Dissertations / Theses on the topic 'Rain and rainfall Tasmania Mathematical models'
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1
To, Chun-hung, and 杜振雄. "Stochastic model of daily rainfall." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B31976098.
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de, Roulhac Darde Gregoire 1956. "APPLICATION OF COMPUTER GRAPHICS IN THE SELECTION OF RAINFALL FREQUENCY MODELS FOR ENVIRONMENTAL ENGINEERING." Thesis, The University of Arizona, 1987. http://hdl.handle.net/10150/276407.
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Sorooshian, Soroosh, and Vijai Kumar Gupta. "Improving the Reliability of Compartmental Models: Case of Conceptual Hydrologic Rainfall-Runoff Models." Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ), 1986. http://hdl.handle.net/10150/614011.
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Hendrickson, Jene Diane, and Soroosh Sorooshian. "CALIBRATION OF RAINFALL-RUNOFF MODELS USING GRADIENT-BASED ALGORITHMS AND ANALYTIC DERIVATIVES." Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ), 1987. http://hdl.handle.net/10150/614186.
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In the past, derivative-based optimization algorithms have not
frequently been used to calibrate conceptual rainfall -riff (CRR)
models, partially due to difficulties associated with obtaining the
required derivatives. This research applies a recently- developed
technique of analytically computing derivatives of a CRR model to a
complex, widely -used CRR model. The resulting least squares response
surface was found to contain numerous discontinuities in the surface
and derivatives. However, the surface and its derivatives were found
to be everywhere finite, permitting the use of derivative -based
optimization algorithms. Finite difference numeric derivatives were
computed and found to be virtually identical to analytic derivatives.
A comparison was made between gradient (Newton- Raphsoz) and
direct (pattern search) optimization algorithms. The pattern search
algorithm was found to be more robust. The lower robustness of the
Newton-Raphsoi algorithm was thought to be due to discontinuities and a
rough texture of the response surface.
5
Goodrich, David Charles. "Basin Scale and Runoff Model Complexity." Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ), 1990. http://hdl.handle.net/10150/614028.
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Distributed Rainfall-Runoff models are gaining widespread acceptance; yet, a
fundamental issue that must be addressed by all users of these models is definition
of an acceptable level of watershed discretization (geometric model complexity). The
level of geometric model complexity is a function of basin and climatic scales as well
as the availability of input and verification data. Equilibrium discharge storage is
employed to develop a quantitative methodology to define a level of geometric model
complexity commensurate with a specified level of model performance. Equilibrium
storage ratios are used to define the transition from overland to channel -dominated
flow response. The methodology is tested on four subcatchments in the USDA -ARS
Walnut Gulch Experimental Watershed in Southeastern Arizona. The catchments
cover a range of basins scales of over three orders of magnitude. This enabled a
unique assessment of watershed response behavior as a function of basin scale.
High quality, distributed, rainfall -runoff data was used to verify the model (KINEROSR). Excellent calibration and verification results provided confidence in
subsequent model interpretations regarding watershed response behavior. An
average elementary channel support area of roughly 15% of the total basin area is
shown to provide a watershed discretization level that maintains model performance
for basins ranging in size from 1.5 to 631 hectares. Detailed examination of
infiltration, including the role and impacts of incorporating small scale infiltration
variability in a distribution sense, into KINEROSR, over a range of soils and
climatic scales was also addressed. The impacts of infiltration and channel losses
on runoff response increase with increasing watershed scale as the relative influence
of storms is diminished in a semiarid environment such as Walnut Gulch. In this
semiarid environment, characterized by ephemeral streams, watershed runoff
response does not become more linear with increasing watershed scale but appears
to become more nonlinear.
6
Enright, Peter 1962. "Simulation of rainfall excess on flat rural watersheds in Quebec." Thesis, McGill University, 1988. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=61952.
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Luckemeier, Richard Ewald 1948. "A rainfall-runoff model for an urban watershed in Tucson, Arizona." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277165.
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The U.S. Geological Survey and the City of Tucson, Arizona, have been collecting rainfall and runoff data on several watersheds in the Tucson area for several years. Among the purposes of this project is to use the data to test rainfall-runoff models in an effort to find one to successfully simulate flood flows in Tucson. One such model, the Distributed Routing Rainfall-Runoff Model (DR3M), was tested using data collected on Rob Wash in Tucson. It was found DR3M performs about as well as it does in other parts of the United States, although it tends to underestimate flood flows for large storms and overestimate flows for smaller storms. Unique features with regard to the hydrology of urban Tucson require special attention when using DR3M; these features are associated with the nature of dry washes and summer rainfall in Tucson. Experience indicates DR3M is not truly a deterministic model.
8
Lau, Wai-hin, and 劉偉憲. "Stochastic analysis of monthly rainfall in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1991. http://hub.hku.hk/bib/B31210387.
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Harrold, Timothy Ives Civil & Environmental Engineering Faculty of Engineering UNSW. "Stochastic generation of daily rainfall for catchment water management studies." Awarded by:University of New South Wales. School of Civil and Environmental Engineering, 2002. http://handle.unsw.edu.au/1959.4/18640.
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This thesis presents an approach for generating long synthetic sequences of single-site daily rainfall which can incorporate low-frequency features such as drought, while still accurately representing the day-to-day variations in rainfall. The approach is implemented in a two-stage process. The first stage is to generate the entire sequence of rainfall occurrence (i.e. whether each day is dry or wet). The second stage is to generate the rainfall amount on all wet days in the sequence. The models used in both stages are nonparametric (they make minimal general assumptions rather than specific assumptions about the distributional and dependence characteristics of the variables involved), and ensure an appropriate representation of the seasonal variations in rainfall. A key aspect in formulation of the models is selection of the predictor variables used to represent the historical features of the rainfall record. Methods for selection of the predictors are presented here. The approach is applied to daily rainfall from Sydney and Melbourne. The models that are developed use daily-level, seasonal-level, annual-level, and multi-year predictors for rainfall occurrence, and daily-level and annual-level predictors for rainfall amount. The resulting generated sequences provide a better representation of the variability associated with droughts and sustained wet periods than was previously possible. These sequences will be useful in catchment water management studies as a tool for exploring the potential response of catchments to possible future rainfall.
10
Kapangaziwiri, Evison. "Revised parameter estimation methods for the Pitman monthly rainfall-runoff model." Thesis, Rhodes University, 2008. http://hdl.handle.net/10962/d1006172.
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In recent years, increased demands have been placed on hydrologists to find the most effective methods of making predictions of hydrologic variables in ungauged basins. A huge part of the southern African region is ungauged and, in gauged basins, the extent to which observed flows represent natural flows is unknown, given unquantified upstream activities. The need to exploit water resources for social and economic development, considered in the light of water scarcity forecasts for the region, makes the reliable quantification of water resources a priority. Contemporary approaches to the problem of hydrological prediction in ungauged basins in the region have relied heavily on calibration against a limited gauged streamflow database and somewhat subjective parameter regionalizations using areas of assumed hydrological similarity. The reliance of these approaches on limited historical records, often of dubious quality, introduces uncertainty in water resources decisions. Thus, it is necessary to develop methods of estimating model parameters that are less reliant on calibration. This thesis addresses the question of whether physical basin properties and the role they play in runoff generation processes can be used directly in the estimation of parameter values of the Pitman monthly rainfall-runoff model. A physically-based approach to estimating the soil moisture accounting and runoff parameters of a conceptual, monthly time-step rainfall-runoff model is proposed. The study investigates the physical meaning of the model parameters, establishes linkages between parameter values and basin physical properties and develops relationships and equations for estimating the parameters taking into account the spatial and temporal scales used in typical model applications. The estimationmethods are then tested in selected gauged basins in southern Africa and the results of model simulations evaluated against historical observed flows. The results of 71 basins chosen from the southern African region suggest that it is possible to directly estimate hydrologically relevant parameters for the Pitman model from physical basin attributes. For South Africa, the statistical and visual fit of the simulations using the revised parameters were at least as good as the current regional sets, albeit the parameter sets being different. In the other countries where no regionalized parameter sets currently exist, simulations were equally good. The availability, within the southern African region, of the appropriate physical basin data and the disparities in the spatial scales and the levels of detail of the data currently available were identified as potential sources of uncertainty. GIS and remote sensing technologies and a widespread use of this revised approach are expected to facilitate access to these data.
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Dupigny-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.
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The sertao of northeast Brazil is a semiarid region characterized by recurring droughts. The vastness of the area (650,000 km$ sp2)$ poses a challenge to the effective monitoring of the impacts of drought at a scale that would be useful to the inhabitants of the sertao. Remote sensing data provide a viable way of assessing the extent and nature of drought across the landscape.The 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.
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Mwelwa, Elenestina Mutekenya. "The application of the monthly time step Pitman rainfall-runoff model to the Kafue River basin of Zambia." Thesis, Rhodes University, 2005. http://hdl.handle.net/10962/d1006171.
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This thesis presents a discussion on the study undertaken in the application of the monthly time step Pitman rainfall-runoff model to the Kafue River basin. The study constituted one of the initial steps in the capacity building and expansion of the application of hydrologic models in the southern African region for water resources assessment, one of the core areas of the Southern African FRIEND project (Flow Regimes from International Experimental Network Data). The research process was undertaken in four major stages, each stage working towards achieving the research objectives. The first stage was the preparation of spatial data which included the selection and delineation of sub-catchments and inclusion of spatial features required to run the Pitman model and transferring the spatial data into SPATSIM. The second stage was the preparation of input data, mainly rainfall, streamflow, evaporation, and water abstraction data. This information was then imported into SPATSIM, which was able to assist in the further preparation of data by assessment of the input data quality, linking of observed flows and spatial interpolation of point rainfall data to average catchment rainfall in readiness for running and calibration of the model. The third stage was the running and calibration of the Pitman model. Use was made of both the automatic calibration facility, as well as manual calibration by means of the time series graph display and analysis facility of SPATSIM. Model calibration was used to obtain the best fit and an acceptable correlation between the simulated and the observed flows and to obtain simulation parameter sets for sub-catchments and regions within the Kafue catchment. The fourth stage was the analysis and evaluation of the model results. This included verification of results over different time periods and validation and testing of parameter transfers to other catchments. This stage also included the evaluation of SPATSIM as a tool for applying the model and as a database for the processing and storage of water resources data. The study’s output includes: A comprehensive database of hydrometeorological, physical catchment characteristics, landuse and water abstraction information for the Kafue basin; calibrated Pitman model parameters for the sub-catchments within the Kafue basin; recommendations for future work and data collection programmes for the application of the model. The study has also built capacity by facilitating training and exposure to rainfall-runoff models (specifically the Pitman model) and associated software, SPATSIM. In addition, the dissemination of the results of this study will serve as an effective way of raising awareness on the application of the Pitman model and the use of the SPATSIM software within Zambia and the region. The overall Pitman model results were found to be satisfactory and the calibrated model is able to reproduce the observed spatial and temporal variations in streamflow characteristics in the Kafue River basin.
13
Li, Yanqiu, and 李艳秋. "Monitoring, analyzing and modeling hydrological processes over a headwater catchment in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43085349.
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Kapangaziwiri, Evison. "Regional application of the Pitman monthly rainfall-runoff model in Southern Africa incorporating uncertainty." Thesis, Rhodes University, 2011. http://hdl.handle.net/10962/d1006178.
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Climate change and a growing demand for freshwater resources due to population increases and socio-economic changes will make water a limiting factor (in terms of both quantity and quality) in development. The need for reliable quantitative estimates of water availability cannot be over-emphasised. However, there is frequently a paucity of the data required for this quantification as many basins, especially in the developing world, are inadequately equipped with monitoring networks. Existing networks are also shrinking due mainly to shortages in human and financial resources. Over the past few decades mathematical models have been used to bridge the data gap by generating datasets for use in management and policy making. In southern Africa, the Pitman monthly rainfall-runoff model has enjoyed relatively popular use as a water resources estimation tool. However, it is acknowledged that models are abstractions of reality and the data used to drive them is imperfect, making the model outputs uncertain. While there is acknowledgement of the limitations of modelled data in the southern African region among water practitioners, there has been little effort to explicitly quantify and account for this uncertainty in water resources estimation tools and explore how it affects the decision making process. Uncertainty manifests itself in three major areas of the modelling chain; the input data used to force the model, the parameter estimation process and the model structural errors. A previous study concluded that the parameter estimation process for the Pitman model contributed more to the global uncertainty of the model than other sources. While the literature abounds with uncertainty estimation techniques, many of these are dependent on observations and are therefore unlikely to be easily applicable to the southern African region where there is an acute shortage of such data. This study focuses on two aspects of making hydrologic predictions in ungauged basins. Firstly, the study advocates the development of an a priori parameter estimation process for the Pitman model and secondly, uses indices of hydrological functional behaviour to condition and reduce predictive uncertainty in both gauged and ungauged basins. In this approach all the basins are treated as ungauged, while the historical records in the gauged basins are used to develop regional indices of expected hydrological behaviour and assess the applicability of these methods. Incorporating uncertainty into the hydrologic estimation tools used in southern Africa entails rethinking the way the uncertain results can be used in further analysis and how they will be interpreted by stakeholders. An uncertainty framework is proposed. The framework is made up of a number of components related to the estimation of the prior distribution of the parameters, used to generate output ensembles which are then assessed and constrained using regionalised indices of basin behavioural responses. This is premised on such indices being based on the best available knowledge covering different regions. This framework is flexible enough to be used with any model structure to ensure consistent and comparable results. While the aim is to eventually apply the uncertainty framework in the southern African region, this study reports on the preliminary work on the development and testing of the framework components based on South African basins. This is necessitated by the variations in the availability and quality of the data across the region. Uncertainty in the parameter estimation process was incorporated by assuming uncertainty in the physical and hydro-meteorological data used to directly quantify the parameter. This uncertainty was represented by the range of variability of these basin characteristics and probability distribution functions were developed to account for this uncertainty and propagate it through the estimation process to generate posterior distributions for the parameters. The results show that the framework has a great deal of potential but can still be improved. In general, the estimated uncertain parameters managed to produce hydrologically realistic model outputs capturing the expected regimes across the different hydro-climatic and geo-physical gradients examined. The regional relationships for the three indices developed and tested in this study were in general agreement with existing knowledge and managed to successfully provide a multi-criteria conditioning of the model output ensembles. The feedback loop included in the framework enabled a systematic re-examination of the estimation procedures for both the parameters and the indices when inconsistencies in the results were identified. This improved results. However, there is need to carefully examine the issues and problems that may arise within other basins outside South Africa and develop guidelines for the use of the framework.iText 1.4.6 (by lowagie.com)
15
Goodrich, David Charles. "Geometric simplification of a distributed rainfall-runoff model over a range of basin scales." Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/185051.
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Distributed rainfall-runoff models are gaining widespread acceptance; yet, a fundamental issue that must be addressed by all users of these models is definition of an acceptable level of watershed discretization (geometric model complexity). The level of geometric model complexity is a function of basin and climatic scales as well as the availability of input and verification data. Equilibrium discharge storage is employed to develop a quantitative methodology to define a level of geometric model complexity commensurate with a specified level of model performance. Equilibrium storage ratios are used to define the transition from overland to channel-dominated flow response. The methodology is tested on four subcatchments in the USDA-ARS Walnut Gulch Experimental Watershed in southeastern Arizona. The catchments cover a range of basins scales of over three orders of magnitude. This enabled a unique assessment of watershed response behavior as a function of basin scale. High quality, distributed, rainfall-runoff data were used to verify the model (KINEROSR). Excellent calibration and verification results provided confidence in subsequent model interpretations regarding watershed response behavior. An average elementary channel support area of roughly 15% of the total basin area is shown to provide a watershed discretization level that maintains model performance for basins ranging in size from 1.5 to 631 hectares. Detailed examination of infiltration, including the role and impacts of incorporating small-scale infiltration variability in a distribution sense, into KINEROSR, over a range of soils and climatic scales was also addressed. The impacts of infiltration and channel losses on runoff response increase with increasing watershed scale as the relative influence of storms is diminished in a semi-arid environment such as Walnut Gulch. In this semi-arid environment, characterized by ephemeral streams, watershed runoff response does not become more linear with increasing watershed scale but appears to become more nonlinear.
16
Robichaud, Alain 1956. "On the modeling of orographic rain using the seeder-feeder mechanism." Thesis, McGill University, 1986. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=66081.
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Chen, Hong, and 陳虹. "Mechanisms and modelling of landslides in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31239948.
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Sawunyama, Tendai. "Evaluating uncertainty in water resources estimation in Southern Africa : a case study of South Africa." Thesis, Rhodes University, 2009. http://hdl.handle.net/10962/d1006176.
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Hydrological models are widely used tools in water resources estimation, but they are simple representations of reality and are frequently based on inadequate input data and uncertainties in parameter values. Data observation networks are expensive to establish and maintain and often beyond the resources of most developing countries. Consequently, measurements are difficult to obtain and observation networks in many countries are shrinking, hence obtaining representative observations in space and time remains a challenge. This study presents some guidelines on the identification, quantification and reduction of sources of uncertainty in water resources estimation in southern Africa, a data scarce region. The analyses are based on example sub-basins drawn from South Africa and the application of the Pitman hydrological model. While it has always been recognised that estimates of water resources availability for the region are subject to possible errors, the quantification of these uncertainties has never been explicitly incorporated into the methods used in the region. The motivation for this study was therefore to contribute to the future development of a revised framework for water resources estimation that does include uncertainty. The focus was on uncertainties associated with climate input data, parameter estimation (and recognizing the uncertainty due model structure deficiencies) methods and water use data. In addition to variance based measures of uncertainty, this study also used a reservoir yield based statistic to evaluate model output uncertainty, which represents an integrated measure of flow regime variations and one that can be more easily understood by water resources managers. Through a sensitivity analysis approach, the results of the individual contribution of each source of uncertainty suggest regional differences and that clear statements about which source of uncertainty is likely to dominate are not generally possible. Parameter sensitivity analysis was used in identifying parameters which are important withinspecific sub-basins and therefore those to focus on in uncertainty analysis. The study used a simple framework for evaluating the combined contribution of uncertainty sources to model outputs that is consistent with the model limitations and data available, and that allows direct quantitative comparison between model outputs obtained by using different sources of information and methods within Spatial and Time Series Information Modelling (SPATSIM) software. The results from combining the sources of uncertainties showed that parameter uncertainty dominates the contribution to model output uncertainty. However, in some parts of the country especially those with complex topography, which tend to experience high rainfall spatial variability, rainfall uncertainty is equally dominant, while the contributions of evaporation and water use data uncertainty are relatively small. While the results of this study are encouraging, the weaknesses of the methods used to quantify uncertainty (especially subjectivity involved in evaluating parameter uncertainty) should not be neglected and require further evaluations. An effort to reduce data and parameter uncertainty shows that this can only be achieved if data access at appropriate scale and quality improves. Perhaps the focus should be on maintaining existing networks and concentrating research efforts on making the most out of the emerging data products derived from remote sensing platforms. While this study presents some initial guidelines for evaluating uncertainty in South Africa, there is need to overcome several constraints which are related to data availability and accuracy, the models used and the capacity or willingness to adopt new methods that incorporate uncertainty. The study has provided a starting point for the development of new approaches to modelling water resources in the region that include uncertain estimates.
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Tumbo, Madaka Harold. "Uncertainties in modelling hydrological responses in gauged and ungauged sub‐basins." Thesis, Rhodes University, 2015. http://hdl.handle.net/10962/d1018568.
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The world is undergoing rapid changes and the future is uncertain. The changes are related to modification of the landscape due to human activities, such as large and small scale irrigation, afforestation and changes to the climate system. Understanding and predicting hydrologic change is one of the challenges facing hydrologists today. Part of this understanding can be developed from observed data, however, there often too few observations and those that are available are frequently affected by uncertainties. Hydrological models have become essential tools for understanding historical variations of catchment hydrology and for predicting future possible trends. However, most developing countries are faced with poor spatial distributions of rainfall and evaporation stations that provide the data used to force models, as well as stream flow gauging stations to provide the data for establishing models and for evaluating their success. Hydrological models are faced with a number of challenges which include poor input data (data quality and poorly quantified human activities on observed stream flow data), uncertainties associated with model complexity and structure, the methods used to quantify model parameters, together with the difficulties of understanding hydrological processes at the catchment or subbasin. Within hydrological modelling, there is currently a trend of dealing with equifinality through the evaluation of parameter identifiability and the quantification of uncertainty bands associated with the predictions of the model. Hydrological models should not only focus on reproducing the past behaviour of a basin, but also on evaluating the representativeness of the surface and subsurface model components and their ability to simulate reality for the correct reasons. Part of this modelling process therefore involves quantifying and including all the possible sources of uncertainty. Uncertainty analysis has become the standard approach to most hydrological modelling studies, but has yet to be effectively used in practical water resources assessment. This study applied a hydrological modelling approach for understanding the hydrology of a large Tanzanian drainage basin, the Great Ruaha River that has many areas that are ungauged and where the available data (climate, stream flow and existing water use) are subject to varying degrees of uncertainty. The Great Ruaha River (GRR) is an upstream tributary of the Rufiji River Basin within Tanzania and covers an area of 86 000 km2. The basin is drained by four main tributaries; the Upper Great Ruaha, the Kisigo, the Little Ruaha and the Lukosi. The majority of the runoff is generated from the Chunya escarpment, the Kipengere ranges and the Poroto Mountains. The runoff generated feeds the alluvial and seasonally flooded Usangu plains (including the Ihefu perennial swamp). The majority of the irrigation water use in the basin is located where headwater sub‐basins drain towards the Usangu plains. The overall objective was to establish uncertain but behavioural hydrological models that could be useful for future water resources assessments that are likely to include issues of land use change, changes in patterns of abstraction and water use, as well the possibility of change in future climates.
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Shin, Mun-Ju. "Pragmatic methods for analysing performance and identifiability issues in rainfall-runoff modelling." Phd thesis, 2014. http://hdl.handle.net/1885/156363.
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Uncertainty has become a primary issue for modellers and decision makers concerned about understanding the behaviour of natural systems. Characterising uncertainty is an important modelling step for assessing the options for managing it. Without an understanding of a model's strength and weakness and of model uncertainty we cannot judge if management interventions will cause significant change. Methods for characterising uncertainty range from empirical, through naive Monte Carlo to formal Bayesian methods. Most uncertainty methods are complex and difficult to implement. But uncertainty analysis can be so much simpler than this and lead to powerful insights and model improvements. This is illustrated in this thesis where it demonstrates that simple methods can provide useful insight into model uncertainty. This thesis uses four hydrological models of varying complexity applied to five catchments of differing characteristics. It shows that uncertainty analysis can be simple and provide crucial insights into the behaviour of environmental models. This thesis begins by showing how a simple global sensitivity analysis can identify parameters in a model that are unimportant in explaining model outputs, and that might improve identifiability either by checking which ones can be fixed or by changing the objective function. The results confirm that for the catchment examined a minimum of five years is required to characterise the sensitivities assuredly and that only the simpler models have well-identified parameters, but parameter sensitivities vary between catchments. The simple global sensitivity analysis is then complemented with an identifiability analysis of the four models. More complex models have more uncertain and poorly-identified parameters. Model structure is shown to be the major problem in obtaining a global solution, far outweighing data informativeness and the objective function selected. Moreover, the more complex models do not dominate the performance of the less complex, the best model depending on the catchment of interest and even the calibration period. This thesis then considers the issue of minimum acceptable model performance. It is argued that a typical hydrological model identification process of optimising the objective function and reporting the performance in a validation period is no longer sufficient practice. If models with lower objective function values are to be accepted, we need to know how bad a model will be considered as good enough. It proposes a generic approach that uses elimination of Pareto-dominated models and cross-validation to identify minimal criteria for which models should be accepted. Finally, this thesis investigated uncertainties introduced by variable time delays between rainfall events and hydrograph response, a response complexity not handled well by rainfall-runoff models. Smaller events tend to have larger time delays and variability compared to larger events. It proposes a simple solution for model calibration by shifting rainfall and/or modelled times series in events by the amount of observed time lag, as calculated by a cross-correlation function. A variable integer time delay method leads to general improvements in simulation on independent periods, when invoking performance metrics of a Shifted Nash-Sutcliffe Efficiency and absolute relative bias. Overall the variable integer time delay method also improved parameter identifiability.
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Mulangu, Chrispin Tshikomba. "Rain attenuation modelling for Southern Africa." Thesis, 2008. http://hdl.handle.net/10413/888.
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In order to address rain attenuation scattering of millimetric waves and microwave sin Botswana, we have employed a comparison technique to determine the Ro.o1 at fourteen diverse locations in Botswana. In addition we have identified two rain climatic zones for Botswana. We note that Matzler employs Mie Scattering technique to determine the specific attenuation due to rain in Central Europe. Both Matzler and Olsen use the exponential distribution of N(D) to calculate y. In this dissertation we use the Mie scattering approach, but assume several distributions, including the log-normal distribution of N(D) as expounded by Ajayi et aI., to determine y for tropical and subtropical regions of Africa. The results show that the extinction coefficients depend
more strongly on temperature at lower frequencies than at higher frequencies for
lognormal distribution: at selected frequencies, we record high attenuation values at rising SHF bands: at 300 GHz, tropical showers take on values of 12, 12.5, 11.9 and 14 dB/km for Gaborone, Francistown, Kasane and Selebi-Phikwe, respectively. The absorption coefficient is significant but decreases exponentially with rain temperature at lower microwave frequencies. The application of the proposed model (Continental Thunderstorm is shown using practical results from Durban) is corroborated using practical results from Durban. Further, based on attenuation measurements, it is found that the lognormal distribution is suitable for Durban at rain rates greater than or equal to 21 mm/h. At rain rates below this, the loss-Thunderstorm is the better fit. Finally in this dissertation the results show that for rainfall intensity below about 10 mm/h for Marshall-Palmer (MP), Joss-Drizzle (JD), Joss-Thunderstorm (JT) and Law-Parson (LP) distributions, and below about 4
mm/h for Continental-Showers (CS), Tropical Showers (TS), Continental Thunderstorms (CT) and Tropical Thunderstorm (TT) distributions, the specific rain backscattering follows Rayleigh scattering law where the rain drops are small with respect to the wavelength when the frequency is 19.5 GHz. At rain rates above 10 mm/h for exponential distribution, and above 4 mm/h for lognormal distribution, the specific backscattering follows Mie scattering law. When the received echo power from rain becomes significant, it contributes to the rise in the noise floor and the radar receiver can lose its target. In addition, the result shows that Mie backscattering efficiency is highest at a raindrop diameter of 4.7mm.Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2008.
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Clothier, Antony Neil. "High resolution space-time modelling of rainfall : the string of beads model." Thesis, 2003. http://hdl.handle.net/10413/4268.
Full textAbstract:
The purpose of this study was to develop a rainfall model, continuous in space-time, which captures both the spatial and temporal structure of rainfall over a range of scales varying from lkm to 128km pixels at temporal resolutions ranging from 5 minute up to 1 year. Such a model could find application in a variety of hydrological fields including the management of flash flood scenarios where it could be used in combination with runoff models as a training tool in the operation of flood control structures, the assessment of flood risk, the management of water resources in an area through the simulation of long rainfall sequences and as a short term rainfall forecasting tool, to name a few. The String of Beads Model (SBM) is a high-resolution space-time model of radar rainfall images. It is a stochastic model that takes advantage of the detailed spatial and temporal information captured by weather radar and combines it with the long term seasonal variation captured by a network of daily raingauges. The alternating wet-dry process, or event arrival and duration, is modelled as a one dimensional process, while the detailed wet process is modelled as a three-dimensional (two space and one time) process at 1km, 5 minute spatial and temporal resolutions respectively, over an area of 16000km2, consistent with the observed radar data. The three-dimensional rainfall events distributed on a one-dimensional time line, is analogous to a "String of Beads". The SBM makes use of a combination of power law numerical filtering techniques and well-known time series models to achieve an efficient algorithm that can be run on an ordinary personal computer. Model output is in the form of image files which, when viewed as an animated sequence, are difficult to distinguish from observed radar rainfall images. Apart from the realistic appearance of these images, when calibrated to daily raingauge data for the region, analysis of the simulated sequences over periods of up to ten years, reveal convincing rainfall statistics for a wide range of spatial and temporal scales. It can be used both as a simulation tool and as a short term forecasting tool. In simulation mode, it can quickly produce long sequences (tens of years) of 128 x 128 km rainfall images at five minute, one kilometre resolution. Such simulations can be used as input to distributed and semi-distributed hydrological models to produce "what if" scenarios for applications in water resources management and flood risk assessment amongst others. In forecasting mode, the SBM has proved effective in producing real time forecasts of up to two hours making it a useful tool for flood warning and management, particularly in steep or urban catchments which react quickly and often give rise to flash floods. It can also be used in a combined simulation-forecasting mode to quickly produce many short term "what if" scenarios which can be used to assess the risk of possible growth or decay scenarios in real time.Thesis (Ph.D.)-University of Natal, Durban, 2003.
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"An analysis of spatial and temporal variation in rainfall characteristics in Hong Kong." 1999. http://library.cuhk.edu.hk/record=b5896328.
Full textAbstract:
Wong Chun Kit.Thesis (M.Phil.)--Chinese University of Hong Kong, 1999.
Includes bibliographical references (leaves [132-143]).
Abstracts in English and Chinese.
List of Tables --- p.i
List of Figures --- p.iv
List of Symbols --- p.v
Chapter CHAPTER ONE: --- INTRODUCTION --- p.1
Chapter 1.1 --- Objectives and Significance of the Study --- p.4
Chapter 1.2 --- Physical Setting of Hong Kong --- p.5
Chapter 1.3 --- Climate of Hong Kong --- p.9
Chapter 1.4 --- Data Acquisition --- p.11
Chapter 1.4.1 --- Raingauges in Hong Kong --- p.11
Chapter 1.4.2. --- Database for the Spatial Variation Analyses --- p.14
Chapter 1.4.2.1. --- Data Selection for the Analyses for Factors Affecting Rainfall ´ؤ Elevation and Aspect --- p.15
Chapter 1.4.2.2. --- Data Selection for the Classification of Stations and Inter-station Correlation Analysis --- p.17
Chapter 1.4.3 --- Database for the Temporal Variation Analyses --- p.20
Chapter CHAPTER TWO : --- LITERATURE REVIEW --- p.22
Chapter 2.1 --- Spatial Variation of Rainfall --- p.22
Chapter 2.2 --- Detection of Temporal Changes in Rainfall --- p.28
Chapter 2.3 --- Urban Influence on Rainfall --- p.29
Chapter 2.4 --- Studies in Hong Kong --- p.33
Chapter CHAPTER THREE : --- METHODOLOGY --- p.33
Chapter 3.1 --- Preliminary Processing of the Data --- p.38
Chapter 3.2 --- Data Analysis --- p.40
Chapter 3.2.1 --- General Pattern of Rainfall Distribution --- p.40
Chapter 3.2.2 --- Data Analyses of Spatial Variation --- p.41
Chapter 3.2.2.1 --- Correlation between Rainfall and Elevation --- p.41
Chapter 3.2.2.2 --- Correlation between Rainfall and Aspect --- p.42
Chapter 3.2.2.3 --- Classification of Stations --- p.43
Chapter 3.2.2.4 --- Inter-Station Correlation Analysis --- p.46
Chapter 3.2.3 --- Data Analysis of Temporal Variation --- p.46
Chapter 3.2.3.1 --- The Running Mean Method --- p.47
Chapter 3.2.3.2 --- The 'Standard Error of the Difference' Test --- p.49
Chapter CHAPTER FOUR: --- RESULTS AND DISCUSSION --- p.50
Chapter 4.1 --- Graphical Representation of Spatial Rainfall Pattern --- p.50
Chapter 4.1.1 --- Annual Rainfall Pattern --- p.50
Chapter 4.1.2 --- Monthly Rainfall Pattern --- p.56
Chapter 4.1.3 --- Frequency Distribution of Raindays --- p.59
Chapter 4.1.4 --- Pentade Rainfall Pattern --- p.64
Chapter 4.1.5 --- Diurnal Rainfall Pattern --- p.67
Chapter 4.1.6 --- Implications of the Spatial Rainfall Pattern --- p.70
Chapter 4.2 --- Analyses of Spatial Variation in Rainfall --- p.78
Chapter 4.2.1 --- Relationship between Rainfall and Elevation --- p.78
Chapter 4.2.2 --- Relationship between Rainfall and Aspect --- p.82
Chapter 4.2.3 --- Classification of Stations --- p.85
Chapter 4.2.3.1 --- Principal Components Interpretation --- p.87
Chapter 4.2.3.2 --- Result of Classification --- p.90
Chapter 4.2.4 --- Inter-Station Correlation Analysis --- p.98
Chapter 4.2.5 --- Discussion of the Rainfall Spatial Variation --- p.103
Chapter 4.3 --- Analyses of Temporal Variation in Rainfall --- p.107
Chapter 4.3.1 --- Annual Rainfall --- p.107
Chapter 4.3.2 --- Monthly Rainfall --- p.110
Chapter 4.3.3 --- Pentade Rainfall --- p.112
Chapter 4.3.4 --- Diurnal Rainfall --- p.117
Chapter 4.3.5 --- Discussion of the Rainfall Temporal Variation --- p.118
Chapter CHAPTER FIVE: --- CONCLUSIONS AND RECOMMENDATIONS --- p.126
Chapter 5.1 --- Summary of Findings --- p.126
Chapter 5.2 --- Limitation of this Research --- p.129
Chapter 5.3 --- Prospects of this Research --- p.130
Bibliography
24
Cui, Gurong. "Rainfall runoff model improvements incorporating a dynamic wave model and synthetic stream networks." Diss., 1999. http://www.newcastle.edu.au/services/library/adt/public/adt-NNCU20030120.144918/index.html.
Full text
25
Rosenberg, Kathrine Joan. "Stochastic modelling of rainfall and generation of synthetic rainfall data at Mawson Lakes." 2004. http://arrow.unisa.edu.au:8081/1959.8/24949.
Full textAbstract:
Mawson Lakes is a new suburban housing development, situated 12 kms from the city of Adelaide in South Australia. The developers, the Mawson Lakes Joint Venture (MLJV), and the local council, the City of Salisbury, intend to capture all stormwater entering the site and recondition all wastewater. The water will then be supplied to residents and businesses for non-potable usage. Modelling the behaviour of the Mawson Lakes catchment under extreme conditions such as drought and prolonged periods of high rainfall will allow the project team to determine optimal water management strategies for the catchment. One of the problems facing the team is the prediction of future rainfall patterns and the typical form of extreme events. In this thesis I have used historical records to construct synthetic rainfall data that will allow the project team to investigate a wide range of typical behaviour. The Gamma distribution has been widely used to approximate the probability density function (PDF) of monthly rainfall totals. However, there is no natural way to extend this method directly to obtain a joint PDF for rainfall densities associated with two or more months, unless the monthly totals are independent. I propose a modified method to construct a suitable PDF using parameters from the maximum likelihood estimate for a marginal Gamma distribution and a series of associated Laguerre polynomials. This series of special functions allows us to match the correlation between monthly totals and to match the observed moments with any level of precision needed. The joint PDF for two months is constructed using a sum of products of associated Laguerre polynomials. In order to get an analytic expression for the marginal distributions and the associated cumulative probabilities, it is convenient to use a weighted total and a weighted proportion contributed from the first month. The method makes extensive use of well-known formulae from the theory of special functions. The cumulative marginal probability density for the weighted total and the cumulative conditional probability density for the weighted proportion are used to generate simulated rainfall totals for each month in a two month period. In theory the simulated data is statistically identical to the observed data. In practice we apply standard statistical methods to check that the simulated data is consistent with the observed data. This method can be extended to the general case of any number of months, but computationally is restricted to only three. For this reason an alternative method is proposed to generate synthetic data for more than three months, which uses groups and subgroups of months, but still retains the characteristics of the original PDF. Although the series method could also be used to model a sequence of days, I propose an alternative method using Markov processes. This method will match a sequence of daily totals, generated from a probability transition matrix, to the monthly total generated by the series method. This methodology allows the research team to simulate certain special cases such as droughts and prolonged periods of high rainfall. These unusual events are of great interest in catchment planning and management.thesis (PhDMathematics)--University of South Australia, 2004.
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"Improved estimation of catchment rainfall for continuous simulation modelling." Thesis, 2005. http://hdl.handle.net/10413/2685.
Full textAbstract:
Long sequences of rainfall at fme spatial and temporal details are increasingly required, not only for hydrological studies, but also to provide inputs for models of crop growth, land fills, tailing dams, disposal of liquid waste on land and other environmentally-sensitive projects. However, rainfall records from raingauges frequently fail to meet the requirements of the above studies. Therefore, it is important to improve the estimation of the depth and spatial distribution of rainfall falling over a catchment. A number of techniques have been developed to improve the estimation of the spatial distribution of rainfall from sparsely distributed raingauges. These techniques range from simple interpolation techniques developed to estimate areal rainfall from point rainfall measurements, to statistical and deterministic models, which generate rainfall values and downscale the rainfall values based on the physical properties of the clouds or rain cells. Furthermore, these techniques include different statistical methods, which combine the rainfall information gathered from radar, raingauges and satellites. Although merging the radar and raingauge rainfall fields gives a best estimate of the "true rainfall field", the length of the radar record and spatial coverage of the radar in a country such as South Africa is relatively short and hence is of limited use in hydrological studies. Therefore, the relationship between the average merged rainfall value for a catchment and a "driver" station, which is selected to represent rainfall in the catchment, is developed and assessed in this study. Rainfall data from the Liebenbergsvlei Catchment near Bethlehem in the Free State Province and a six-month record of radar data are used to develop relationships between the average merged subcatchment rainfall for each of the Liebenbergsvlei subcatchments and a representative raingauge selected to represent the rainfall in each of the subcatchments. The relationships between daily raingauges and the average rainfall depth of the subcatchments are generally good and in most of the subcatchments the correlation coefficient is greater than 0.5. It was also noted that, in most of the subcatchments, the daily raingauges overestimate the average areal rainfall depth of the subcatchments. In addition, the String of Beads Model (SBM) developed by Clothier and Pegram (2002) was used to generate synthetic rainfall series for the Liebenbergsvlei catchments. The SBM is able to produce rainfall values at a spatial resolution of IxI km with a 5 minute temporal resolution. The SBM is a high-resolution space-time model of radar rainfall images, which takes advantage of the detailed spatial and temporal information captured by weather radar and combines it with the long-term seasonal variation captured by a network of daily raingauges. Statistics from a 50 year period of generated rainfall values were compared with the statistics computed from a 50 year raingauge data series, and it was found that the generated rainfall values mimic the rainfall data from the raingauges reasonably well. The relationship developed between the merged catchment rainfall values and driver rainfall station values, which are selected to represent the mean areal rainfall of the subcatchment, was used to adjust the Conventional Driver rainfall Station (CDS) into Modified Driver Station (MDS) values. Streamflow was simulated using both the CDS and MDS rainfall compared against the observed streamflow from the Liebenbergsvlei catchment. In general, the streamflow simulated by the ACRU model do not correlate well with the observed streamflow, which is attributed to unrealistic observed flow and inter-catchments transfers of water. However, it is noted that the volume of streamflow simulated with the MDS rainfall is only 71 % of that simulated with the CDS rainfall, thus highlighting the limitation of using the CDS rainfall approach for modelling and the need to apply the methodology to improve the estimation of catchment rainfall developed in this study to other catchments in South Africa.Thesis (M.Sc.)-University of KwaZulu-Natal, 2005.
27
Nguyen, Hiep Van. "Numerical simulations of airflow and weather during the summer over the island of Oahu." Thesis, 2006. http://hdl.handle.net/10125/20707.
Full text
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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.
Full textAbstract:
"May 2002" Includes list of papers published during this study Errata slip inserted inside back cover of v. 1 Includes bibliographical references (leaves 331-357) V. 1. [Text} -- v. 2. Appendices Develops an alternative design flood estimation methodology. Establishing a relationship between catchment characteristics and the rainfall excess frequency duration proportions enables the definition of these proportions for generic catchment types, increasing the potential for translation to catchments with limited data but similar hydrographic properties, thereby improving design process.
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Smithers, Jeffrey Colin. "Development and evaluation of techniques for estimating short duration design rainfall in South Africa." Thesis, 1998. http://hdl.handle.net/10413/7756.
Full textAbstract:
The objective of the study was to update and improve the reliability and accuracy of short
duration (s 24 h) design rainfall values for South Africa. These were to be based on
digitised rainfall data whereas previous studies conducted on a national scale in South Africa
were based on data that were manually extracted from autographic charts. With the longer
rainfall records currently available compared to the studies conducted in the early 1980s,
it was expected that by utilising the longer, digitised rainfall data in conjunction with
regional approaches, which have not previously been applied in South Africa, that more
reliable short duration design rainfall values could Ix: estimated.
A short duration rainfall database was established for South Africa with the majority of the
data contributed by the South African Weather Bureau (SAWB). Numerous errors such as
negative and zero time steps were identified in the SAWB digitised rainfall data. Automated
procedures were developed to identify the probable cause of the errors and appropriate
adjustments to the data were made. In cases where the cause of the error could be
established, the data were adjusted to introduce randomly either the minimum, average or
maximum intensity into the data as a result of the adjustment. The effect of the adjustments
was found to have no significant effect on the extracted Annual Maximum Series (AMS).
However, the effect of excluding erroneous points or events with erroneous points resulted
in significantly different AMS. The low reliability of much of the digitised SAW B rainfall
data was evident by numerous and large differences between daily rainfall totals recorded
by standard, non-recording raingauges, measured at 08:00 every day, and the total rainfall
depth for the equivalent period extracted from the digitised data. Hence alternative
techniques of estimating short duration rainfall values were developed, with the focus on
regional approaches and techniques that could be derived from daily rainfall totals measured
by standard raingauges.
Three approaches to estimating design storms from the unreliable short duration rainfall
database were developed and evaluated. The first approach used a regional frequency
analysis, the second investigated scaling relationships of the moments of the extreme events
and the third approach used a stochastic intra-daily model to generate synthetic rainfall
series.
In the regional frequency analyses, 15 relatively homogeneous rainfall clusters were
identified in South Africa and a regional index storm based approach using L-moments was
applied. Homogeneous clusters were identified using site characteristics and tested using
at-site data. The mean of the AMS was used as the index value and in 13 of the 15 relatively
homogeneous clusters the index value for 24 h durations were well estimated as a function
of site characteristics only, thus enabling the estimation of 24 h duration design rainfall
values at any location in South Africa.
In 13 of the 15 clusters the scaling properties of the moments of the AMS were used to
successfully estimate design rainfall values for duration < 24h, using the moments of the
AMS extracted from the data recorded by standard raingauges and regional relationships
based on site characteristics. It was found that L-moments scaled better and over a wider
range of durations than ordinary product moments.
A methodology was developed for the derivation of the parameters for two Bartlett-Lewis
rectangular pulse models using only standard raingauge data, thus enabling the estimation
of design values for durations as short as 1 h at sites where only daily rainfall data are
available.
In view of the low reliability of the majority of short duration rainfall data in South Africa,
it is recommended that the regional index value approach be adopted for South Africa, but
scaled using values derived from the daily rainfall data. The use of the intra-daily stochastic
rainfall models to estimate design rainfall values is recommended as further independent
confirmation of the reliability of the design values.Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 1998.
30
Knoesen, Darryn Marc. "The development and assessment of techniques for daily rainfall disaggregation in South Africa." Thesis, 2005. http://hdl.handle.net/10413/3439.
Full textAbstract:
The temporal distribution of rainfall , viz. the distribution of rainfall intensity during a storm, is an important factor affecting the timing and magnitude of peak flow from a catchment and hence the flood-generating potential of rainfall events. It is also one of the primary inputs into hydrological models used for hydraulic design purposes. The use of short duration rainfall data inherently accounts for the temporal distribution of rainfall, however, there is a relative paucity of short duration data when compared to the more abundantly available daily data. One method of overcoming this is to disaggregate courser-scale data to a finer resolution, e.g. daily to hourly. A daily to hourly rainfall disaggregation model developed by Boughton (2000b) in Australia has been modified and applied in South Africa. The primary part of the model is the . distribution of R, which is the fraction of the daily total that occurs in the hour of maximum rainfall. A random number is used to sample from the distribution of R at the site of interest. The sample value of R determines the other 23 values, which then undergo a clustering procedure. This clustered sequence is then arranged into 1 of 24 possible temporal arrangements, depending when the hour the maximum rainfall occurs. The structure of the model allows for the production of 480 different temporal distributions with variation between uniform and non-uniform rainfall. The model was then regionalised to allow for application at sites where daily rainfall data, but no short duration data, were available. The model was evaluated at 15 different locations in differing climatic regions in South Africa. At each location, observed hourly rainfall data were aggregated to yield 24-hour values and these were then disaggregated using the methodology. Results show that the model is able to retain the daily total and most of the characteristics of the hourly rainfall at the site, for when both at-site and regional information are used. The model, however, is less capable of simulating statistics related to the sequencing of hourly rainfalls, e.g. autocorrelations. The model also tends to over-estimate design rainfalls, particularly for the shorter durations .Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2005.
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Crimp, Steven Jeffrey. "Simulating sea-surface temperature effects on Southern African rainfall using a mesoscale numerical model." Thesis, 1996. https://hdl.handle.net/10539/24293.
Full textAbstract:
Dissertation submitted to the Faculty of Science, University of the Witwatersrand, for
completion of the Degree of' Master of ScienceThe atmospheric response of the Colorado State University Regional Atmospheric Modelling System (RAMS) to sea-surface temperature anomaliesis investigated. A period of four days was chosen from 21 to 24 January 1981, where focus was placed on the development and dissipation of a tropical-temperate trough across Southern Africa. Previous experimenting this mesoscalenumerical model have detemined the kinematic, moisture, and thermodynamic nature of these synoptic features. The research in this dissertation focuses specifically on the sensitivity of the numerical model's simulated responses to positive sea-surface temperature anomalies. Three separate experiments were devised, in which positive anomalous temperatures were added to the ocean surface north of Madagascar (in the tropical Indian Ocean), at the region of the Agulhas Current retroflection, and along the tropical African west coast (in the Northern Benguela and Angola currents). The circulation aspects of each sensitivity test were investigated through the comparison of simulated variables such as vapour and cloud mixing ratios, temperature, streamlines and vertical velocity, with the same variables created by a control simulation. The results indicate that for the first sensitivity test, (the Madagascar anomaly), cyclogenesis was initiated over the area of modified sea temperatures which resulted in a marginal decrease in continental precipitation. The second sensitivity test (over the Agulhas retroflection) produced a much smaller simulated response to the addition of anomalously warm sea temperatures than the tropical Indian Ocean anomaly. Instability and precipitation values increased over the anomalously warm retroflection region, and were slowly transferred along the westerly wave perturbation and the South African east coast. The third sensitivity experiment showed a predominantly localised simulated increase in precipitation over Gabon and the Congo, with the slow southward progression of other simulated circulation differences taking place. The small perturbations in each of the simulated meteorological responses are consistent with the expected climate response to anomalously warm sea-surface temperatures in those areas.
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