Tesis sobre el tema "Rainfall probabilities"
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Cung, Annie. "Statistical modeling of extreme rainfall processes in consideration of climate change". Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=100788.
Texto completoThe objective of the present research is therefore to find the best method for estimating accurately extreme rainfalls for the current time period and future periods in the context of climate change. The analysis of extreme rainfall data from the province of Quebec (Canada) revealed that, according to L-moment ratio diagrams, the data may be well described by the Generalized-Extreme-Value (GEV) distribution. Results also showed that a simple scaling relationship between non-central moments (NCM) and duration can be established and that a scaling method based on NCMs and scaling exponents can be used to generate accurate estimates of extreme rainfalls at Dorval station (Quebec, Canada). Other results demonstrated that the method of NCMs can accurately estimate distribution parameters and can be used to construct accurate Intensity-Duration-Frequency (IDF) curves.
Furthermore, a regional analysis was performed and homogenous regions of weather stations within Quebec were identified. A method for the estimation of missing data at ungauged sites based on regional NCMs was found to yield good estimates.
In addition, the potential impacts of climate change on extreme rainfalls were assessed. Changes in the distribution of annual maximum (AM) precipitations were evaluated using simulations from two Global Climate Models (GCMs) under the A2 greenhouse gas emission scenario: the Coupled Global Climate Model version 2 (CGCM2A2) of the Canadian Centre for Climate Modelling and Analysis, and the Hadley Centre's Model version 3 (HadCM3A2). Simulations from these two models were downscaled spatially using the Statistical DownScaling Model (SDSM). A bias-correction method to adjust the downscaled AM daily precipitations for Dorval station was tested and results showed that after adjustments, the values fit the observed AM daily precipitations well. The analysis of future AM precipitations revealed that, after adjustments, AM precipitations downscaled from CGCM2A2 increase from current to future periods, while AM precipitations downscaled from HadCM3A2 show a mild decrease from current to future periods, for daily and sub-daily scales.
Patron, Glenda G. "Joint probability distribution of rainfall intensity and duration". Thesis, This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-06232009-063226/.
Texto completoSuyanto, Adhi. "Estimating the exceedance probabilities of extreme floods using stochastic storm transportation and rainfall - runoff modelling". Thesis, University of Newcastle Upon Tyne, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386794.
Texto completoVavae, Hilia. "A simple forecasting scheme for predicting low rainfalls in Funafuti, Tuvalu". The University of Waikato, 2008. http://hdl.handle.net/10289/2435.
Texto completoMarx, Hester Gerbrecht. "The use of artificial neural networks to enhance numerical weather prediction model forecasts of temperature and rainfall". Diss., Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-02102009-161401/.
Texto completoMoatshe, Peggy Seanokeng. "Verification of South African Weather Service operational seasonal forecasts". Pretoria: [S.n.], 2009. http://upetd.up.ac.za/thesis/available/etd-08112009-131703.
Texto completoChen, Chia-Jeng. "Hydro-climatic forecasting using sea surface temperatures". Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/48974.
Texto completoRoulin, Emmannuel. "Medium-range probabilistic river streamflow predictions". Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209270.
Texto completoThe research began by analyzing the meteorological predictions at the medium-range (up to 10-15 days) and their use in hydrological forecasting. Precipitation from the ensemble prediction system of the European Centre for Medium-Range Weather Forecasts (ECMWF) were used. A semi-distributed hydrological model was used to transform these precipitation forecasts into ensemble streamflow predictions. The performance of these forecasts was analyzed in probabilistic terms. A simple decision model also allowed to compare the relative economic value of hydrological ensemble predictions and some deterministic alternatives.
Numerical weather prediction models are imperfect. The ensemble forecasts are therefore affected by errors implying the presence of biases and the unreliability of probabilities derived from the ensembles. By comparing the results of these predictions to the corresponding observed data, a statistical model for the correction of forecasts, known as post-processing, has been adapted and shown to improve the performance of probabilistic forecasts of precipitation. This approach is based on retrospective forecasts made by the ECMWF for the past twenty years, providing a sufficient statistical sample.
Besides the errors related to meteorological forcing, hydrological forecasts also display errors related to initial conditions and to modeling errors (errors in the structure of the hydrological model and in the parameter values). The last stage of the research was therefore to investigate, using simple models, the impact of these different sources of error on the quality of hydrological predictions and to explore the possibility of using hydrological reforecasts for post-processing, themselves based on retrospective precipitation forecasts.
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La prévision des débits des rivières se fait traditionnellement sur la base de mesures en temps réel des précipitations sur les bassins-versant et des débits à l'exutoire et en amont. Ces données sont traitées dans des modèles mathématiques de complexité variée et permettent d'obtenir des prévisions précises pour des temps courts. Pour prolonger l'horizon de prévision à quelques jours – afin d'être en mesure d'émettre des alertes précoces – il est nécessaire de prendre en compte les prévisions météorologiques. Cependant celles-ci présentent par nature une dynamique sensible aux erreurs sur les conditions initiales et, par conséquent, pour une gestion appropriée des risques, il faut considérer les prévisions en termes probabilistes. Actuellement, les prévisions d'ensemble sont effectuées à l'aide d'un modèle numérique de prévision du temps avec des conditions initiales perturbées et permettent d'évaluer l'incertitude.
La recherche a commencé par l'analyse des prévisions météorologiques à moyen-terme (10-15 jours) et leur utilisation pour des prévisions hydrologiques. Les précipitations issues du système de prévisions d'ensemble du Centre Européen pour les Prévisions Météorologiques à Moyen-Terme ont été utilisées. Un modèle hydrologique semi-distribué a permis de traduire ces prévisions de précipitations en prévisions d'ensemble de débits. Les performances de ces prévisions ont été analysées en termes probabilistes. Un modèle de décision simple a également permis de comparer la valeur économique relative des prévisions hydrologiques d'ensemble et d'alternatives déterministes.
Les modèles numériques de prévision du temps sont imparfaits. Les prévisions d'ensemble sont donc entachées d'erreurs impliquant la présence de biais et un manque de fiabilité des probabilités déduites des ensembles. En comparant les résultats de ces prévisions aux données observées correspondantes, un modèle statistique pour la correction des prévisions, connue sous le nom de post-processing, a été adapté et a permis d'améliorer les performances des prévisions probabilistes des précipitations. Cette approche se base sur des prévisions rétrospectives effectuées par le Centre Européen sur les vingt dernières années, fournissant un échantillon statistique suffisant.
A côté des erreurs liées au forçage météorologique, les prévisions hydrologiques sont également entachées d'erreurs liées aux conditions initiales et aux erreurs de modélisation (structure du modèle hydrologique et valeur des paramètres). La dernière étape de la recherche a donc consisté à étudier, à l'aide de modèles simples, l'impact de ces différentes sources d'erreur sur la qualité des prévisions hydrologiques et à explorer la possibilité d'utiliser des prévisions hydrologiques rétrospectives pour le post-processing, elles-même basées sur les prévisions rétrospectives des précipitations.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
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.
Texto completoAkil, Nicolas. "Etude des incertitudes des modèles neuronaux sur la prévision hydrogéologique. Application à des bassins versants de typologies différentes". Electronic Thesis or Diss., IMT Mines Alès, 2021. http://www.theses.fr/2021EMAL0005.
Texto completoFloods and droughts are the two main risks in France and require a special attention. In these conditions, where climate change generates increasingly frequent extreme phenomena, modeling these risks is an essential element for water resource management.Currently, discharges and water heights are mainly predicted from physical or conceptual based models. Although efficient and necessary, the calibration and implementation of these models require long and costly studies.Hydrogeological forecasting models often use data from incomplete or poorly dimensioned measurement networks. Moreover, the behavior of the study basins is in most cases difficult to understand. This difficulty is thus noted to estimate the uncertainties associated with hydrogeological modeling.In this context, this thesis, supported by IMT Mines Alès and financed by the company aQuasys and ANRT, aims at developing models based on the systemic paradigm. These models require only basic knowledge on the physical characterization of the studied basin, and can be calibrated from only input and output information (rainfall and discharge/height).The most widely used models in the environmental world are neural networks, which are used in this project. This thesis seeks to address three main goals:1. Development of a model design method adapted to different variables (surface water flows/height) and to very different types of basins: watersheds or hydrogeological basins (groundwater height)2. Evaluation of the uncertainties associated with these models in relation to the types of targeted basins3. Reducing of these uncertaintiesSeveral basins are used to address these issues: the Blavet basin in Brittany and the basin of the Southern and Central Champagne Chalk groundwater table
MOUSAVI, NADOSHANI SEYED SAEID. "Composition des lois élémentaires en hydrologie régionale : application à l'étude des régimes de crue". Grenoble 1, 1997. http://www.theses.fr/1997GRE10165.
Texto completoKanetsi, Khahiso. "Annual peak rainfall data augmentation - A Bayesian joint probability approach for catchments in Lesotho". Thesis, 2017. https://hdl.handle.net/10539/25567.
Texto completoThe 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
Howes, Carolann. "Components of ocean sea-level pressure and their relationship with rainfall over Southern Africa". Thesis, 2015. http://hdl.handle.net/10539/18199.
Texto completoMonthly mean s e a - l e v e l p r e s s u r e ove r th e o c ea nic areas a d j a c e n t t o t h e Kepublic o f South A f r i c a i s an aly s e d . R ela t i o n s h i p s between t h e oceanic p r e s s u r e and r a i n f a l l over t h i s p a r t o f t h e c o n t i n e n t a re d i s c u s s e d . P r i n c i p a l compon e n ts a n a l y s i s is used t o d e r i v e u n c o r r e l a t e d f u n c t i o n s of th e o r i g i n a l p r e s s u r e v a r i a b l e s . Three major p r e s s u r e f i e l d s were i d e n t i f i e d , termed a g e n e r a l , a l o n g i t u d i n a l and a l a t i t u d i n a l p r e s s u r e f i e l d . The r e l a t i o n s h i p s between p r e s s u r e and r a i n f a l l a re a s s e s s e d by r e g r e s s i n g monthly r a i n f a l l on t h e p r i n c i p a l comnonent s c o r e s . R a i n f a l l in w in te r maxima a r e a s appears t o be d i r e c t l y r e l a t e d t o oceanic s e a - l e v e l p r e s s u r e s i t u a t i o n s , whereas the r e s t o f th e country shows an o u t - o f - s e a s o n r e l a t i o n s h i p between r a i n f a l l and p r e s s u r e over n o n - c o n t i n e n t a l a r e a s .
Cartwright, Tina Johnson Krishnamurti T. N. "Warm season mesoscale superensemble precipitation forecasts". 2004. http://etd.lib.fsu.edu/theses/available/etd-10252004-132554.
Texto completoAdvisor: Dr. T.N. Krishnamurti, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed Jan. 14, 2005). Includes bibliographical references.
Mazumder, Tanvir, University of Western Sydney, of Science Technology and Environment College y School of Engineering. "Application of the joint probability approach to ungauged catchments for design flood estimation". 2005. http://handle.uws.edu.au:8081/1959.7/22731.
Texto completo(M. Eng.) (Hons)
D'Abreton, Peter Charles. "The dynamics and energetics of tropical-temperature troughs over Southern Africa". Thesis, 1992. http://hdl.handle.net/10539/21609.
Texto completoGR 2017
Mazumder, Tanvir. "Application of the joint probability approach to ungauged catchments for design flood estimation". Thesis, 2005. http://handle.uws.edu.au:8081/1959.7/22731.
Texto completoSmithers, Jeffrey Colin. "Development and evaluation of techniques for estimating short duration design rainfall in South Africa". Thesis, 1998. http://hdl.handle.net/10413/7756.
Texto completoThesis (M.Sc.)-University of Natal, Pietermaritzburg, 1998.
Knoesen, Darryn Marc. "The development and assessment of techniques for daily rainfall disaggregation in South Africa". Thesis, 2005. http://hdl.handle.net/10413/3439.
Texto completoThesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2005.
Ghile, Yonas Beyene. "Development of a framework for an integrated time-varying agrohydrological forecast system for southern Africa". Thesis, 2007. http://hdl.handle.net/10413/352.
Texto completoThesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2007.
Loveridge, Melanie. "Loss models for design flood estimation : toward applications within a Monte Carlo environment". Thesis, 2016. http://hdl.handle.net/1959.7/uws:38506.
Texto completoMashinye, Mosedi Deseree. "Long term seasonal and annual changes in rainfall duration and magnitude in Luvuvhu River Catchment, South Africa". Diss., 2018. http://hdl.handle.net/11602/1152.
Texto completoDepartment of Hydrology and Water Resources
This study was aimed at investigating the long term seasonal and annual changes in rainfall duration and magnitude at Luvuvhu River Catchment (LRC). Rainfall in this catchment is highly variable and is characterised of extreme events which shift runoff process, affect the timing and magnitude of floods and drought, and alter groundwater recharge. This study was motivated by the year to year changes of rainfall which have some effects on the availability of water resources. Computed long term total seasonal, annual rainfall and total number of seasonal rainy days were used to identify trends for the period of 51 years (1965- 2015), using Mann Kendal (MK), linear regression (LR) and quantile regression methods. The MK, LR and quantile regression methods have indicated dominance of decreasing trends of the annual, seasonal rainfall and duration of seasonal rainfall although they were not statistically significant. However, statistical significant decreasing trends in duration of seasonal rainfall were identified by MK and LR at Matiwa, Palmaryville, Levubu, and Entabeni Bos stations only. Quantile regression identified the statistically significant decreasing trends on 0.2, 0.5 and 0.7 quantiles only in the Palmaryville, Levubu and Entabeni Bos, respectively. Stations with non-statistically significant decreasing trends of annual and seasonal rainfall had magnitude of change ranging from 0.12 to 12.31 and 0.54 to 6.72 mm, respectively. Stations with non-statistically increasing trends of annual and seasonal rainfall magnitude had positive magnitude of change ranging from 1.51 to 6.78 and 2.05 to 6.51 mm, respectively. The Study recommended further studies using other approaches to determine the duration of rainfall to improve, update and compare the results obtained in the current study. Continuous monitoring and installation of rain gauges are recommended on the lower reaches of the catchment for the findings to be of complete picture for the whole catchment and to also minimize the rainfall gaps in the stations. Water resources should be used in a sustainable way to avoid water crisis risk in the next generations.
NRF