.doi.org/10.26848/rbgf.v5i3.232781.
Повний текст джерелаNam, Woosung, Hongjoon Shin, Younghun Jung, Kyungwon Joo, and Jun-Haeng Heo. "Delineation of the climatic rainfall regions of South Korea based on a multivariate analysis and regional rainfall frequency analyses." International Journal of Climatology 35, no. 5 (October 28, 2014): 777–93. http://dx.doi.org/10.1002/joc.4182.
Повний текст джерелаElesbon, Abrahão A. A., Demetrius D. da Silva, Gilberto C. Sediyama, Hugo A. S. Guedes, Carlos A. A. S. Ribeiro, and Celso B. de M. Ribeiro. "Multivariate statistical analysis to support the minimum streamflow regionalization." Engenharia Agrícola 35, no. 5 (October 2015): 838–51. http://dx.doi.org/10.1590/1809-4430-eng.agric.v35n5p838-851/2015.
Повний текст джерелаThayakaran, R., and N. I. Ramesh. "Multivariate models for rainfall based on Markov modulated Poisson processes." Hydrology Research 44, no. 4 (January 2, 2013): 631–43. http://dx.doi.org/10.2166/nh.2013.180.
Повний текст джерелаДисертації з теми "Multivariate rainfall analysis"
Martinengo, Marta. "Improving some non-structural risk mitigation strategies in mountain regions: debris-flow rainfall thresholds, multi-hazard flooding scenarios and public awareness." Doctoral thesis, Università degli studi di Trento, 2022. http://hdl.handle.net/11572/353702.
Повний текст джерелаMahbub, S. M. Parvez Bin. "Impact of urban traffic and climate change on water quality from road runoff." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/47139/1/Parvez_Mahbub_Thesis.pdf.
Повний текст джерелаBARRETO, Aldinete Bezerra. "Eventos extremos de chuva em salvador: uma abordagem matemático-estatística do ambiente atmosférico." Universidade Federal de Campina Grande, 2012. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1627.
Повний текст джерелаMade available in DSpace on 2018-09-03T15:08:48Z (GMT). No. of bitstreams: 1 ALDINETE BEZERRA BARRETO - TESE PPGMET 2012..pdf: 6263495 bytes, checksum: 1008afd187e39f22ffed865972093dbc (MD5) Previous issue date: 2012-05-08
CNPq
O objetivo deste estudo é caracterizar o regime de chuvas de Salvador em várias escalas de tempo, com foco em eventos extremos de chuva, e identificar padrões da circulação atmosférica de grande escala relacionados com tais eventos. O período de estudo é de 1964 a 2009. Métodos matemático-estatísticos (Percentil, Correlação Linear, Análise de Ondeletas, Análise de Componentes Principais (ACP) e Análise de Agrupamento) foram aplicados a dados observacionais de precipitação e dados em ponto de grade de reanálise. A técnica do percentil aplicada à série temporal dos dados diários de precipitação possibilitou classificar como eventos extremos os totais diários com valor igual ou maior do que 50 mm. O principal período chuvoso, abril a julho, detém 61% de todos os eventos da série. A análise de correlação linear mostrou uma relação direta entre a ocorrência dos eventos extremos e total mensal de chuva acima da média. A análise de ondeletas indicou que os eventos estão relacionados com, pelo menos, três tipos de oscilação na escala intrassazonal: de até 12 dias, de 12-24 dias e de 48-96 dias, o que sugere a contribuição de sistemas de escala sinótica como os distúrbios de leste e os sistemas frontais, e de circulações de escala planetária como a Oscilação de Madden-Julian. A ACP aplicada a dados de reanálise identificou padrões nos baixos níveis com configuração indicativa da presença do cavado equatorial/ZCIT, ondas de latitudes médias austrais e ZCAS, essa última relacionada com eventos dos meses de verão (dezembro-janeiro-fevereiro). O padrão do principal período chuvoso tem estrutura ondulatória no escoamento de oeste do hemisfério sul. Todos os padrões apresentam um cavado invertido no leste do Nordeste e área oceânica próxima, resultante da propagação/interação de sistemas atmosféricos da área tropical-extratropical. Nos altos níveis (200 hpa), o padrão relacionado com os eventos de verão mostra a Alta da Bolívia deslocada para nordeste, e o cavado de ar superior posicionado sobre o Atlântico tropical. A estrutura dominante nos padrões de inverno (junho-julho-agosto) é: (a) ondas de latitudes médias austrais com propagação em latitudes baixas, ou (b) uma área de difluência próxima ao equador relacionada com a ZCIT.
The objective in this study is to characterize the rainfall regime of Salvador on various time scales, with a focus on extreme rainfall events, and to identify large scale atmospheric circulation patterns related to such events. The period of study is from 1964 to 2009. Mathematical-statistical methods (Percentiles, Linear Correlation, Wavelet Analysis, Principal Component Analysis (PCA), Cluster Analysis) were applied to observational precipitation and gridpoint reanalysis data. The percentile technique applied to daily precipitation time series allowed to classify as extreme events daily rainfall totals equal to or greater than 50 mm. The main rainy period, from April to July, has 61% of all events. The linear correlation analysis identified a direct relation between the occurrence of extreme events and above-normal monthly rainfall totals. The wavelet analysis indicated that the events are related to, at least, three types of oscillations on the intraseasonal time scale: up to 12 days, 12-24 days and 48-96 days, suggesting the contribution of synoptic scale systems such as easterly disturbances and frontal systems, and planetary scale circulations as the Madden-Julian Oscillation. The PCA applied to reanalysis data identified low level patterns depicting the equatorial trough/ITCZ, southern mid-latitude waves and SACZ, the last one related to summer month events (December-January-February). The pattern of the main rainy period has a wavelike structure in the southern westerlies. All patterns show an inverted trough in eastern Northeast and the nearby oceanic area, a result of the propagation /interaction of tropical-extratropical atmospheric systems. At high levels (200 hpa), the summer pattern shows the Bolivian high displaced northeastward, and the upper level trough located over the tropical Atlantic. The dominating structure in the winter patterns (June-July-August) is: (a) southern mid-latitude waves propagating toward low latitudes, or (b) a difluence area close to the equator related to the ITCZ.
Fann, Jyr-shiuan, and 范植軒. "Establishing rainfall-runoff ANN model in watershed with multivariate analysis." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/40407392207447601078.
Повний текст джерела逢甲大學
水利工程與資源保育研究所
99
Different spatial distribution and environmental change on the simulation of rainfall-runoff process has a considerable impact in watershed. Artificial intelligence has prove to be an efficient way for hydrological modeling and widely used for rainfall-runoff process modeling in recent years. By clarifying the relationship between the physiographic and hydrological, allows us to understand how to make the spatial variability affect hydrological. This fact proves that the different of physiographic for the modeling of rainfall-runoff is very important. The study will use the factor analysis and structural equation modeling to filter important physiographic factor which has enough to represent watershed. Structural equation modeling (SEM) is different from factor analysis, that has the theory of priority and the purpose is to improve the model fit. We use a back-propagation neural network (BPN) which has input layer, hidden layer and out layer, and the form was considered by time distribution of rainfall-runoff and the space distribution of watershed environment. Besides, the form operates in learning by input-output that in order to combine and construct the system which are simulating. We expect the study can establish the nonlinear relationship among the physiographic factors, precipitation, and outflow of the specific watershed. Further more, we hope it can estimate the outflow of the sub-watershed or the other watershed which is an area of physiographic factors that are similar to the watershed. With validation tests at Wu-Xi watershed, it performed concluded fair forecast results and which could effectively simplify the model.
Частини книг з теми "Multivariate rainfall analysis"
Manoj, S., C. Valliyammai, and V. Kalyani. "Multivariate Regression Analysis of Climate Indices for Forecasting the Indian Rainfall." In Lecture Notes in Networks and Systems, 713–20. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3172-9_67.
Повний текст джерелаHudnurkar, Shilpa, Vidur Sood, Vedansh Mishra, Manobhav Mehta, Akash Upadhyay, Shilpa Gite, and Neela Rayavarapu. "Multivariate Time Series Forecasting of Rainfall Using Machine Learning." In Artificial Intelligence of Things for Weather Forecasting and Climatic Behavioral Analysis, 87–106. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-3981-4.ch007.
Повний текст джерелаDai, Q., D. Han, and P. K. Srivastava. "Radar Rainfall Sensitivity Analysis Using Multivariate Distributed Ensemble Generator." In Sensitivity Analysis in Earth Observation Modelling, 91–102. Elsevier, 2017. http://dx.doi.org/10.1016/b978-0-12-803011-0.00005-7.
Повний текст джерелаMoazami, S., and S. Golian. "Ensemble-Based Multivariate Sensitivity Analysis of Satellite Rainfall Estimates Using Copula Model." In Sensitivity Analysis in Earth Observation Modelling, 273–94. Elsevier, 2017. http://dx.doi.org/10.1016/b978-0-12-803011-0.00014-8.
Повний текст джерелаAl-Thukair, Assad, Yasin Jemal, and Alexis Nzila. "Influence of Climatic Factors on the Abundance and Profusion of Mosquitoes in Eastern Province, Saudi Arabia." In Mosquito Research - Recent Advances in Pathogen Interactions, Immunity, and Vector Control Strategies [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.104615.
Повний текст джерелаPolyak, Ilya. "Second Moments of Rain." In Computational Statistics in Climatology. Oxford University Press, 1996. http://dx.doi.org/10.1093/oso/9780195099997.003.0010.
Повний текст джерела