Dissertations / Theses on the topic 'Rainfall frequency analysi'

Frequency analysis is a vital tool when nding a well-suited probability distributionin order to predict extreme rainfall. The regional frequency approach have beenused for determination of homogeneous regions, using 11 sites in Skane, Sweden. Todescribe maximum annual daily rainfall, the Generalized Logistic (GLO), GeneralizedExtreme Value (GEV), Generalized Normal (GNO), Pearson Type III (PE3),and Generalized Pareto (GPA) distributions have been considered. The method ofL-moments have been used in order to nd parameter estimates for the candidatedistributions. Heterogeneity measures, goodness-of-t tests, and accuracy measureshave been executed in order to accurately estimate quantiles for 1-, 5-, 10-, 50- and100-year return periods. It was found that the whole province of Skane could beconsidered as homogeneous. The GEV distribution was the most consistent withthe data followed by the GNO distribution and they were both used in order toestimate quantiles for the return periods. The GEV distribution generated the mostprecise estimates with the lowest relative RMSE, hence, it was concluded to be thebest-t distribution for maximum annual daily rainfall in the province.

Increased extreme precipitation has been documented in many regions around the world, in- cluding central and northern Europe. Global warming increases average temperature, which in turn enhances atmospheric water holding capacity. These changes are believed to increase the frequency and/or intensity of extreme precipitation events. In determining the design storm, or a worst probable storm, for infrastructure design and failure risk assessment, experts commonly assume that statistics of extreme precipitation do not change significantly over time. This so- called notion of stationarity assumes that the statistics of future extreme precipitation events will be similar to those of historical observations. This study investigates the consequences of using a stationary assumption as well as the alternative: a non-stationary framework that con- siders temporal changes in statistics of extremes. Here we evaluate stationary and non-stationary return levels for 10-year to 50-year extreme precipitation events for different durations (1-day, 2-day, ..., 7-day precipitation events), based on the observed daily precipitation from Sweden. Non-stationary frequency analysis is only considered for stations with statistically significant trends over the past 50 years at 95% confidence (i.e., 15 to 39 % out of 139 stations, depend- ing on duration, 1-day, 2-day, ..., 7-day). We estimate non-stationary return levels using the General Extreme Value distribution with time-dependent parameters, inferred using a Bayesian approach. The estimated return levels are then compared in terms of duration, recurrence in- terval and location. The results indicate that a stationary assumption might, when a significant trend exists, underestimate extreme precipitation return levels by up to 40 % in Sweden. This report highlights the importance of considering better methods for estimating the recurrence in- terval of extreme events in a changing climate. This is particularly important for infrastructure design and risk reduction.
Ökad extrem nederbörd har dokumenterats globalt, däribland centrala och norra Europa. Den globala uppvärmningen medför en förhöjd medeltemperatur vilket i sin tur ökar avdunstning av vatten från ytor samt atmosfärens förmåga att hålla vatten. Dessa förändringar tros kunna öka och intensifiera nederbörd. Vid bestämning av dimensionerande nederbördsintensiteter för byggnationsprojekt antas idag att frekvensen och storleken av extrem nederbörd inte kommer att förändras i framtiden (stationäritet), vilket i praktiken innebär ingen förändring i klimatet. Den här studien syftar till att undersöka effekten av en icke-stationärt antagande vid skattning av dimensionerande nederbördsintensitet. Icke-stationära och stationära nerderbördsintensiteter föråterkomsttider mellan 10 och 100år bestämdes utifrån daglig och flerdaglig svensk nederbörds- data. Nederbördintensiteterna bestämdes med extremvärdesanalys i mjukvaran NEVA, där den generella extremvärdesfördelningen anpassades till årlig maximum nederbörd på platser i Sverige som påvisade en ökande trend under de senaste 50åren (15% till 39 % utav 139 stationer, beroende på varaktighet). De dimensionerande nederbördsintensiteterna jämfördes sedan med avseende på varaktighet, återkomsttid och plats. Resultaten indikerade på att ett stationärt antagande riskerar att underskatta dimensionerande nederbördsintensiteter för en viss återkomsttid med upp till 40 %. Detta indikerar att antagandet om icke-stationäritet har större betydelse för olika platser i Sverige, vilket skulle kunna ge viktig information vid bestämning av dimensionerande regnintensiteter.

An accurate estimation of hydrologic extremes is fundamental for its manyimplications on engineering design, flood quantification and mapping, insurance and re-insurance purposes, policy-making. Traditional methods,hinging on the Generalized Extreme Value (GEV) distribution, are founded on often-overlooked and untested assumptions, make an ineffective use of the available data, and are ill-suited for accounting for inter-annual variability. With the aim of improving the estimation accuracy of high return period extremes, this dissertation focuses on the Metastatistical Extreme Value Distribution (MEVD), an approach introduced to relax some of the limitations of the traditional Extreme Value Theory. The present work first analyzes the definition of the optimal MEVD formulation as a function of local climatic factors and of key statistical properties of rainfall at the daily scale. It concludes that the inter-annual variability of rainfall statistical properties plays an important role in the definition of the optimal time window to be used for parameter estimation. In the largest amount of cases examined, except for very dry climates, with few rainy days, the analysis window should be kept to the minimum of 1 year in order to resolve the time variability of the distributions. The use of short time windows also makes the MEVD a suitable approach to study extremes in a changing climate, as it contributes to its ability to resolve inter-annual variability. Up to now, the MEVD has been applied mainly to rainfall (at the daily and hourly scale). Here, for the first time, the MEVD is used to study streamflow data, developing a flood frequency analysis MEVD-based on series of flow peaks in the Continental United States. Moreover, the impact of El Niño Southern Oscillation (ENSO) on flood regimes is evaluated. In the comparison with the GEV, results show the outperformance of the MEVD in ~76% of the analyzed stations, with a significant reduction in the estimation error especially when considering return periods much higher than the size of the sample used to estimate the distributional parameters. Yet, a negligible improvement in the estimation of extreme floods was found when stratifying peaks according to ENSO phases. In the end, leveraging the appealing property of the MEVD to naturally include mixtures of distributions in its formulation, a MEVD that distinguishes between non-Tropical Cyclones (TCs) and Tropical Cyclones-induced rainfall is applied to several American metropolitan areas. The impact of TCs on rainfall is well distinguishable, and the use of a mixed MEVD approach resulted beneficial in several cases. Its advantage in the reduction of the estimation error when compared to the single-distribution MEVD was found to be more significant when considering cumulative values of rainfall over consecutive days, due to the prolonged impact TCs have on rainfall over time.

Statistical estimation of design rainfall is considered a consolidated topic in hydrology. However, extreme rainfalls and their consequences still constitute one of the most critical natural risks worldwide, particularly in urban environments. Additional efforts for improving the spatio-temporal analysis of extreme rainfalls are then required, particularly at the regional scale. In this work, a new set of data and techniques for improving the spatial statistical analysis of extreme rainfall is proposed. Italy is considered a challenging case study, due to its specific geographic and orographic settings, associated with recurring storm-induced disasters. At first, the rain-gauge data patchiness resulting from the evolution of the monitoring agencies and networks, is tackled with the "patched kriging" methodology. The technique, involving a sequential annual interpolation, provides complete annual maxima series consistent with the available data. This allows to extract all the information avaialble from the gauge records, considering also the information "hidden" in the shortest series, increasing the robustness of the results. Interpolation techniques, however, can only reflect the estimation variance determined by the spatial and temporal data resolution. Additional improvements can be obtained integrating the rain gauge information with remote sensing products, able to provide more details on the spatial structure of rainstorms. In this direction, a methodology aimed at maximizing the efficiency of weather radar when dealing with large rainfall intensities is developed. It consists in a quasi-real-time calibration procedure, adopting confined spatial and temporal domains for an adaptive estimation of the relation between radar reflectivity and rainfall rate. This allows one to follow the well-known spatio-temporal variability of the reflectivity-rainfall relation, making the technique suitable for a systematic operational use, regardless of the local conditions. The methodology, applied in a comprehensive case study reduces the bias and increases the accuracy of the radar-based estimations of severe rainfall intensities. The field of the satellite estimation of preciptation is then explored, by analyzing the ability of both the Tropical Rainfall Measurement Mission (TRMM) and the recently launched Global Precipitation Measurement (GPM) mission to help identifying the timing of severe rainfall events on wide spatial domains. For each considered product, the date of occurrence of the most intense annual daily records are identified and compared with the ones extracted from a global rain-gauge database. The timing information can help in tracking the pattern of deep convective systems and support the identification of localized rainfall system in poorly gauged areas. The last part of the work deals with the analysis of rainfall extremes at the country scale, with a particular focus on the most severe rainfall events occurred in Italy in the last century. Many of these events have been studied as individual case studies, due to the large recorded intensities and/or to their severe consequences, but they have been seldom expressly addressed as a definite population. To try to provide new insights in a data-drived approach, a comprehensive set of annual rainfall maxima has been compiled, collecting data from the different regional authorities in charge. The database represents the reference knowledge for extremes from 1 to 24 hours durations in Italy, and includes more than 4500 measuring points nationwide, with observation spanning the period 1916-2014. Exploratory statistical analyses for providing information on the climatology of extreme rainfall at the national scale are carried out and the stationarity in time of the highest quantiles is analysed by pooling up all the data for each duration together. The cumulative empirical distributions are explored looking for clues of the existence of a class of "super-extremes" with a peculiar statistical behavior. The analysis of the spatial the distribution of the records exceeding the 1/1000 overall empirical probability shows an interesting spatial clustering. However, once removed the influence of the uneven density of the rain gauge network in time and space, the spatial susceptibility to extraordinary events seems quite uniformly distributed at the country scale. The analyses carried out provide quantitative basis for improving the rainstorm estimation in gauged and ungauged locations, underlining the need of further research efforts for providing maps for hydrological design with uniform reliability at the various scales of technical interest.

A regional envelope curve (REC) of flood flows summarises the current bound on our experience of extreme floods in a region. RECs are available for most regions of the world. Recent scientific papers introduced a probabilistic interpretation of these curves and formulated an empirical estimator of the recurrence interval T associated with a REC, which, in principle, enables us to use RECs for design purposes in ungauged basins. The main aim of this work is twofold. First, it extends the REC concept to extreme rainstorm events by introducing the Depth-Duration Envelope Curves (DDEC), which are defined as the regional upper bound on all the record rainfall depths at present for various rainfall duration. Second, it adapts the probabilistic interpretation proposed for RECs to DDECs and it assesses the suitability of these curves for estimating the T-year rainfall event associated with a given duration and large T values. Probabilistic DDECs are complementary to regional frequency analysis of rainstorms and their utilization in combination with a suitable rainfall-runoff model can provide useful indications on the magnitude of extreme floods for gauged and ungauged basins. The study focuses on two different national datasets, the peak over threshold (POT) series of rainfall depths with duration 30 min., 1, 3, 9 and 24 hrs. obtained for 700 Austrian raingauges and the Annual Maximum Series (AMS) of rainfall depths with duration spanning from 5 min. to 24 hrs. collected at 220 raingauges located in northern-central Italy. The estimation of the recurrence interval of DDEC requires the quantification of the equivalent number of independent data which, in turn, is a function of the cross-correlation among sequences. While the quantification and modelling of intersite dependence is a straightforward task for AMS series, it may be cumbersome for POT series. This paper proposes a possible approach to address this problem.

The conventional approach to the frequency analysis of extreme rainfall is complicated by non-stationarity resulting from climate change. In this study significant trends in extreme rainfall are detected using statistical trend tests (Mann-Kendall test and t-test) for all over the Korean Peninsula. The violation of the stationarity for 1 hour annual maximum series is detected for large part of the area especially for southwestern and northeastern regions. For stations showing non-stationarity, the non-stationary generalized extreme value (GEV) distribution model with a location parameter in the form of linear function of time makes significant improvement in modeling rainfall extremes when compared to the stationary GEV model. The Bartlett-Lewis rainfall model is used to generate annual maximum series for the purpose of generating the Intensity-Duration-Frequency (IDF) curve. Using 100 sets of 50 year synthetic annual maxima, it is found that the observed annual rainfall maximum series are reasonably represented by the model. The observed data is perturbed by change factors to incorporate the climate change scenario from the WRF (Weather Research and Forecasting) regional climate model into IDF estimates. The IDF curves for the future period 2040-2079 show highest estimates for all return periods and rainfall durations. The future IDF estimates show significant difference from the IDF estimates of the historical period (1968-2000). Overall, IDF curves show an increasing tendency over time. A historical and future climate simulation is evaluated over the Colorado River Basin using a 111-year simulation (1969-2079) of the WRF climate change scenario. We find the future projections show statistically significant increases in temperature with larger increases in the northern part of the basin. There are statistically insignificant increases in precipitation, while snowfall shows a statistically significant decrease throughout the period in all but the highest elevations and latitudes. The strongest decrease in snowfall is seen at high elevations in the southern part of the basin and low elevations in the northern part of the basin.

Les crues – telles que les laves torrentielles – engendrées dans les torrents lors de fortes précipitations peuvent mobiliser de grande quantité de sédiments. Lorsqu'elles atteignent les zones urbanisées, elles peuvent mettre en dangers à la fois les personnes et les biens. Les approches visant à réduire le risque torrentiel se basent largement sur des seuils intensité-durée de pluie qui déterminent les conditions minimum de déclenchement d’une lave torrentielle. Pourtant, ces seuils sont sujets à une forte variabilité liée, non seulement aux différences inter-sites, mais aussi à la méthode appliquée lors de leur établissement. De plus, ils peuvent entraîner des fausses prédictions, l’intensité et la durée de l’épisode de pluie n’étant pas les seules variables explicatives. Ce travail de thèse vise (i) à fournir un cadre méthodologique rigoureux pour l’établissement des seuils de pluie afin de limiter les sources de variabilité, et (ii) à améliorer leurs performances en considérant à la fois les facteurs de déclenchement et de prédisposition. Il s’appuie sur les données d’un observatoire des crues torrentielles, mis en place dans les Alpes françaises en 2011 sur les torrents très actifs du Manival et du Réal. Dans un premier temps, les images et mesures hautes-fréquences collectées entre 2011 et 2016 ont été analysées afin de détecter et de caractériser les crues torrentielles. Pour appréhender la diversité des écoulements observés, une classification phénoménologique a été proposée. Dans un second temps, la condition minimum intensité-durée de pluie requise pour déclencher une lave torrentielle a été établie. La sensibilité du seuil à la définition d’un épisode de pluie a été évaluée. Dans un troisième temps, un modèle de régression logistique a été implémenté pour discriminer les épisodes de pluies critiques qui n’ont pas engendré de lave torrentielle. Il a permis de sélectionner les variables explicatives les plus pertinentes. Finalement, des pistes de travail ont été avancées pour (i) passer de conditions critiques établies à une échelle locale vers une échelle régionale, en perspective d’une application au sein d’un système d’alerte dédié aux risques hydrométéorologiques, et (ii) passer des conditions de déclenchement d’une lave torrentielle dans la zone de production sédimentaire aux conditions de propagation jusqu'aux zones à enjeux
Flows – such as debris flows – caused by heavy rainfalls in torrents can mobilise a huge amount of sediments. When they reach the urbanised areas, they may endanger the people’s safety or cause damages. Approaches aimed at mitigating torrential risk widely rely on rainfall intensity-duration thresholds which determine the minimum debris-flow triggering conditions. However, these thresholds suffer from a high variability related not only to inter-site differences but also to the method applied to design them. In addition, they are likely to cause false prediction because the intensity and the duration of the rainfall event are not the only explanatory variables. This PhD research work aim (i) to provide a rigorous methodological framework for designing rainfall threshold in order to limit the variability sources, and (ii) to improve their performances by including both the triggering and the predisposing factors. It is supported by field observations stemming from high-frequency monitoring stations installed since 2011 on two very active debris flow-prone torrents in the French Alps: the Manival and the Réal. First, the images and data gathered between 2011 and 2016 were analysed in order to detect and characterise the sediment laden-flows. To deal with the variety of recorded flows, a phenomenological classification was performed. Second, the minimum intensity-duration threshold for debris-flow triggering was assessed. The threshold sensitivity to the rainfall event definition was estimated. Third, a logistic regression model was used to discriminate the critical rainfall events which do not lead to a debris flow. It makes it possible to select the most relevant explanatory variables. At last, several avenues of work were proposed (i) to move the knowledge of debris-flow initiation conditions from a local to a regional level, with a view to application in a warning system dedicated to hydrometeorological risks, and (ii) to improve the ability to predict, not the debris-flow triggering in the production zone, but the debris-flow propagation up to the area concerned

Flooding is of great concern world-wide, causing damage to infrastructure, property and loss of life. Low-income countries, in particular, can be negatively affected by flood events due to their inherent vulnerabilities. Moreover, data to perform studies for flood risk management in low-income regions are often scarce or lacking sufficient quality. This thesis proposes new methodologies and explores the use of unconventional sources of information in flood hazard assessment in areas where the quantity or sufficient quality of traditional hydrometrical data are lacking.  One method was developed to account for errors in spatially averaged rainfall, from a sparse rain-gauge network, used as input to a rainfall-runoff model. A spatially-averaged and event-dependent rainfall depth multiplier led to improvements of the hydrographs at calibration. And by using a distribution of the multiplier, identified from previous events in the catchment, improvement in predictions could also be obtained. A second method explored the possibility of reproducing an unmeasured extreme flood event using a combination of models, post-event data, precipitation and an uncertainty-analysis framework. This combination allowed the identification of likelihood-associated parameter sets from which the flood hazard map for the extreme event could be obtained. A third and fourth study made at the regional scale explored the value of catchment similarities, and the effects of climate on the hydrological response of catchments. Flood frequency curves were estimated for 36 basins, assumed ungauged, using regional information of short flow records, and local information about the frequency of the storm. In the second regional study, hydro-climatic information provided great value to constrain predictions of series of daily flow from a hydrological model. Previously described methods, used in combination with unconventional information within an uncertainty analysis, proven to be useful for flood hazard assessment at basins with data limitations. The explored data included: post-event measurements of an extreme flood event, hydro-climate regional information and local precipitation data. The methods presented in this thesis are expected to support development of hydrological studies underpinning flood-risk reduction in data-poor areas.
Extremt höga vattenflöden ställer till stora problem i hela världen. De skadar infrastruktur och egendom och orsakar död. Framför allt kan låg- och medelinkomstländer vara väldigt sårbara för extrema flöden. I dessa länder saknas dessutom ofta data som behövs för att kunna bedöma översvämningsrisker, eller så finns bara data av dålig kvalitet. Denna avhandling föreslår nya metoder som använder okonventionella informationskällor vid bedömning av översvämningsrisker i områden där traditionella hydrologiska data saknas eller har otillräcklig kvalitet. En metod utvecklades för att ta hänsyn till fel i rumslig medelnederbörd beräknad från ett glest nät av nederbördsmätare att användas som indata i en nederbörds-avrinningsmodell. Användning av en multiplikator för medelvärdesbildad nederbörd, i tid och rum, för enskilda högflödestillfällen ledde till förbättrad modellkalibrering. Genom att använda multiplikatorfördelningar, identifierade från tidigare högflödestillfällen i avrinningsområdet, kunde också prognoser förbättras. En andra metod använde sig av möjligheten att reproducera ett extremt högflöde inom ramen för en osäkerhetsanalys med hjälp av en kombination av modeller, nederbördsdata och data som uppmätts i efterhand. Denna kombination gjorde det möjligt att identifiera parametervärdesuppsättningar med hophörande sannolikheter ur vilka det gick att erhålla en översvämningskarta för det höga flödet. En tredje och fjärde studie i regional skala utforskade värdet av likheter mellan avrinningsområden och hur områdenas hydrologiska gensvar beror av klimatet. Kurvan för kumulativa högflödesfrekvenser (flood frequency curve, FFC) kunde skattas med hjälp av lokal nederbördsinformation och regional information om korta tidsserier av vattenföring från 36 avrinningsområden som antogs sakna vattenföringsdata. I den andra regionala studien visade sig hydroklimatisk information av värde för att avgränsa godtagbara prognoser för daglig vattenföring från en hydrologisk modell. Tidigare beskrivna metoder, använda tillsammans med okonventionell information inom ramen för en osäkerhetsanalys, visade sig vara användbara för att bedöma översvämningsrisker i avrinningsområden med databegränsningar. Bland utforskade data fanns: mätningar i efterhand av ett extremt högflöde, hydroklimatisk regional information och lokala nederbördsmätningar. Metoderna i denna avhandling förväntas kunna stödja utvecklingen av hydrologiska studier av höga flöden och översvämningar i områden med bristande datatillgång.
Las inundaciones ocasionan daños a la infraestructura, propiedad y pérdida de vidas a nivel mundial. Los países en desarrollo son los más vulnerables a inundaciones, la calidad y cantidad de datos hidro-climatológicos disponibles en los mismos dificulta el desarrollo de estudios para la evaluación de riesgo a esta amenaza. Esta tesis propone métodos en la que se hace uso de fuentes de información no-convencionales para la evaluación de riesgo por inundación en regiones con datos escasos o limitados. Un método considera el error asociado a la precipitación promedio sobre cuencas en modelos lluvia-escorrentía como un factor multiplicador del histograma del evento. El uso de la precipitación promedio junto con una distribución probabilística del factor multiplicador como datos de entrada a un modelo de lluvia-escorrentía mejoraron los hidrogramas durante los periodos de calibración y predicción. Un segundo método exploró la posibilidad de reproducir un evento extremo de inundación usando una combinación de modelos hidrológicos e hidráulico, un análisis de incertidumbre, datos hidrométricos recopilados después del evento y datos de precipitación registrados durante-el-evento. Dicha combinación permitió la identificación de los parámetros de los modelos y la elaboración un mapa de amenaza por inundaciones para dicho evento. Adicionalmente, se estimaron curvas de frecuencia de inundaciones para 36 cuencas, asumidas no aforadas, mediante un método de regionalización que usa registros de caudal de corta duración disponibles en la región. Dichas curvas fueron extendidas haciendo uso de información local sobre la frecuencia de las tormentas. Se encontró que la información hidro-climatológica tiene un gran valor para reducir el rango de incertidumbre de las simulaciones de caudal diaria de un modelo hidrológico. Los métodos anteriores se usaron en combinación con información no-convencional dentro de un análisis de incertidumbre y han probado su utilidad para la evaluación de riesgo por inundaciones en cuencas con registros escasos o limitados. Los datos utilizados en esta tesis incluyen datos hidrométricos recopilados pasado el evento, registros hidro-climatológicos regionales y precipitación local. Se espera que los métodos presentados aquí contribuyan al desarrollo de estudios hidrológicos importantes para la reducción del riesgo por inundaciones en regiones con déficit de registros hidro-climatológicos.

碩士
國立臺灣大學
統計碩士學位學程
107
The Annual Maximum Series (AMS) method is a conventional way of conducting rainfall frequency analysis, which plays a crucial role in hydrology engineering in terms of hydrological risk assessment. Given any design duration, the method retrieves only the maximum rainfall within a year and approximate the Annual Maximum Rainfall (AMR) distribution by the Generalized Extreme Value (GEV) distribution according to the Extremal Types Theorem. However, the GEV approximation is inappropriate since AMS is prone to have insufficient sample size and does not take storm events and storm types into account. To overcome the above problems, the Event Maximum Series (EMS) method is proposed. The EMS method classifies storm events in Taiwan into Typhoon, Meiyu, frontal rain and convective storm. The AMR distribution of a given storm type can be derived from the corresponded event occurrence distribution and event rainfall distribution, and the AMR distribution of all events is a mixture distribution of different types of AMR distribution. As a result, the EMS method provides a more suitable and effective design-rainfall than the traditional approach. The EMS method outperforms the AMS approach in many ways. In Monte Carlo simulation, the EMS method is superior to AMS method in terms of the bias and Root Mean Squared Error (RMSE). Three stations in Taiwan are selected for frequency analysis and peak flow analysis, the results show that EMS method can avoid overestimation, capture larger peak flow events and is less affected by outliers. Finally, simulation and real data analyses of confidence interval (CI) through bootstrap method are performed. Although CI of both method does not achieve the theoretical coverage rate, the coverage rate of EMS method is more stable in different return period.

碩士
中原大學
土木工程研究所
89
Precipitation is a significant factor for hydraulic designs and project schedule control. It is a very important subject by using the past rainfall records and certain analysis methods to find the distributions of rainfall for various hydraulic engineering designs. In this study the rainfall data for one hundred years are collected from the Central Weather Bureau in the Taipei Rainfall Station. This study is focus on the long duration of rainfall analysis. Using the annual maximum series and the annual exceedance series of daily rainfall to analyze and to fit each distribution. The Goodness-of-Fit Test and the Standard Error Method are used to compare the feasibility of the distributions. The results of this study show that the Pearson TypeⅢ distribution is the best choice for both annual maximum series and annual exceedance series analysis.

碩士
國立臺灣大學
農業工程學系
82
The data files of rainfall including the weather stations of CentralWeather Bureau, Taiwan Provincial Water Conservancy Bureau, and Taiwan Electric Power Company were collected and analysed in order todevelop the relations among rainfall intensity , duration and frequency for Taiwan area. The annual maximum serious is used for selection of rainfall in frequency analysis. The criteria for selection of weather stations is those have record length longer than ten years. In this research, 167 stations were chosen, which include 21 stations from Central Weather Bureau, 96 stations from Taiwan Provincial Water Conservancy Bureau, and 50 stations from Taiwan Eletric Power Company. Frequency analysis was done for a total of 167 stations based on Pearson Type of III distribution . The results from frequency analysis is used as the source data for developing rainfall intensity , duration and frequency relations. Then, multiple regression is applied to estimate the coefficients of Rainfall Intensity - Duraion - Frequency formula. The regression is based on the source data from frequency analysis corresponding return period and duration. In order to improve the accuracy of Rainfall Intensity - Duration - Frequency formula, The rainfall duration was divided into long duration and short duration. The long duration is five to seventy - two hours, and the short duration is ten minutes to five hours. The established regional Rainall Intensity - Duration - Frequency relationship for Taiwan has been preliminarily verified and shown applicable in planning and design of hydraulic works.

碩士
逢甲大學
水利工程與資源保育學系
104
Regional analysis is a very important part of the design in hydraulic engineering. Base on measured data from the past,this study can find correlations between the stations.Therefore, regional analysis solve the situation inadequate data, and creates a partition for each of rainfall in Taiwan. This study used two cluster approaches, Cluster analysis and self-organizing map (SOM) with the reference of 127 raingauge data (recorded over 20-years). Hydrological factors presented annual maximum 24-hour rainfall data (mean, standard deviation, skewness and kurtosis), and Physiographical factor displayed station locations and elevation.After this study established each rainfall characteristics partitions, this study detected partition information by L-moment method.The results showed that after adjusting rainfall characteristics data, the two classifications were likely uniformity. Next, this study used the goodness-of-fit measurement to select the best regional probability distributions of rainfall.The Cluster Analysis results show that the best regional probability distribution for 2 normal distribution ,the Gumbel I and the Pearson type III distribution were the best for 1 region.On the other hand, SOM only shows 3 normal distributions and 2 Gumbel I distributions.Finally, this study used SOM results and with Thiessen polygons method dividing Taiwan rainfall characteristics into several partition. In the absence of rainfall frequency analysis information, this storm frequency analysis results will provide a reference for the design of future project planning.

碩士
國立交通大學
土木工程學系
84
The purpose of this study is to identify appropriate probability distributions for the annual maximum precipitation of various duration at ninety-two recording rain gauging stations in Taiwan .The method used in the frequency analysis is the L-moment method along with various goodness-of-fit procedures. Also, this study aims at developing a non- dimensional rainfall intensity-duration-frequency (IDF) equations based on a rainfall intensity with 25-year return period and 1-hour duration.To enhance the accuracy of the regional analysis, the cluster analysis was applied using the parameter in the IDF equation and geographical coordinates of each station. It is found the 92 raingage stations can be clustered separated by into two areas separated by the line connecting ({EMBED Equation |} E , {EMBED Equation |} N) and ({EMBED Equation |} E , {EMBED Equation |}N), as the demarcation.In the regional analysis, empirical relationships for each groupwere developed to relate each parameter in the IDF equation to the mean annual precipitation and elevation. The regional equations for the parameters in the IDF equation can be used to estimate extreme precipitation characteristics at locations where there is no precipitation record.

碩士
國立臺灣海洋大學
河海工程學系
98
The purpose of this research is to investigate the impact of climate change on the hydrologic frequency of drought and flood in Taiwan. Totally, 83 rain gauges with records over Taiwan were selected. Based on downscaled GCM outputs under the A1B emissions scenario, frequency of the maximum consecutive dry days and maximum 1-day, 2-day, and 3-day rainfall within 2080-2099 are studied, as compared with those within 1979-1998. Daily rainfall data from 20-km mesh AOGCM are applied. Because of underestimation of the data, it would be needed to correct the downscaling data by using the quadrant conversion method. Then the corrected data for the 83 stations over Taiwan are analyzed based on the Log-Pearson type III distribution and kriging method to realize the impact of the drought and flood frequency on Taiwan. The results show that the change of the maximum consecutive dry days within 2080-2099 over Taiwan is not significant. No large-scale drought（consecutive 100 days without rainfall）occurs in the future in the return period of 100 years, and extreme rainfall would occur in the mountains and eastern region.

碩士
華梵大學
環境與防災設計學系碩士班
107
Huafan University is located in the Ta-Lun Shan area of Shih ding District, New Taipei City. It is about 430 meters to 570 meters above sea level. There is a weather station on the campus to measure the rainfall and temperature data. For slope disaster prevention there are SAA (Shape Accel Array) observation instruments to monitor slope displacement. The area of Huafan University is listed in the landslide-landslip geologically sensitive area by the Central Geological Survey. The analysis of slope displacement is more important. This study is separated into two parts. First is to analysis the characteristic of different duration rainfall intensity–duration-frequency Curve (IDF) in Huafan University, and second is to induce rainfall with tilting displacement greater than 0.5mm. The first part selects the date from 2004 to 2017 of Huafan weather station, and selects the annual maximum rainfall data from 5 minutes to 1 hour called short duration and 1 hour to 48 hours called long duration. By frequency analysis, the most suitable theoretical probability distribution is obtained, the short duration IDF and the long duration IDF are established. It is known from the study that the long duration IDF formula estimates the short duration rainfall intensity value, which is overestimated, especially when the rainfall duration is 5 minutes. The data of four days cumulative rainfall amount greater then 100mm are used to as the background value of the second part of the analysis. The second part is to select the data with the daily displacement greater than 0.5mm from SAA for the number SIS-11A and the four-day cumulative greater than 100mm, and calculate the average rainfall intensity value in two different ways. The first type is the day when the displacement occurs, as the first day, and continues to calculate forward. The second type is the three days before the tilting displacement day as the first day, and then continues to calculate backwards. Will these two methods are compared to the background values. The rainfall intensity during typhoon is widely distributed on one day and two days. The daily rainfall intensity falls between 1 (mm/day) and 305 (mm/day). The distribution of rainfall intensity on the three days and four days is concentrated. The rainfall intensity falls between 47 (mm/day) and 147 (mm/day), while the rainfall intensity of the southwest monsoon affects the four days rainfall intensity from 28 (mm/day) to 85 (mm/day). The four days rainfall intensity falls from 25 (mm/day) to 55 (mm/day). It has probability to occur tilting displacement greater than 0.5 mm when rainfall intensity is small. Keywords： Frequency Analysis、IDF、Shape Accel Array、Tilting Displacement

碩士
國立臺灣大學
農業工程學系
82
The main purpose of this study is to investigate the profound statistical characteristics for L-moments method and to use the L-moment diagram for selecting a suitable distribution.The sample estimators of L-moments are only linear combinations of the ranked observations , consequently they are subject to less bias than ordinary product moments. This is because ordinary product moment estimators such as variance and skewness require squaring and cubing the observations , respectively , which cause them to give greater weight to the observations far from the mean , resulting in substantial bias and variance. In present study , the theoretical data sets ( Gumbel & Exponential) were generated by Monte Carlo simulation and used to investigate the statistical characteristics of L-moments. The results of Monte Carlo experiments show that the L-moments estimators of parameters are more accurate than the product moments' estimators of parameter. The product moment ratios of skewness and Kurtosis are remarkably biased even for samples sizes of n=1000. The Monte Carlo simulation is performed to generate the theoretical data of PT3、LN3、GPA、UNIFORM、GUMBEL 、EXPONENTIAL distributions. The data sets are then used to verify whether the moment diagram can suitably identify their original distributions. Monte Carlo experiments reveal that the use of L-moment diagrams for selecting the suitable distribution is better than the use of product moment ratio diagrams. Moreover, the results show that it is easy to misled for selecting a suittable distribution if the product moment ratio diagrams is used. The L-moment diagrams are then used to identify the appropriate probability distribution for the rainfall data in the northern、central、southern and eastern Taiwan area.

碩士
國立交通大學
土木工程學系研究所
85
Engineers usually face a variety of uncertainties resided in the practical applications of the hydrological models. These uncertainties will affect directly the reliability of the model output,and indirectly the adequacyof water resources planning and hydraulic structure design.Aiming at the commonly used rainfall intensity-duration-frequency(IDF) formulathis study investigates its parameter uncertainty using the bootstrap resamplingmethod. In the meanwhile, the uncertainty of the regional IDF formaula developedby Yang et al.(1996)is evaluated by the frist-order approximation method.Forthermore, the representative reg ional averaged IDF formula of a given watershed can be obtained by integrating the on-site IDF formula,based on theconcept of area weighting. This regional average IDF formula can be used toestimate the design rainfall intensity of a watershed.Most of the large dams in Taiwan are designed according to the probable maximunprecipitation(PMP). However, the design of PMP is deterministic. This study,basedon the proposed regional average IDF formula, estimates the corresponding returnperiods of the PMP's at several damsites. The results provide useful informationfor the evaluation of dam safety

The thesis is concerned with development of efficient regional frequency analysis (RFA) approaches to estimate quantiles of hydrometeorological events. The estimates are necessary for various applications in water resources engineering. The classical approach to estimate quantiles involves fitting frequency distribution to at-site data. However, this approach cannot be used when data at target site are inadequate or unavailable to compute parameters of the frequency distribution. This impediment can be overcome through RFA, in which sites having similar attributes are identified to form a region, and information is pooled from all the sites in the region to estimate the quantiles at target site. The thesis proposes new approaches to RFA of precipitation, meteorological droughts and floods, and demonstrates their effectiveness. The approach proposed for RFA of precipitation overcomes shortcomings of conventional approaches with regard to delineation and validation of homogeneous precipitation regions, and estimation of precipitation quantiles in ungauged and data sparse areas. For the first time in literature, distinction is made between attributes/variables useful to form homogeneous rainfall regions and to validate the regions. Another important issue is that some of the attributes considered for regionalization vary dynamically with time. In conventional approaches, there is no provision to consider dynamic aspects of time varying attributes. This may lead to delineation of ineffective regions. To address this issue, a dynamic fuzzy clustering model (DFCM) is developed. The results obtained from application to Indian summer monsoon and annual rainfall indicated that RFA based on DFCM is more effective than that based on hard and fuzzy clustering models in arriving at rainfall quantile estimates. Errors in quantile estimates for the hard, fuzzy and dynamic fuzzy models based on the proposed approach are shown to be significantly less than those computed for Indian summer monsoon rainfall regions delineated in three previous studies. Overall, RFA based on DFCM and large scale atmospheric variables appeared promising. The performance of DFCM is followed by that of fuzzy and hard clustering models. Next, a new approach is proposed for RFA of meteorological droughts. It is suggested that homogeneous precipitation regions have to be delineated before proceeding to develop drought severity - areal extent - frequency (SAF) curves. Drought SAF curves are constructed at annual and summer monsoon time scales for each of the homogeneous rainfall regions that are newly delineated in India based on the proposed approach. They find use in assessing spatial characteristics and frequency of meteorological droughts. It overcomes shortcomings associated with classical approaches that construct SAF curves for political (e.g., state, country) and physiographic regions (e.g., river basin), based on spatial patterns of at-site values of drought indices in the study area, without testing homogeneity in rainfall. Advantage of the new approach can be noted especially in areas that have significant variations in temporal and spatial distribution of precipitation (possibly due to variations in topography, landscape and climate). The DFCM is extended to RFA of floods, and its effectiveness in prediction of flood quantiles is demonstrated by application to Godavari basin in India, considering precipitation as time varying attribute. Six new homogeneous regions are formed in Godavari basin and errors in quantile estimates based on those regions are shown to be significantly less than those computed based on sub-zones delineated in Godavari basin by Central Water Commission in a previous study.

碩士
國立臺灣師範大學
地理學系
101
The frequency analysis is often applied in disaster prevention planning, hydraulic works design, and hazard risk analysis. It is possible to estimate the maximum volume of intensive rainfall and peak discharge based on a suitable probability distribution. The frequency analysis is also helpful for people to understand the hydrological characteristics in a watershed, and to enhance the efficiency of watershed management. The Chingmei stream watershed is selected as a study area in this research. The extreme hydrological events are analyzed, including the annual maximum daily discharge and annual one-day maximum rainfall during the period from 1970 to 2009. Four probability distributions are compared, including extreme-value type I distribution, logarithmic normal distribution, Pearson type III distribution, and logarithmic Pearson type III distribution. The estimated annual maximum daily discharge in late stage (1987-2009) is higher than that in early stage (1970-1986). Their variation is from 9.45% to 54.59%. The average of annual maximum daily discharges in late stage is bigger surpassing up to 17.77%, and the standard deviation is also increasing up to 32.45%. The estimated one-day maximum rainfall in late stage is higher than that in early stage. Their variation is from 12.87% up to 56.34%. The average of one-day maximum rainfall in late stage is bigger surpassing up to 16.74%, and the standard deviation is also exceeding up to 65.19%.The other is that the amounts of runoff and rainfall become larger during the wet season and lower during the dry seasons. Discharge in the wet season variation is from 9.12% to 12.62%. The average of wet season discharge in late stage is bigger surpassing up to 8.34%, and the standard deviation is also increasing up to 35.50%. Besides, the discharge variation is from -8.55% to -14.01% in dry season. The average of discharge in the dry season in late stage decreases to 13.42%, and the standard deviation is also up to 10.52%.These results present that extreme events increase interannually, including floods and drought. In conclusion, there is an increasing trend for the annual maximum daily discharge and annual one-day maximum rainfall in the Chingmei stream watershed. The variation is enhancing and the frequency is strengthening. It reveals that the occurrence probability of extreme hydrological events is rising in the further. The Chingmei stream is an important river in the suburbs of Taipei city. As the settlement extended along the valley, flood plains were occupied and communities were close to channel. Weather pattern and surface runoff in Taiwan have been considerably affected by the change of global climate. Therefore, the integrated watershed management should focus on land-use planning in Changed steam watershed. This will help us response to the change of runoff and rainfall characteristics in change stream.

碩士
國立成功大學
測量及空間資訊學系碩博士班
98
Typhoons are the most serious weather system that strike Taiwan annually. There are about three or four typhoons that affect Taiwan every year and bring destructive winds and extreme rainfalls. They can seriously cause damages of agriculture, industry and human casualties. Historical records show that on the average, there are about 20 typhoons form in this area each year and among them three to four may invade Taiwan. Plum rains are the unique weather and climate phenomenon taking place annually only in eastern Asia including Taiwan region and coastal China because this region is located in one of distinct monsoon areas in the world. Plum rains season in Taiwan is from May to June every year. This study propose the procedures facilitate GPS network PPP derived ZWD for investigating the characteristics of extreme rainfall triggered by typhoons and plum rains, the temporal and spatial relationships between GPS network PPP derived ZWD and rainfall is essential. The cross-correlation analysis is applied to GPS-PPP estimated ZWD series and accumulated precipitation series collected at four sites during typhoon cases and plum rains to obtain time delay. The Wavelet Transform spectrum analysis is applied to obtain specific frequency information to identify the ZWD and rainfall disturbance; moreover, it reveals exactly when certain events take place. The results illustrates that there is about 2-7 hours time delay in Taiwan in typhoon cases and plum rains. The characteristics of rainfall could be detected by using the Wavelet Transform analysis; it could clearly catch the time information from rainfall records. The daily cycle of variation of ZWD also could be caught by using Wavelet Transform analysis. The well-distributed e-GPS network can be considered as supplemental meteorological sensors to monitor the characteristics of extreme rainfall triggered by weather events. With improved near real-time precise products provided by other institutions, a near real-time GPS network PPP based meteorological sensors can provide useful information for developing early warning system for climate events like typhoons, plum rains, and seasonal thunderstorm in the future.

碩士
淡江大學
水資源及環境工程學系碩士班
100
Under global climate change, the frequency of extreme hydrological events such as floods and droughts has increased, complicating frequency analyses. Reasonable estimates of return periods for extreme events cannot be obtained through the use of traditional L-moments method in frequency analyses. Instead, LH-moments method which assigns higher weights to data at extreme ends of the distribution should be applied for parameter estimations. In this research, the LH-moments method is applied in the frequency analysis of extreme rainfall events, in which rainfall data are fitted to 3-parameter generalized extreme value (GEV) distribution model. The weighing factor (m) for data at extreme ends of the distribution is raised in order to obtain better estimation of the return periods. The value of the shape parameter κ is used to determine the weighing factor m, so the most reasonable return period can be obtained. The value of the shape parameter κ would also serve as a reference for follow-up data analysis.

碩士
淡江大學
水資源及環境工程學系碩士班
101
In recent years, the influence of global climate change is more significant, such as the extreme rainfall events have occurred frequently. In general, the L-moments are adopted and all data are usually given the equal weighting in conventional approach of rainfall frequency analysis. However, the consequence problem is that the return periods are always estimated higher for those extreme rainfall (or higher tail) events of recently occurring. Wang (1997) first introduced the idea of LH-moments, increasing the weighting of high tail parts of Generalized Extreme Value (GEV) distribution were developed for frequency analysis of extreme rainfall event. Moreover, Yu et al. (2012) derived the general form for various weighting factor m of LH-moments of GEV and also real applied to estimating the return period of extreme rainfall in Taiwan. The purpose of this study is to explore an approach of LH-moments for Pearson Type III distribution (PT3). First of all, the synthetic data of various parameter sets are generated to evaluate the rationality of return period estimate of LH-moments for data at high tail part of PT3. Eventually, it is hopeful that this study can be further adopted to play a referential role on application of hydrologic design.

碩士
淡江大學
水資源及環境工程學系碩士班
95
The purpose of the study aims to estimate frequencies of annual maximum 1-day rainfall for ungauged sites in Taiwan using regionalization approach. The index flood method with parameters estimated by L-moments is used to establish the regional frequency model. Kriging is then employed to estimate the mean annual maximum 1-day rainfall of ungauged sites in order to analyze the rainfall magnitudes of various frequencies. Delineation of homogeneous regions is determined by cluster analysis in this study based on the coordinates of the rainfall gauge stations, the means and coefficient of variation of the annual maximum 1-day rainfall. The L-moment based discordancy, heterogeneity, and goodness-of-fit measures are then used to detect unusual sites and select the optimal regional probability models. In this study, a total of 77 rainfall gauge stations are used as the basis to estimate the frequencies of the annual maximum 1-day rainfall for ungauged sites. The number of homogeneous regions derived by cluster analysis is 3. The best regional probability model for one region is Pearson type Ⅲ distribution, and generalized Pareto distribution is the best model for the other two regions. Frequency analysis for ungauged sites needs to establish the variogram models of the mean and coefficient of variation of the annual maximum 1-day rainfall first. The obtained variogram models is then used to estimate the mean annual maximum 1-day rainfall for the ungauged sites. The ungauged sites belong to which homogeneous region depend on the minimum distance to the centroid of the homogeneous regions. Combined with the derived regional frequency model and estimated mean annual maximum 1-day rainfall, the computing procedures of frequency analysis for ungauged sites are identical with the procedures of gauged sites.

碩士
國立臺灣大學
生物環境系統工程學研究所
102
Extreme rainfall events occur increasingly and cause enormous loss; consequently, regional frequency analysis has become more important and widely used to estimate the return period of floods. However, the dependence among stations was not considered in the past. Studies have shown that the variation of rainfall patterns was affected by monsoon, especially during winter, in I-Lan area, i.e. the northeast corner of Taiwan. The most important factor that affects the precipitation in I-Lan is the local circulation caused by the triangle-shaped terrain. Therefore, without the influence of strong weather systems, e.g. typhoon, extreme rainfall events still occur. The purpose of this study is applying techniques of copula to analyze the multisite stochastic hourly rainfall patterns and regional frequency considering the dependence among surrounding rainfall stations during the period of 1960-2011. This model is following three steps to analyze the rainfall patterns and return periods. First, we use copulas to model the dependence among rainfall stations without the influence of marginal distributions, and then pair-copula structures are applied to separate the multivariate copula into several of bivariate copulas. Second, conditional probability density function is used to realize the major space-time pattern of local precipitation with different scenarios. Finally, copula-based regional frequency analysis is compared with the index flood methods with L-moments, and the return period simulation IV considering dependence among stations is also exhibited in this part. After constructing the dependent structure, the joint density function can be used to simulate the complicate regional rainfall patterns and regional return periods. In a specific scenario, the rainfall in downstream is more than in upstream when the extreme rainfall event occurs in midstream. Furthermore, copula-based return periods considering dependence are more accord with the real events than the index flood methods with L-moments. Considering dependent structure by copula can not only simulate the complex rainfall patterns but also reduce the possibility of underestimated or overestimated situation.

The scarcity of data poses a challenging obstacle for the study of natural disasters, especially in developing countries where the social vulnerability plays as important a role as the physical vulnerability.  The work presented in this thesis is oriented towards the demonstration of the usefulness of press archives as a data source for the temporal and spatial analysis of landslides in Tegucigalpa, Honduras for the period between 1980 and 2005.  In the last four decades, Tegucigalpa has been characterized by a disorganized urban growth that has significantly contributed to the destabilization of the city’s slopes.  In the first part of the thesis, a description of the database compilation procedure is provided.  The limitations of using data derived from press archives have also been addressed to indicate how these affect the subsequent landslide analyses.  In the second part, the temporal richness offered by press archives has allowed the establishment of rainfall thresholds for landslide occurrence.  Through the use of the critical rainfall intensity method, the analysis of rainfall thresholds for 7, 15, 30 and 60 antecedent days shows that the number of yielded false alarms increases with the threshold duration.  A new method based on the rainfall frequency contour lines was proposed to improve the distinction between days with and without landslides.  This method also offers the possibility to identify the landslides that may only occur with a major contribution of anthropogenic disturbances as well as those landslides induced by high-magnitude rainfall events.  In the third part, the matrix method has been employed to construct two landslide susceptibility maps: one based on the multi-temporal press-based landslide inventory and a second one based on the landslide inventory derived from an aerial photograph interpretation carried out in 2014.  Despite the low spatial accuracy provided by the press archives in locating the landslides, both maps exhibit 69% of consistency in the susceptibility classes and a good agreement in the areas with the highest propensity to landslides.  Finally, the integration of these studies with major actions required to improve the process of landslide data collection is proposed to prepare Tegucigalpa for future landslides.

碩士
國立臺灣海洋大學
河海工程學系
99
The purpose of this research is to assess the potential impact of climate change on hydrologic frequency of extreme events (drought and flood) in Taiwan. Provided by IPCC’S GCM A1B scenarios of climate model data in CGCM3(T47)and CNRM-CM3, The adjusted data by using the quadrant conversion method over Taiwan are analyzed based on the Log-Pearson type III distribution and kriging method to realize the maximum consecutive dry days and maximum 1-day, 2-day, and 3-day rainfall within 2080-2099, as compared with those within 1979-1998. For maximum 1-day to 3-day rainfall and cumulative dry days, the outcomes of CNRM-CM3(2080-2099) is higher than other models, and the outcome of CGCM3(2080-2099) is similar to the ensemble of future climate by CGCM3(T47)、CNRM-CM3、FGOALS-g1.0、GFDL-CM2.0 and CGCM2.3.2. Overall, all of GCMs’ outcomes are higher than the past value(1979-1998). This result appears the quantity and intensity of rainfall and dry might increase in the future.

碩士
國立中興大學
水土保持學系所
98
In these recent years, because of global warming influence, the climate became more anomalous and hydrology events became more extreme, it caused rainfall distribution in Taiwan area to be more unbalanced, and brought about an extremely severe disaster. In search of the most suitable ways for rainfall spatial distribution in Shei-Pa National Park, this research will take Shei-Pa National Park as the boundary, and use Spline , IDW(Inverse Distance Weighted), Kriging method to estimate the distribution of rainfall space, also compare the merits and demerits of these three methods, and find out the most suitable analysis method that used in this area and Hydrological observation station where is located at severe shortage area. This study will divide the rainfall into long time annual rainfall and short time daily cloudburst, and will be discussed separately, (1) for annual rainfall side, collect in the study area of annual rainfall in year 2000, and estimate its annual rainfall space distribution by using those three methods above, and also use geographical information system and traditional Thiessen Polygons method to calculate the average of annual rainfall volume, for comparing its results. (2) For cloudburst side, collect in the study area of the highest accumulated rainfall volume for 24, 48, 72 delayed rainfall volume, and also use the most extreme value of Gumbel type I distribution method and Log-Pearson Type III distribution method to analyze among 5, 10, 20, 50, 100 rainfall frequency for each year, and also take this rainfall volume as property value, and use those three methods above to estimate the distribution of cloudburst space. (3) Finally, using RMS to analyze annual rainfall and cloudburst space distribution result, and also find out the most suitable method that used in the distribution of rainfall space, and analyze DAD(Depth Area Duration) of this area and also K, n value of Hortan formula. The conclusions of this study are : (1). IDW(Inverse Distance Weighted) and Kriging method are better used in analyzing of annual rainfall space distribution, but the average of annual rainfall volume that analyzed by three methods are almost same, but it is more accurate than the results of analysis by Thiessen Polygons method. (2). Kriging method is better used in analyzing of cloudburst space distribution, its average relative error is only 7%, while by using those two other methods it will be 14%. (3). Although IDW(Inverse Distance Weighted) method is better than Spline method in annual rainfall space distribution, but the results of cloudburst space distribution are the worst, conform to Gotway and other people theory, only the stability of IDW(Inverse Distance Weighted) method is bad, and can be easily influenced by the factors. (4). The annual rainfall space distribution uses 11 sample size, while cloudburst space distribution used 14 sample size, the both sample sizes are different, and cloudburst space distribution relative error is the lowest(only 10%), we can know that if sample sizes are more, the results will be more accurate. (5). Kriging method result is the best after using RMS analysis method. There are two suggestions : (1). The average relative error is only 13.3% by using Kriging analysis method, while by using RMS analysis method, its residual is 76. Therefore, this study suggests using Kriging analysis method in annual and daily rainfall space distribution analysis. (2). When cloudburst is analyzed by using Kriging method, it can cause the boundary of estimate will be wider, thus cloudburst frequency analysis should use Log-Pearson Type III distribution method.

碩士
國立成功大學
土木工程學系碩博士班
100
The aim of this study is to investigate the influence of the strength of precipitation to the stability of slope land along highways those spreading in the watershed of river Da-Jia during typhoons Toraji, Mindulle and Morakot. By collecting the historical precipitation data in site, the completed rainfall events during those typhoons can be obtained and be adopted to calculate the accumulated rainfall(R) and rainfall intensity(I) of the watershed. Furthermore, the concept of rolling rainfall intensity is proposed to illustrate that accumulated rainfall and rainfall intensity are not only the factors that led to the damage of slope land along the highway, the effect of duration of the rainfall intensity has to be included. Furthermore, accumulated rainfall and rolling rainfall intensity are also used to establish the snake line that is the analysis model of rainfall hydrograph and can be expressed the variations of accumulated rainfall and rolling rainfall intensity with time. In addition, both physiographical conditions and the rainfall data in area where disasters were occurred were collected. The physiographical conditions can be classified as four factors which as elevation, degree of slope, direction of slope and geologic condition and with Log-Pearson Type Ⅲ Distribution, the rainfall data is used to calculate the recurrence interval and classified it according to the severity of the disasters in the past for frequency analysis. By combining the results of classification and analysis with the snake line, the critical rainfall envelope of the study area can be defined. The disaster event occurred on June 10, 2012 is verified with the critical rainfall envelope. It is shown that the critical rainfall envelope can be the basis for the disaster capacity of mountain highway slope.