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Journal articles on the topic "Rainfall frequency analysi"
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Jun, Changhyun, Xiaosheng Qin, Yeou-Koung Tung, and Carlo De Michele. "Storm event-based frequency analysis method." Hydrology Research 49, no. 3 (November 9, 2017): 700–710. http://dx.doi.org/10.2166/nh.2017.175.
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Abstract In this study, a storm event-based frequency analysis method was proposed to mitigate the limitations of conventional rainfall depth–duration–frequency (DDF) analysis. The proposed method takes the number, rainfall depth, and duration of rainstorm events into consideration and is advantageous in estimation of more realistic rainfall quantiles for a given return period. For the purpose of hydraulics design, the rainfall depth thresholds are incorporated to retrieve the rainstorm events for estimating design rainfalls. The proposed method was tested against the observed rainfall data from 1961 to 2010 at Seoul, Korea and the computed rainfall quantiles were compared with those estimated using the conventional frequency analysis method. The study results indicated that the conventional method was likely to overestimate the rainfall quantiles for short rainfall durations. It represented that the conventional method could reflect rainfall characteristics of actual rainstorm events if longer durations (like 24 hours) were considered for estimation of design rainfalls.
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Nguyen, V.-T.-V., T. D. Nguyen, and F. Ashkar. "Regional frequency analysis of extreme rainfalls." Water Science and Technology 45, no. 2 (January 1, 2002): 75–81. http://dx.doi.org/10.2166/wst.2002.0030.
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This study proposes two alternative methods for estimating the distribution of extreme rainfalls for sites where rainfall data are available (gaged sites) and for locations without data (ungaged sites). The first method deals with the estimation of short-duration rainfall extremes from available rainfall data for longer durations using the “scale-invariance” concept to account for the relationship between statistical properties of extreme rainfall processes for different time scales. The second method is concerned with the estimation of extreme rainfalls for ungaged sites. This method relies on a new definition of homogeneous sites. Results of the numerical application using data from a network of 10 recording rain gauges in Quebec (Canada) indicate that the proposed methods are able to provide extreme rainfall estimates that are comparable with those based on observed at-site rainfall data.
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Boardman, John, and David Favis-Mortlock. "Frequency-magnitude distributions for soil erosion, runoff and rainfall - a comparative analysis." Zeitschrift für Geomorphologie Supplement Volumes 115 (July 1, 1999): 51–70. http://dx.doi.org/10.1127/zfgsuppl/115/1999/51.
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Fontanazza, C. M., G. Freni, G. La Loggia, and V. Notaro. "Uncertainty evaluation of design rainfall for urban flood risk analysis." Water Science and Technology 63, no. 11 (June 1, 2011): 2641–50. http://dx.doi.org/10.2166/wst.2011.169.
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A reliable and long dataset describing urban flood locations, volumes and depths would be an ideal prerequisite for assessing flood frequency distributions. However, data are often piecemeal and long-term hydraulic modelling is often adopted to estimate floods from historical rainfall series. Long-term modelling approaches are time- and resource-consuming, and synthetically designed rainfalls are often used to estimate flood frequencies. The present paper aims to assess the uncertainty of such an approach and for suggesting improvements in the definition of synthetic rainfall data for flooding frequency analysis. According to this aim, a multivariate statistical analysis based on a copula method was applied to rainfall features (total depth, duration and maximum intensity) to generate synthetic rainfalls that are more consistent with historical events. The procedure was applied to a real case study, and the results were compared with those obtained by simulating other typical synthetic rainfall events linked to intensity–duration–frequency (IDF) curves. The copula-based multi-variate analysis is more robust and adapts well to experimental flood locations even if it is more complex and time-consuming. This study demonstrates that statistical correlations amongst rainfall frequency, duration, volume and peak intensity can partially explain the weak reliability of flood-frequency analyses based on synthetic rainfall events.
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MALEKINEZHAD, HOSSEIN, and ARASH ZARE-GARIZI. "Regional frequency analysis of daily rainfall extremes using L-moments approach." Atmósfera 27, no. 4 (January 13, 2015): 411–27. http://dx.doi.org/10.20937/atm.2014.27.04.07.
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Daily extreme precipitation values are among environmental events with the most disastrous consequences for human society. Information on the magnitudes and frequencies of extreme precipitations is essential for sustainable water resources management, planning for weather-related emergencies, and design of hydraulic structures. In the present study, regional frequency analysis of maximum daily rainfalls was investigated for Golestan province located in the northeastern Iran. This study aimed to find appropriate regional frequency distributions for maximum daily rainfalls and predict the return values of extreme rainfall events (design rainfall depths) for the future. L-moment regionalization procedures coupled with an index rainfall methodwere applied to maximum rainfall records of 47 stations across the study area. Due to complex geographicand hydro-climatological characteristics of the region, an important research issue focused on breaking downthe large area into homogeneous and coherent sub-regions. The study area was divided into five homogeneousregions, based on the cluster analysis of site characteristics and tests for the regional homogeneity.The goodness-of-fit results indicated that the best fitting distribution is different for individual homogeneousregions. The difference may be a result of the distinctive climatic and geographic conditions. The estimatedregional quantiles and their accuracy measures produced by Monte Carlo simulations demonstrate that theestimation uncertainty as measured by the RMSE values and 90% error bounds is relatively low when returnperiods are less than 100 years. But, for higher return periods, rainfall estimates should be treated withcaution. More station years, either from longer records or more stations in the regions, would be required forrainfall estimates above T=100 years. It was found from the analyses that, the index rainfall (at-site averagemaximum rainfall) can be estimated reasonably well as a function of mean annual precipitation in Golestanprovince. Index rainfalls combined with the regional growth curves, can be used to estimate design rainfallsat ungauged sites. Overall, it was found that cluster analysis together with the L-moments based regional frequencyanalysis technique could be applied successfully in deriving design rainfall estimates for northeasternIran. The approach utilized in this study and the findings are of great scientific and practical merit, particularlyfor the purpose of planning for weather-related emergencies and design of hydraulic engineering structures
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Lee, Chang-Hwan, Jae-Hyun Ahn, and Tae-Woong Kim. "Evaluation of Probability Rainfalls Estimated from Non-Stationary Rainfall Frequency Analysis." Journal of Korea Water Resources Association 43, no. 2 (February 28, 2010): 187–99. http://dx.doi.org/10.3741/jkwra.2010.43.2.187.
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Kim, Dong-IK, Dawei Han, and Taesam Lee. "Reanalysis Product-Based Nonstationary Frequency Analysis for Estimating Extreme Design Rainfall." Atmosphere 12, no. 2 (January 31, 2021): 191. http://dx.doi.org/10.3390/atmos12020191.
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Nonstationarity is one major issue in hydrological models, especially in design rainfall analysis. Design rainfalls are typically estimated by annual maximum rainfalls (AMRs) of observations below 50 years in many parts of the world, including South Korea. However, due to the lack of data, the time-dependent nature may not be sufficiently identified by this classic approach. Here, this study aims to explore design rainfall with nonstationary condition using century-long reanalysis products that help one to go back to the early 20th century. Despite its useful representation of the past climate, the reanalysis products via observational data assimilation schemes and models have never been tested in representing the nonstationary behavior in extreme rainfall events. We used daily precipitations of two century-long reanalysis datasets as the ERA-20c by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the 20th century reanalysis (20CR) by the National Oceanic and Atmospheric Administration (NOAA). The AMRs from 1900 to 2010 were derived from the grids over South Korea. The systematic errors were downgraded through quantile delta mapping (QDM), as well as conventional stationary quantile mapping (SQM). The evaluation result of the bias-corrected AMRs indicated the significant reduction of the errors. Furthermore, the AMRs present obvious increasing trends from 1900 to 2010. With the bias-corrected values, we carried out nonstationary frequency analysis based on the time-varying location parameters of generalized extreme value (GEV) distribution. Design rainfalls with certain return periods were estimated based on the expected number of exceedance (ENE) interpretation. Although there is a significant range of uncertainty, the design quantiles by the median parameters showed the significant relative difference, from −30.8% to 42.8% for QDM, compared with the quantiles by the multi-decadal observations. Even though the AMRs from the reanalysis products are challenged by various errors such as quantile mapping (QM) and systematic errors, the results from the current study imply that the proposed scheme with employing the reanalysis product might be beneficial to predict the future evolution of extreme precipitation and to estimate the design rainfall accordingly.
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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences 18, no. 10 (October 15, 2014): 4065–76. http://dx.doi.org/10.5194/hess-18-4065-2014.
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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when non-stationarity is present in extreme rainfall events. A methodology consisting of threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and non-stationarity analysis, and stationary and non-stationary generalised Pareto distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on intensity–frequency–duration (IFD) relationships. The methodology developed was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, 3 h and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.
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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences Discussions 11, no. 6 (June 16, 2014): 6311–42. http://dx.doi.org/10.5194/hessd-11-6311-2014.
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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when non-stationarity is present in extreme rainfall events. A methodology consisting of, threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and non-stationarity analysis, and stationary and non-stationary Generalized Pareto Distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on Intensity–Frequency–Duration (IFD) relationships. The developed methodology was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, and 3 and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.
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Shimizu, Keita, Tadashi Yamada, and Tomohito J. Yamada. "Uncertainty Evaluation in Hydrological Frequency Analysis Based on Confidence Interval and Prediction Interval." Water 12, no. 9 (September 12, 2020): 2554. http://dx.doi.org/10.3390/w12092554.
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The shortage of extreme rainfall data gives substantial uncertainty to design rainfalls and causes predictions for torrential rainfall to deviate strongly from adopted probability distributions used in river planning. These torrential rainfalls are treated as outliers which existing studies do not evaluate. However, probability limit method test which its acceptance region expresses with high accuracy the range where observed ith order statistics could realize. Confidence interval which quantifies uncertainty of adopted distributions can be constructed by assuming that these critical values in both sides of the adopted region follow the same function form applied to actual observed data. Furthermore, its validity is proved through comparison of confidence interval derived from ensemble downscaling calculations. In addition, these critical values are almost in accordance with outliers in samples from the ensemble downscaling calculations. Therefore, prediction interval which expresses the range that an unknown observed datum can take is constructed by extrapolating the critical values for limit estimation of a future datum. In this paper, quantification method of uncertainty of design rainfall and occurrence risk of outliers in the traditional framework, using the proposed confidence interval and prediction interval, is shown. Moreover, their application to future climate by using Bayesian statistics is explained.
Dissertations / Theses on the topic "Rainfall frequency analysi"
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MAZZOGLIO, PAOLA. "Geographically-based approaches to the statistical analysis of rainfall extremes." Doctoral thesis, Politecnico di Torino, 2022. https://hdl.handle.net/11583/2973799.
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Rudberg, Olov, and Daniel Bezaatpour. "Regional Rainfall Frequency Analysis." Thesis, Stockholms universitet, Statistiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-186813.
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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.
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Eckersten, Sofia. "Updating Rainfall Intensity-Duration-Frequency Curves in Sweden Accounting for the Observed Increase in Rainfall Extremes." Thesis, Uppsala universitet, Luft-, vatten och landskapslära, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-283714.
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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.
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Wadden, David. "Rainfall distribution in the City of St. John's : temporal distribution, spatial variation, frequency analysis, and Tropical Storm Gabrielle /." Internet access available to MUN users only, 2002. http://collections.mun.ca/u?/theses,49727.
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Tanaka, Tomohiro. "Extreme flood frequency analysis and flood risk curve development considering spatiotemporal rainfall variability." 京都大学 (Kyoto University), 2016. http://hdl.handle.net/2433/217150.
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Alias, Nor Eliza Binti. "IMPROVING EXTREME PRECIPITATION ESTIMATES CONSIDERING REGIONAL FREQUENCY ANALYSIS." 京都大学 (Kyoto University), 2014. http://hdl.handle.net/2433/192162.
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Miniussi, Arianna. "The metastatistical extreme value distribution for rainfall and flood frequency analysis with external drivers." Doctoral thesis, Università degli studi di Padova, 2021. http://hdl.handle.net/11577/3425928.
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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.
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LIBERTINO, ANDREA. "Advances in the space-time analysis of rainfall extremes." Doctoral thesis, Politecnico di Torino, 2017. http://hdl.handle.net/11583/2671346.
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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.
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Tagliaferri, Lorenza. "Probabilistic Envelope Curves for Extreme Rainfall Events - Curve Inviluppo Probabilistiche per Precipitazioni Estreme." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amslaurea.unibo.it/99/.
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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.
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Wi, Sungwook. "Impact of Climate Change on Hydroclimatic Variables." Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/265344.
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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.
Books on the topic "Rainfall frequency analysi"
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Geological Survey (U.S.), ed. Variation of warm-season rainfall frequency in the southern Colorado Plateau and its effect on runoff and alluvial-channel morphology: A preliminary analysis. [Denver, Colo.?]: Dept. of the Interior, U.S. Geological Survey, 1989.
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Hereford, Richard. Variation of warm-season rainfall frequency in the southern Colorado Plateau and its effect on runoff and alluvial-channel morphology: A preliminary analysis. [Denver, Colo.?]: Dept. of the Interior, U.S. Geological Survey, 1989.
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Geological Survey (U.S.), ed. Variation of warm-season rainfall frequency in the southern Colorado Plateau and its effect on runoff and alluvial-channel morphology: A preliminary analysis. [Denver, Colo.?]: Dept. of the Interior, U.S. Geological Survey, 1989.
Find full textBook chapters on the topic "Rainfall frequency analysi"
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Nguyen, Chi Cong, Phuoc Vo, Viet Long Doan, Quang Binh Nguyen, Tien Cuong Nguyen, and Quoc Dinh Nguyen. "Assessment of the Effects of Rainfall Frequency on Landslide Susceptibility Mapping Using AHP Method: A Case Study for a Mountainous Region in Central Vietnam." In Progress in Landslide Research and Technology, Volume 1 Issue 2, 2022, 87–98. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-18471-0_7.
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AbstractVietnam’s mountainous regions often encounter landslides, frequently resulting in fatalities, infrastructure damage, and landscape destruction. A landslide susceptibility map is an effective tool for mitigating disaster impacts on hazard-prone areas. This study investigates the applicability of the Analytic Hierarchy Process to produce a landslide susceptibility index. Eight major impact factors are analyzed using SAGA, a GIS-based toolkit, including slopes, aspect, land use, soil type, elevation, distance to road, distance to stream, and antecedent rainfall. Four landslide susceptibility maps are produced corresponding to frequency scenarios of 3-day antecedent rainfall data which is taken from Regional Frequency Analysis (RFA). We assess the modeling performances using Area Under the Curve (AUC) index and the results show that the AHP model has good performance. The findings demonstrate a significant influence of rainfall antecedent conditions on the susceptibility map of landslides in this study area.
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Canterford, R. P., N. R. Pescod, H. J. Pearce, L. H. Turner, and R. J. Atkinson. "Frequency Analysis of Australian Rainfall Data as used for Flood Analysis and Design." In Hydrologic Frequency Modeling, 293–302. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3953-0_20.
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Reed, Duncan W. "Rainfall frequency analysis for flood design." In Coping with Floods, 59–75. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1098-3_5.
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El Adlouni, Salaheddine, and Taha B. M. J. Ouarda. "Frequency analysis of extreme rainfall events." In Geophysical Monograph Series, 171–88. Washington, D. C.: American Geophysical Union, 2010. http://dx.doi.org/10.1029/2010gm000976.
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Saber, Mohamed, Sameh A. Kantoush, Mohammed Abdel-Fattah, Tetsuya Sumi, Jose Andres Moya, and Karim Abdrabo. "Flash Flood Modeling and Mitigation in Arid and Semiarid Basins: Case Studies from Oman and Brazil." In Natural Disaster Science and Mitigation Engineering: DPRI reports, 355–81. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2904-4_13.
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AbstractThe behaviors and impacts of flash floods (FF) are different based on the climatic regions. To understand such difference, two case studies were selected for the analysis: Wadi Uday, Oman and Sume Basin, Paraiba, Brazil. The rainfall-runoff inundation model (RRI) was used to simulate the discharge and flood inundation of the recent flood events to understand the severity and frequency of flash floods to better assess the current mitigation measures. The current FF situations in arid and semiarid basins were analyzed, and the hazards associated with flood phenomenon were assessed for various calculated rainfall return periods using RRI model. To this end, a flash flood index (average water depth per total basin area) was calculated as a basis to understand the impact of flash floods. A coupling of this index with the FF histories was included to provide a comprehensive overview of the FF vulnerability of arid and semiarid basins. We concluded that FFs tend to be more severe and extreme in arid regions than in semiarid regions, despite the lower frequency of FFs and the water scarcity in arid regions. Distributed dams also proved to be more effective in preventing FFs in arid regions than in semiarid regions.
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Quenum, Gandome Mayeul L. D., Nana A. B. Klutse, Eric A. Alamou, Emmanuel A. Lawin, and Philip G. Oguntunde. "Precipitation Variability in West Africa in the Context of Global Warming and Adaptation Recommendations." In African Handbook of Climate Change Adaptation, 1533–54. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_85.
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AbstractIt is commonly accepted that the Earth’s climate is changing and will continue to change in the future. Rising temperatures are one of the direct indicators of global climate change. To investigate how the rising global temperature will affect the spatial pattern of rainfall in West Africa, the precipitation and potential evapotranspiration variables from ten Global Climate Models (GCMs) under the RCP8.5 scenario were driven by the Rossby Centre regional atmospheric model (RCA4) from the COordinated Regional Climate Downscaling EXperiment (CORDEX) and analyzed at four specific global warming levels (GWLs) (i.e., 1.5 °C, 2.0 °C, 2.5 °C, and 3.0 °C) above the preindustrial level. This study utilized three indices, the precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP) over West Africa to explore the spatiotemporal variations in the characteristics of precipitation concentrations. Besides, the analysis of the effect of the specified GWLs on the Consecutive Dry Days (CDD), Consecutive Wet Days (CWD), and frequency of the intense rainfall events allowed to a better understanding of the spatial and temporal patterns of extreme precipitation in West Africa. Results reveal that, for the projections simulations and at each GWL, the rainfall onset starts one month earlier in the Gulf of Guinea in response to the control period. To encourage adaptation to the various changes in climate in general, and particularly in respect of rainfall, this study proposes several adaptation methods that can be implemented at the local (country) level, as well as some mitigation and adaptation strategies at the regional (West African) level.
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Tiwari, Binod, and Duc Tran. "Using Experimental Models to Calibrate Numerical Models for Slope Stability and Deformation Analysis." In Progress in Landslide Research and Technology, Volume 1 Issue 1, 2022, 185–95. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-16898-7_13.
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AbstractLandslides cause significant loss of lives and properties globally. Rainfall and earthquake are considered to be two frequent causes of landslides although there are dozens of natural or anthropogenic triggers of landslides. Experimental or numerical analyses by varying a single parameter—while keeping other triggers constant—help researchers/practitioners to understand the influence of each triggering factor on slope stability/landslides. However, experimental modeling of landslides in laboratory is exhaustive, time consuming, and expensive process. There are various experimental methods available for such modeling—ranging from centrifuge modeling to small scale 1 g models—depending on the need, available resources, and funds. With the wide availability of materials and development of better sensors/instruments, our capability to perform laboratory experiments, specifically for landslide modeling, has been much easier and accessible in recent decades. Such experiments are valuable to calibrate numerical models so that various analyses can be performed on the real-world problems. In this study, we prepared laboratory scale slopes in Plexiglas containers at varying densities and slope inclinations, and instrumented the slopes properly to measure real time suction, displacement, advancement of wetting front, and accelerations at various locations and depths within the model. The slopes were subjected to rainfall and/or earthquake shaking to evaluate the effect of rainfall and earthquakes—separately and combined—on slope stability. The experimental results were used to calibrate the numerical modeling effort so that a full spectrum of sensitivity analyses could be performed for a slope located in an expensive neighborhood of Southern California.
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Al-Amri, Nassir S., and Ali M. Subyani. "Analysis of Rainfall, Missing Data, Frequency and PMP in Al-Madinah Area, Western Saudi Arabia." In Regional Geology Reviews, 235–48. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21874-4_9.
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Snaibi, Wadii, and Abdelhamid Mezrhab. "Livestock Breeders’ Adaptation to Climate Variability and Change in Morocco’s Arid Rangelands." In African Handbook of Climate Change Adaptation, 1853–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_18.
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AbstractSince the mid-1970s, the high plateaus of eastern Morocco have experienced proven trends of climate change (CC) such as a significant decrease in rainfall amounts and an increase in the droughts’ frequency. Consequently, the CC threatens the sustainability of this pastoral ecosystem and negatively affects the breeding of small ruminants, the main local-level livelihood, which becomes more vulnerable due to its high dependence on climatic conditions. This chapter aims to analyze breeders’ adaptation practices by taking into account their social stratification based on the size of the sheep flock in possession. Data were analyzed using descriptive statistics, Kruskal-Wallis and Mann-Whitney tests to examine the differences in the adoption’ frequency of CC adaptation measures according breeders’ classes and Chi-square independence test to identify the factors explaining these observed differences. The analysis of local adaptation practices reveals that they are endogenous but above all curative, aiming at a short-term logic and have a low to medium relevance compared to the specific objective of adaptation to CC. In addition, there are significant differences in the frequency of adoption of CC adaptation strategies (chi-square value = 8.1112, p = 0.017, df = 2) within categories of breeders, in particular between small and larger breeders (U statistic = 58.000, p = 0.008). The significant factors explaining these differences are socioeconomic (age, household size, equipment, training, and membership of a basic professional organization). It is therefore recommended to target small breeders as a priority and to set up support measures (equipment, training, funding, organization of breeders).
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Saber, Mohamed, Sameh A. Kantoush, Tetsuya Sumi, Yusuke Ogiso, Tahani Alharrasi, Takahiro Koshiba, Mohammed Abdel-Fattah, et al. "Integrated Study of Flash Floods in Wadi Basins Considering Sedimentation and Climate Change: An International Collaboration Project." In Natural Disaster Science and Mitigation Engineering: DPRI reports, 401–22. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2904-4_15.
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AbstractRecently, Wadi flash floods (WFFs) have happened frequently in arid environments, resulting in great damage the society and the environment. In Oman, severe WFFs have occurred repeatedly within the last 10 years causing a huge impact on human lives and properties. This paper aims at introducing the framework of an international collaboration project between Japan and Oman for WFF management considering sediment dynamics and climate changes. Four research groups were established: climate change (G1), rainfall-runoff modeling (G2), sediment yield and transport (G3), and sedimentation and infiltration processes (G4). Several field investigations were conducted since 2017 until now. The detailed field survey to assess the deposited sediment in a dry reservoir by using sediment bars, and infiltration test, as well as drone survey were addressed. Some of the preliminary results and findings from the field investigation is discussed. The results show there is an adverse impact of sedimentation clogging on the infiltration process at the reservoirs. Based on the historical rainfall data analysis, there is a systematic increasing trend of the annual average precipitation with remarkable cycles over the MENA region and Oman. The knowledge obtained from this project is expected to be valuable to understanding sediment dynamics at Wadi basins.
Conference papers on the topic "Rainfall frequency analysi"
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BEILICCI, Erika Beata Maria, and Robert BEILICCI. "Influence of Rainfall Characteristics on Runoff in a Small Watershed." In Air and Water – Components of the Environment 2021 Conference Proceedings. Casa Cărţii de Ştiinţă, 2021. http://dx.doi.org/10.24193/awc2021_13.
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Due to climate change, extreme rainfall is more frequent, and the phenomenon of drought and desertification in some parts of the world is accentuated. Scientists forecast that these trends to continue as the planet continue to warm. An increasingly common phenomenon is the occurrence of flash floods in areas where human intervention on natural conditions has been significant. Over this intervention is superimposed the modification of the characteristics of extreme rainfalls (duration, intensity, height), resulting a series of negative consequences on the ecosystems of the watersheds. For their protection, a more accurate forecast of the size and times of occurrence of the maximum water flows and levels in different sections are needed. This forecast must be made with appropriate methods, such as the use of advanced hydroinformatic tools. This paper analyses the influence of rainfall characteristics on runoff in a small watershed, using rainfall-runoff phenomenon modelling. The modelling is realized using advanced hydroinformatic tool MIKE11, developed by Danish Hydraulic Institute (DHI).
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Pucci, Alessandro, Hélder S. Sousa, and José C. Matos. "Predicting the change of hydraulic loads on bridges: a case study in Italy with a 100-year database." In IABSE Congress, New York, New York 2019: The Evolving Metropolis. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2019. http://dx.doi.org/10.2749/newyork.2019.0442.
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<p>Planet Earth is naturally subject to climatic variability, but over the recent decades extreme deviations have been observed. Climate change, as a manmade-induced process, is mainly due to the increase of greenhouse gasses emission. Global warming consequences drive also to an intensification of hydrological cycles, leading to more frequent and severe precipitations. In parallel, several bridges have collapsed in the last years due to extreme rainfalls. Although the impacts of climate change on built environment do not always present a direct cause-effect relation, analysis on specific parameters (as rain volume) that are inputs in bridge design, can clarify some aspects of this interaction. In this paper, the peak discharge variation of different rivers located in the northwest of Italy, within the last 100 years, is analyzed. A cluster analysis was performed to understand if the hydraulic design loads should be considered with a different intensity if the bridge had been built with reference to an up-to-date database, or if in the last decades, when the majority of these structures were built. The rainfall data was analyzed through classical techniques, such as the frequency-based statistical method, but without the stationary time hypothesis. In this case, the extreme value theory was used for the estimation of intensity-duration curve parameters. By introducing a second-order analysis, where random variables can change over time, an increase-trend of rainfall height was found, and the peak discharge was determined accordingly. The relevant parameters on the case-study area were preliminarily obtained through geographic information systems. The results evidenced that nowadays-floods parameters are significantly different from those of the past, and this behavior is escalated when high return period values are assumed. Furthermore, although hydraulic design loads are increasing, many existing bridges are not properly maintained, leading to an increased number of collapses.</p>
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Purwaningsih, Tuti, Dian Kusumaningrum, and Yuniarti Eka Putri Miladi. "Rainfall frequency analysis in Indonesia using spatial approach." In 3RD INTERNATIONAL CONFERENCE ON CHEMISTRY, CHEMICAL PROCESS AND ENGINEERING (IC3PE). AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0063127.
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Armstrong, Rachel, and Robert F. Carlson. "Analysis of Rainfall Frequency Data for Fairbanks Alaska." In 11th International Conference on Cold Regions Engineering. Reston, VA: American Society of Civil Engineers, 2002. http://dx.doi.org/10.1061/40621(254)72.
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Nam, Woo-Sung, Hong-Joon Shin, Jun-Haeng Heo, and Kyung-Duk Kim. "Regional Rainfall Frequency Analysis Based on Generalized Logistic Model." In World Water and Environmental Resources Congress 2005. Reston, VA: American Society of Civil Engineers, 2005. http://dx.doi.org/10.1061/40792(173)488.
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Perera, Helani, Miyuru Gunathilake, and Upaka Rathnayake. "Satellite Rainfall Products for analysis of Rainfall trends for Mahaweli River Basin." In The SLIIT International Conference on Engineering and Technology 2022. Faculty of Engineering, SLIIT, 2022. http://dx.doi.org/10.54389/zzug8067.
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The presence of accurate and spatiotemporal data is of utmost importance in hydrological studies for river basins. However, limited ground-measured rainfall data restrict the accuracy of these analyses. Data scarcities can often be seen not only in many developing countries but also in the developed world. Therefore, much attention is given to alternative techniques to accomplish the data requirement. Precipitation data extraction from satellite precipitation products is one of the frequently used techniques in the absence of ground-measured rainfall data. The Mahaweli River Basin (MRB) is the largest river basin in Sri Lanka and it covers 1/6th of the total land area of the country. Mahaweli River is the heart of the country and the water of it is being used for many activities, including hydropower development, water supply, irrigation, etc. Therefore, analyzing rainfall trends of MRB is interesting and worthwhile for many stakeholders of the river basin. Therefore, this research investigates the suitability of Satellite Rainfall Products (SRP’s) as an alternative for Rain Gauge measured data in the MRB by performing trend analysis between the two datasets. Six precipitation products, namely PERSIANN, PERSIANNCCS, PERSIANN-CDR, GPM IMERG V06, TRMM-3B42 V7, TRMM-3B42RT V7 were extracted for 10-35 years for 14 locations of the MRB spatially distributed in the three climatic zones of the catchment. Non-parametric tests, including the Mann-Kendall test and Sen’s slope estimator tests, were used to detect the possible rainfall trends in precipitation products. Significant increasing trends were observed for both ground-measured and SRP’s in the annual scale while mixed results were observed in monthly and seasonal scales. The trends from ground-measured rainfall and SRP’s were compared and the suitability of SRP’s as an alternative technique was stated. KEYWORDS: ground-measured rainfall data, Mahaweli River Basin, rainfall trends, satellite precipitation products, PERSIANN, IMERG, TRMM
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Yamano, Hidemasa, Hiroyuki Nishino, and Kenichi Kurisaka. "Development of Probabilistic Risk Assessment Methodology of Decay Heat Removal Function Against Combination Hazards of Strong Wind and Rainfall for Sodium-Cooled Fast Reactors." In 2017 25th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/icone25-66059.
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This paper describes probabilistic risk assessment (PRA) methodology development against combination hazard of strong wind and rainfall. In this combination hazard PRA, a hazard curve has been evaluated in terms of maximum instantaneous wind speed, hourly rainfall, and rainfall duration. A scenario analysis provided event sequences resulted from the combination hazard of strong wind and rainfall. The event sequence was characterized by the function loss of auxiliary cooling system, of which heat transfer tubes could crack due to cycle fatigue by cyclic contact of rain droplets. This situation could occur if rain droplets ingress into air cooler occurs after the air cooler roof failure due to strong-wind-generated missile impact. This event sequence was incorporated into an event tree which addressed component failure by the combination hazard. Finally, a core damage frequency has been estimated the order of 10−7/year in total by multiplying discrete hazard frequencies by conditional decay heat removal failure probabilities. A dominant sequence is the failure of the auxiliary cooling system by the missile impact after the failure of external fuel tank by the missile impact. A dominant hazard is the maximum instantaneous wind speed of 40–60 m/s, the hourly rainfall of 20–40 mm/h, and the rainfall duration of 0–10 h.
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Kwon, Young-Moon, Jeong-Woo Han, and Tae-Woong Kim. "Application of Bivariate Frequency Analysis for Estimating Design Rainfalls." In World Environmental and Water Resources Congress 2008. Reston, VA: American Society of Civil Engineers, 2008. http://dx.doi.org/10.1061/40976(316)616.
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Wong, Man, and Yeou-Koung Tung. "Regional Frequency Analysis of Extreme Rainfalls in Hong Kong." In World Environmental and Water Resources Congress 2013. Reston, VA: American Society of Civil Engineers, 2013. http://dx.doi.org/10.1061/9780784412947.324.
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Pathak, Chandra S. "Frequency Analysis of Short Duration Rainfall for Central and South Florida." In World Water and Environmental Resources Congress 2001. Reston, VA: American Society of Civil Engineers, 2001. http://dx.doi.org/10.1061/40569(2001)227.
Full textReports on the topic "Rainfall frequency analysi"
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Wagner, Anna, Christopher Hiemstra, Glen Liston, Katrina Bennett, Dan Cooley, and Arthur Gelvin. Changes in climate and its effect on timing of snowmelt and intensity-duration-frequency curves. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41402.
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Snow is a critical water resource for much of the U.S. and failure to account for changes in climate could deleteriously impact military assets. In this study, we produced historical and future snow trends through modeling at three military sites (in Washington, Colorado, and North Dakota) and the Western U.S. For selected rivers, we performed seasonal trend analysis of discharge extremes. We calculated flood frequency curves and estimated the probability of occurrence of future annual maximum daily rainfall depths. Additionally, we generated intensity-duration-frequency curves (IDF) to find rainfall intensities at several return levels. Generally, our results showed a decreasing trend in historical and future snow duration, rain-on-snow events, and snowmelt runoff. This decreasing trend in snowpack could reduce water resources. A statistically significant increase in maximum streamflow for most rivers at the Washington and North Dakota sites occurred for several months of the year. In Colorado, only a few months indicated such an increase. Future IDF curves for Colorado and North Dakota indicated a slight increase in rainfall intensity whereas the Washington site had about a twofold increase. This increase in rainfall intensity could result in major flood events, demonstrating the importance of accounting for climate changes in infrastructure planning.
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Pradeep Kumar, Kaavya. Reporting in a Warming World: A Media Review. Indian Institute for Human Settlements, 2021. http://dx.doi.org/10.24943/rwwmr08.2021.
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The media plays a critical role in terms of shaping public perceptions, but they have a task on their hands in terms of effectively communicating a subject as vast and complex as climate change. India is among the countries most affected and yet reporting on the subject has been episodic, with peaks around the time of climate summits and in the immediate aftermath of disasters such as cyclones, heatwaves and extreme rainfall events. Through a media review, undertaken as part of the Earth Journalism Network Asia-Pacific Media Grant, we sought to understand patterns of representation in news coverage about urban drought and extreme weather events – predicted to occur more frequently and intensely in a warming world. This report details the methodology we followed, our findings and analyses them in the context of other work done as part of the evolving field of climate change communication.
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Hudgens, Bian, Jene Michaud, Megan Ross, Pamela Scheffler, Anne Brasher, Megan Donahue, Alan Friedlander, et al. Natural resource condition assessment: Puʻuhonua o Hōnaunau National Historical Park. National Park Service, September 2022. http://dx.doi.org/10.36967/2293943.
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Natural Resource Condition Assessments (NRCAs) evaluate current conditions of natural resources and resource indicators in national park units (parks). NRCAs are meant to complement—not replace—traditional issue- and threat-based resource assessments. NRCAs employ a multi-disciplinary, hierarchical framework within which reference conditions for natural resource indicators are developed for comparison against current conditions. NRCAs do not set management targets for study indicators, and reference conditions are not necessarily ideal or target conditions. The goal of a NRCA is to deliver science-based information that will assist park managers in their efforts to describe and quantify a park’s desired resource conditions and management targets, and inform management practices related to natural resource stewardship. The resources and indicators emphasized in a given NRCA depend on the park’s resource setting, status of resource stewardship planning and science in identifying high-priority indicators, and availability of data and expertise to assess current conditions for a variety of potential study resources and indicators. Puʻuhonua o Hōnaunau National Historical Park (hereafter Puʻuhonua o Hōnaunau NHP) encompasses 1.7 km2 (0.7 mi2) at the base of the Mauna Loa Volcano on the Kona coast of the island of Hawaiʻi. The Kona coast of Hawaiʻi Island is characterized by calm winds that increase in the late morning to evening hours, especially in the summer when there is also a high frequency of late afternoon or early evening showers. The climate is mild, with mean high temperature of 26.2° C (79.2° F) and a mean low temperature of 16.6° C (61.9° F) and receiving on average 66 cm (26 in) of rainfall per year. The Kona coast is the only region in Hawaiʻi where more precipitation falls in the summer than in the winter. There is limited surface water runoff or stream development at Puʻuhonua o Hōnaunau NHP due to the relatively recent lava flows (less than 1,500 years old) overlaying much of the park. Kiʻilae Stream is the only watercourse within the park. Kiʻilae Stream is ephemeral, with occasional flows and a poorly characterized channel within the park. A stream gauge was located uphill from the park, but no measurements have been taken since 1982. Floods in Kiʻilae Stream do occur, resulting in transport of fluvial sediment to the ocean, but there are no data documenting this phenomenon. There are a small number of naturally occurring anchialine pools occupying cracks and small depressions in the lava flows, including the Royal Fishponds; an anchialine pool modified for the purpose of holding fish. Although the park’s legal boundaries end at the high tide mark, the sense of place, story, and visitor experience would be completely different without the marine waters adjacent to the park. Six resource elements were chosen for evaluation: air and night sky, water-related processes, terrestrial vegetation, vertebrates, anchialine pools, and marine resources. Resource conditions were determined through reviewing existing literature, meta-analysis, and where appropriate, analysis of unpublished short- and long-term datasets. However, in a number of cases, data were unavailable or insufficient to either establish a quantitative reference condition or conduct a formal statistical comparison of the status of a resource within the park to a quantitative reference condition. In those cases, data gaps are noted, and comparisons were made based on qualitative descriptions. Overall, the condition of natural resources within Puʻuhonua o Hōnaunau NHP reflects the surrounding landscape. The coastal lands immediately surrounding Puʻuhonua o Hōnaunau NHP are zoned for conservation, while adjacent lands away from the coast are agricultural. The condition of most natural resources at Puʻuhonua o Hōnaunau NHP reflect the overall condition of ecological communities on the west Hawai‘i coast. Although little of the park’s vegetation...