Estimation of Short-Duration Rainfall Distribution Using Data Measured at Longer Time Scales

1994 ◽  
Vol 29 (1-2) ◽  
pp. 39-45 ◽  
Author(s):  
Van-Thanh Van Nguyen ◽  
Ganesh Raj Pandey
Keyword(s):  
Mathematical Model ◽  
Probability Distribution ◽  
Time Scales ◽  
Short Duration ◽  
Daily Rainfall ◽  
Regional Model ◽  
Rainfall Data ◽  
Rainfall Distribution ◽  
Proposed Model ◽  
Using Data

An investigation on how to estimate the distribution of short-duration (hours or shorter) rainfalls based on available daily rainfall measurements was undertaken. On the basis of the theory of multifractal multiplicative cascades, a scale-independent mathematical model was proposed to represent the probability distribution of rainfalls at various time scales. Using rainfall records from a network of seven recording gauges in the Montreal region in Quebec (Canada), it was found that the proposed model could provide adequate estimates of the distribution of hourly rainfalls at locations where these short-duration rainfall data are not available. Further, it has been observed that one single regional model can be developed to describe the scaling nature of rainfall distributions within the whole study area.

scholarly journals Probability Distribution of Philippine Daily Rainfall Data

2017 ◽  
Author(s):  
Vanessa Althea B. Bermudez ◽  
Ariel Bettina B. Abilgos ◽  
Diane Carmeliza N. Cuaresma ◽  
Jomar F. Rabajante
Keyword(s):  
Probability Distribution ◽  
Probability Distributions ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Economic Systems ◽  
Tropical Country ◽  
Data Set ◽  
Cumulative Rainfall ◽  
The Pacific ◽  
The Pacific Ocean

Philippines as an archipelago and tropical country, which is situated near the Pacific ocean, faces uncertain rainfall intensities. This makes environmental, agricultural and economic systems affected by precipitation difficult to manage. Time series analysis of Philippine rainfall pattern has been previously done, but there is no study investigating its probability distribution. Modeling the Philippine rainfall using probability distributions is essential, especially in managing risks and designing insurance products. Here, daily and cumulative rainfall data (January 1961 - August 2016) from 28 PAGASA weather stations are fitted to probability distributions. Moreover, the fitted distributions are examined for invariance under subsets of the rainfall data set. We observe that the Gamma distribution is a suitable fit for the daily up to the ten-day cumulative rainfall data. Our results can be used in agriculture, especially in forecasting claims in weather index-based insurance.

scholarly journals Using Mixed Probability Distribution Functions for Modelling Non-Zero Sub-Daily Rainfall in Australia

Geosciences ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 43
Author(s):  
Md Masud Hasan ◽  
Barry F. W. Croke ◽  
Shuangzhe Liu ◽  
Kunio Shimizu ◽  
Fazlul Karim
Keyword(s):  
Probability Distribution ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Mean Square ◽  
Weibull Distributions ◽  
Rainfall Events ◽  
High Rainfall

Probabilistic models for sub-daily rainfall predictions are important tools for understanding catchment hydrology and estimating essential rainfall inputs for agricultural and ecological studies. This research aimed at achieving theoretical probability distribution to non-zero, sub-daily rainfall using data from 1467 rain gauges across the Australian continent. A framework was developed for estimating rainfall data at ungauged locations using the fitted model parameters from neighbouring gauges. The Lognormal, Gamma and Weibull distributions, as well as their mixed distributions were fitted to non-zero six-minutes rainfall data. The root mean square error was used to evaluate the goodness of fit for each of these distributions. To generate data at ungauged locations, parameters of well-fit models were interpolated from the four closest neighbours using inverse weighting distance method. Results show that the Gamma and Weibull distributions underestimate and lognormal distributions overestimate the high rainfall events. In general, a mixed model of two distributions was found better compared to the results of an individual model. Among the five models studied, the mixed Gamma and Lognormal (G-L) distribution produced the minimum root mean square error. The G-L model produced the best match to observed data for high rainfall events (e.g., 90th, 95th, 99th, 99.9th and 99.99th percentiles).

scholarly journals Observation of Short Duration Rainfall in Yogyakarta

2019 ◽  
Vol 8 (11) ◽  
pp. 2741-2745
Keyword(s):  
High Resolution ◽  
Short Duration ◽  
Distribution Patterns ◽  
Rainfall Event ◽  
Rainfall Data ◽  
Observation Data ◽  
Rainfall Distribution ◽  
Rainfall Events ◽  
Hourly Rainfall ◽  
Mitigation Effort

On the observation of hourly rainfall data in Java Island, for the modelling watershed purpose, it can be seen that short duration rainfall events are the most dominant. The percentage of short duration rainfall event is almost 70% of the observation data. By using the high resolution of hourly rainfall data with 5 minutes’ intervals, it can be easily to describe the rainfall distribution patterns that occur. This research observed high resolution of hourly rainfall data in hilly and mountainous at Mount Merapi area in Yogyakarta. It purposed to mitigation effort due to the rainfall events that often falls with short duration and high intensity.

scholarly journals CORRELATION-REGRESSION ANALYSIS OF THE COMPETITIVENESS OF ENTERPRISE PRODUCTS

2020 ◽  
Vol 10 (86) ◽  
Author(s):  
Volodymyr Ulanchuk ◽  
◽  
Olena Zharun ◽  
Serhiy Sokolyuk ◽  
◽  
...  
Keyword(s):  
Mathematical Model ◽  
Regression Analysis ◽  
Correlation Equation ◽  
Regression Equation ◽  
Short Term ◽  
Flexible Tool ◽  
Proposed Model ◽  
Using Data ◽  
Short Term Forecasting ◽  
The Impact

The economic purpose of correlation-regression analysis is to determine the possible options for product competitiveness management, as well as an assessment of possible ways to achieve the desired result. The developed model can be used to improve planning and increase the level of product competitiveness. The forecast of results, though for the short term, gives the chance to learn about the prospects of obtaining the appropriate level of competitiveness of products in accordance with the degree of application of the impact on it. The forecast is dynamic and adapts to changes based on the latest data. The proposed model can be integrated into the existing decision support system to increase the competitiveness of products. In addition, correlation-regression analysis makes it possible to estimate the current situation using a regression equation. The mathematical reflection of the study of product competitiveness is the economic-mathematical model, which determines its functioning and assessment of changes in its effectiveness in the event of possible changes in the characteristics of economic activity. The parameters of economic models are estimated using the methods of mathematical statistics according to real statistical information. The task of correlation-regression analysis is to construct and analysis of the economic-mathematical model of the regression equation (correlation equation, which reflects the dependence of the resultant feature on several factor features and gives an estimate of the degree of connection density. Using data on the magnitude and direction of action of the analyzed factors, you can get the data that can be obtained to assess the relevant impact on the current level of product competitiveness. That is, such an analysis is a powerful and flexible tool for studying the relationships between product competitiveness indicators. The use of this method makes it possible to better understanding of the level of influence of factors on the competitiveness of products, and, accordingly, learn to manage the processes that take place, as well as more accurately predict their further interaction. These studies are important for the formation and implementation of management decisions to increase the competitiveness of products, because it narrows the choice of indicators with the greatest impact on its level. The ability to determine short-term forecasting of such impacts makes it possible to determine regional perspectives under the conditions of implemented measures.

scholarly journals Development of IDF-curves for tropical india by random cascade modeling

2013 ◽  
Vol 10 (4) ◽  
pp. 4709-4738 ◽  
Author(s):  
A. Rana ◽  
L. Bengtsson ◽  
J. Olsson ◽  
V. Jothiprakash
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Efficient Design ◽  
Daily Data ◽  
Current Design ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Fine Time

Abstract. Efficient design of urban drainage systems is based on statistical analysis of past rainfall events at fine time scales. However, fine time scale rainfall data are usually lacking in many parts of the world. A possible way forward is to develop methods to derive fine time scale rain intensities from daily observations. This paper applied cascade-based disaggregation modeling for generation of fine time scale rainfall data for Mumbai, India from daily rainfall data. These data were disaggregated to 10-min values. The model was used to disaggregate daily data for the period 1951–2004 and develop intensity-duration-frequency (IDF) relationships. This disaggregation technique is commonly used assuming scale-invariance using constant parameters. For the Mumbai rains it was found better to use parameters dependent on time scale and rain volume. Very good agreement between modeled and observed disaggregation series was found for the time scales larger than 1/2 h for the 1/2-yr period when short term data were available. Although the parameters were allowed to change with time scale, the rain intensities of duration shorter than 1/2 h were overestimated. When IDF-curves had been established, they showed that the current design standard for Mumbai city, 25 mm h−1, has a return period of less than one year. Thus, annual recurring flooding problems in Mumbai appear evident.

scholarly journals Daily rainfall disaggregation for Tocantins State, Brazil

2017 ◽  
Vol 12 (4) ◽  
pp. 605 ◽  
Author(s):  
Virgilio Lourenço da Silva Neto ◽  
Marcelo Ribeiro Viola ◽  
Demetrius David da Silva ◽  
Carlos Rogério de Mello ◽  
Silvio Bueno Pereira ◽  
...  
Keyword(s):  
Probability Distribution ◽  
Short Duration ◽  
Daily Rainfall ◽  
Hydraulic Structures ◽  
Return Periods ◽  
Intense Rainfall ◽  
Chi Square ◽  
Historical Series ◽  
Kolmogorov Smirnov ◽  
Comparison Of The Results

In order to design effective Brazilian hydraulic structures, it is necessary to obtain data relating to short-duration intense rainfall from historical series of daily rainfall. This recurring need can be fulfilled by rainfall disaggregation methodology. The objective of this study was to determine the intense rainfall disaggregation constants for the State of Tocantins and to compare these constants with those obtained for other regions of Brazil. For the modeling of the frequency of intense rainfall of different durations of less than 24 hours, the Gumbel probability distribution (GPD) was employed using rainfall series from 10 locations in Tocantins state. The results showed that the GPD was adequate by the Kolmogorov-Smirnov and Chi-square tests. The disaggregation constants presented low variability values for different return periods (from 10 to 100 years); the values for Tocantins state are: h12h/h24h=0.93, h6h/h24h=0.86, h4h/h24h=0.82, h3h/h24h=0.78, h2h/h24h=0.72, h1h/h24h=0.61, h50min/h1h=0.92, h40min/h1h=0.83, h30min/h1h=0.68, h20min/h30min=0.76 e h10min/h30min=0.46. The comparison of the results with those from studies developed for other Brazilian regions showed variations of up to -62.30%, allowing us to conclude that the use of local constants is important in the process of rainfall disaggregation.

scholarly journals Development of a new high spatial resolution (0.25° × 0.25°) long period (1901-2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region

MAUSAM ◽  
2021 ◽  
Vol 65 (1) ◽  
pp. 1-18 ◽  
Author(s):  
D.S Pai ◽  
M Rajeevan ◽  
O.P Sreejith ◽  
B. Mukhopadhyay ◽  
N.S Satbha
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Data Sets ◽  
Gridded Data ◽  
Rainfall Distribution ◽  
Data Set ◽  
The Western Ghats

ABSTRACT. The study discusses development of a new daily gridded rainfall data set (IMD4) at a high spatial resolution (0.25° × 0.25°, latitude × longitude) covering a longer period of 110 years (1901-2010) over the Indian main land.  A comparison of IMD4 with 4 other existing daily gridded rainfall data sets of different spatial resolutions and time periods has also been discussed. For preparing the new gridded data, daily rainfall records from 6955 rain gauge stations in India were used, highest  number of stations used by any studies so far for such a purpose. The gridded data set was developed after making quality control of basic rain-gauge stations. The comparison of IMD4 with other data sets suggested that the climatological and variability features of rainfall over India derived from IMD4 were comparable with the existing gridded daily rainfall data sets. In addition, the spatial rainfall distribution like heavy rainfall areas in the orographic regions of the west coast and over northeast, low rainfall in the lee ward side of the Western Ghats etc. were more realistic and better presented in IMD4 due to its higher spatial resolution and to the higher density of rainfall stations used for its development.

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