Multivariate frequency analysis of urban rainfall characteristics using three-dimensional copulas

2018 ◽  
Vol 2017 (1) ◽  
pp. 206-218 ◽  
Author(s):  
Chenglin Liu ◽  
Yuwen Zhou ◽  
Jun Sui ◽  
Chuanhao Wu
Keyword(s):  
Probability Distribution ◽  
Frequency Analysis ◽  
Three Dimensional ◽  
Rainfall Data ◽  
Rainfall Characteristics ◽  
Design Rainfall ◽  
Rainfall Depth ◽  
Multivariate Frequency Analysis ◽  
Continuous Rainfall

Abstract Urban runoff is a major cause of urban flooding and is difficult to monitor in the long term. In contrast, long term continuous rainfall data are generally available for any given region. As a result, it has become customary to use design rainfall depth as a proxy for runoff in urban hydrological analyses, with an assumption of the same frequency for runoff and rainfall. However, this approach has lack of overall coordination and cannot fully reflect the variability of rainfall characteristics. To address this issue, this study presents a three-dimensional copula-based multivariate frequency analysis of rainfall characteristics based on a long term (1961–2012) rainfall data from Guangzhou, China. Firstly, continuous rainfall data were divided into individual rainfall events using the rainfall intensity method. Then the characteristic variables of rainfall (design rainfall depth, DRD; total rainfall depth, TRD; peak rainfall depth, PRD) were sampled using the annual maximum method. Finally, a copula method was used to develop the multivariate joint probability distribution and the conditional probability distribution of rainfall characteristics. The results showed that the copula-based method is easy to implement and can better reflect urban rainstorm characteristics. It can serve a scientific reference for urban flood control and drainage planning.

scholarly journals Storm event-based frequency analysis method

2017 ◽  
Vol 49 (3) ◽  
pp. 700-710 ◽  
Author(s):  
Changhyun Jun ◽  
Xiaosheng Qin ◽  
Yeou-Koung Tung ◽  
Carlo De Michele
Keyword(s):  
Conventional Method ◽  
Frequency Analysis ◽  
Return Period ◽  
Rainfall Data ◽  
Storm Event ◽  
Analysis Method ◽  
Rainfall Characteristics ◽  
Study Results ◽  
Rainfall Depth ◽  
Event Based

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.

scholarly journals Joint return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation

2012 ◽  
Vol 9 (5) ◽  
pp. 6781-6828 ◽  
Author(s):  
S. Vandenberghe ◽  
M. J. van den Berg ◽  
B. Gräler ◽  
A. Petroselli ◽  
S. Grimaldi ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Three Dimensional ◽  
Distribution Functions ◽  
Return Periods ◽  
Design Variables ◽  
Joint Return ◽  
Design Values ◽  
Multivariate Frequency Analysis ◽  
Joint Return Period

Abstract. Most of the hydrological and hydraulic studies refer to the notion of a return period to quantify design variables. When dealing with multiple design variables, the well-known univariate statistical analysis is no longer satisfactory and several issues challenge the practitioner. How should one incorporate the dependence between variables? How should the joint return period be defined and applied? In this study, an overview of the state-of-the-art for defining joint return periods is given. The construction of multivariate distribution functions is done through the use of copulas, given their practicality in multivariate frequency analysis and their ability to model numerous types of dependence structures in a flexible way. A case study focusing on the selection of design hydrograph characteristics is presented and the design values of a three-dimensional phenomenon composed of peak discharge, volume and duration are derived. Joint return period methods based on regression analysis, bivariate conditional distributions, bivariate joint distributions, and Kendal distribution functions are investigated and compared highlighting theoretical and practical issues of multivariate frequency analysis. Also an ensemble-based method is introduced. For a given design return period, the method chosen clearly affects the calculated design event. Eventually, light is shed on the practical implications of a chosen method.

scholarly journals Frequency Analysis of Rainfall Data Using Probability Distribution Models

2019 ◽  
Vol 8 (06) ◽  
pp. 1390-1396 ◽  
Author(s):  
H. Baghel ◽  
H.K. Mittal ◽  
P.K. Singh ◽  
K.K. Yadav ◽  
S. Jain
Keyword(s):  
Probability Distribution ◽  
Frequency Analysis ◽  
Rainfall Data ◽  
Distribution Models

scholarly journals Regional Frequency Analysis of Rainfall Using L-Moment Method as A Design Rainfall Prediction

2020 ◽  
Vol 1000 (1000) ◽  
Author(s):  
Devita Mayasari
Keyword(s):  
Probability Distribution ◽  
Frequency Analysis ◽  
Moment Method ◽  
Regional Frequency Analysis ◽  
Test Model ◽  
Discharge Data ◽  
Maximum Rainfall ◽  
Generalized Logistic Distribution ◽  
Design Rainfall ◽  
The Moment

Frequency analysis is a method for predicting the probability of future hydrological events based on historical data. Frequency analysis of rain data and discharge data is generally carried out using the moment method, but the moment method has a large bias, variant, and slope so that it has the potential to produce inaccurate hydrological design magnitudes. The L-moment method is a linear combination of Probability Weighted Moment which processes data in a concise and linear manner. This research was conducted that L-moment method will obtain a regional probability distribution and design rainfall which can be used as a basis for calculating hydrological planning in anticipation of disasters. The location of the study in Mount Merapi area was chosen in order to more accurately predict the maximum rainfall that could cause cold lava in the area to reduce the risk of loss to the people living around Mount Merapi. The results showed that the entire rainfall stations homogeneous and no data was released. The L-moment regional ratio results τ2R  = 0.203, τ3R = 0.166, dan τ4R  = 0.169. The homogeneity and heterogeneity tests show that all rainfall stations are uniform or homogeneous. No data were released from the discordance test results. Growth factor value increases in each design rainfall return periods. The regional probability distribution that is suitable for the research area is Generalized Logistic distribution with design rainfall equation has been formulated. Test model showed the minimum RBias = 0.45%, maximum RBias = 41.583%, minimum RRSME = 0.45%, and maximum RRSME = 71.01%. The stability of L-moment method showed by model test minimum error = 1.64% and maximum error = 16.60%.

scholarly journals Cascade Rainfall Disaggregation Application in U.S. Central Plains

2017 ◽  
Vol 7 (4) ◽  
pp. 30 ◽  
Author(s):  
Jurgen D. Garbrecht ◽  
Rabi Gyawali ◽  
Robert W. Malone ◽  
John C. Zhang
Keyword(s):  
Time Series ◽  
Model Performance ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Rainfall Time Series ◽  
Random Component ◽  
Rainfall Characteristics ◽  
Hourly Rainfall ◽  
Replicated Observations

Long-term observations of daily rainfall are common and routinely available for a variety of hydrologic applications. In contrast, observations of 10 or more years of continuous hourly rainfall are rare. Yet, sub-daily rainfall data are required in rainfall-runoff models. Rainfall disaggregation can generate sub-daily time-series from available long term daily observations. Herein, the performance of Multiplicative Random Cascade (MRC) model at disaggregating daily-to-hourly rainfall was investigated. The MRC model was parameterized and validated with 15 years of continuous observed daily and hourly rainfall data at three weather stations in Oklahoma. Model performance, or degree to which the disaggregated rainfall time series replicated observations, was assessed using 46 variables of hourly rainfall characteristics, such as longest wet spell duration, average number of rainfall hours per year, and largest hourly rainfall. Findings include: a) average-type hourly rainfall characteristics were better replicated than single value characteristics such as longest, maximum, or peak hourly rainfall; b) the large number of sub-trace hourly rainfall values (<0.254 mm h-1) generated by the MRC model were not supported by observations; c) the random component of the MRC model led to a variation under 15% of the average value for most rainfall characteristics with the exceptions of the “longest wet spell duration” and “maximum hourly rainfall”; and d) the MRC model produced fewer persistent rainfall events compared to those in the observed rainfall record. The large number of generated trace rainfall values and difficulties to replicate reliably extreme rainfall characteristics, reduces the number of potential hydrologic applications that could take advantage of the MRC disaggregated hourly rainfall. Nevertheless, in most cases, the disaggregated rainfall generated by the MRC model replicated observed average-type rainfall characteristics well.

Practical electron tomography

1995 ◽  
Vol 53 ◽  
pp. 742-743
Author(s):  
C.L. Woodcock
Keyword(s):  
Electron Tomography ◽  
Tomographic Reconstruction ◽  
Three Dimensional ◽  
3D Shape ◽  
Computational Resources ◽  
Shape Of Particles

Despite the potential of the technique, electron tomography has yet to be widely used by biologists. This is in part related to the rather daunting list of equipment and expertise that are required. Thanks to continuing advances in theory and instrumentation, tomography is now more feasible for the non-specialist. One barrier that has essentially disappeared is the expense of computational resources. In view of this progress, it is time to give more attention to practical issues that need to be considered when embarking on a tomographic project. The following recommendations and comments are derived from experience gained during two long-term collaborative projects.Tomographic reconstruction results in a three dimensional description of an individual EM specimen, most commonly a section, and is therefore applicable to problems in which ultrastructural details within the thickness of the specimen are obscured in single micrographs. Information that can be recovered using tomography includes the 3D shape of particles, and the arrangement and dispostion of overlapping fibrous and membranous structures.

Custom Presurgical Planning for Midfacial Reconstruction

2020 ◽  
Vol 36 (06) ◽  
pp. 696-702
Author(s):  
Nolan B. Seim ◽  
Enver Ozer ◽  
Sasha Valentin ◽  
Amit Agrawal ◽  
Mead VanPutten ◽  
...  
Keyword(s):  
Multidisciplinary Approach ◽  
Functional Performance ◽  
Three Dimensional ◽  
Free Tissue Transfer ◽  
Long Term Effects ◽  
Presurgical Planning ◽  
Dental Rehabilitation ◽  
Midface Reconstruction ◽  
Reconstructive Algorithm

AbstractResection and reconstruction of midface involve complex ablative and reconstructive tools in head and oncology and maxillofacial prosthodontics. This region is extraordinarily important for long-term aesthetic and functional performance. From a reconstructive standpoint, this region has always been known to present challenges to a reconstructive surgeon due to the complex three-dimensional anatomy, the variable defects created, combination of the medical and dental functionalities, and the distance from reliable donor vessels for free tissue transfer. Another challenge one faces is the unique features of each individual resection defect as well as individual patient factors making each preoperative planning session and reconstruction unique. Understanding the long-term effects on speech, swallowing, and vision, one should routinely utilize a multidisciplinary approach to resection and reconstruction, including head and neck reconstructive surgeons, prosthodontists, speech language pathologists, oculoplastic surgeons, dentists, and/or craniofacial teams as indicated and with each practice pattern. With this in mind, we present our planning and reconstructive algorithm in midface reconstruction, including a dedicated focus on dental rehabilitation via custom presurgical planning.

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