scholarly journals Frequency Analysis of Low Flows

1985 ◽  
Vol 16 (2) ◽  
pp. 105-128 ◽  
Author(s):  
G. V. Loganathan ◽  
C. Y. Kuo ◽  
T. C. McCormick
Keyword(s):  
Lower Bounds ◽  
Frequency Analysis ◽  
Probability Distributions ◽  
Flow Analysis ◽  
Extreme Value ◽  
Low Flow ◽  
Type Iii ◽  
Low Flows ◽  
Pearson Type

The transformations (i) SMEMAX (ii) Modified SMEMAX (iii) Power and Probability Distributions (iv) Weibull (α,β,γ) or Extreme value type III (v) Weibull (α,β,0) (vi) Log Pearson Type III (vii) Log Boughton are considered for the low flow analysis. Also, different parameter estimating procedures are considered. Both the Weibull and log Pearson can have positive lower bounds and thus their use in fitting low flow probabilities may not be physically justifiable. A new derivation generalizing the SMEMAX transformation is proposed. A new estimator for the log Boughton distribution is presented. It is found that the Boughton distribution with Cunnane's plotting position provides a good fit to low flows for Virginia streams.

scholarly journals Intercomparison of evaluation of low-flow characteristics of streams using statistical modelling approach

MAUSAM ◽  
2021 ◽  
Vol 57 (2) ◽  
pp. 291-300
Author(s):  
N. VIVEKANANDAN
Keyword(s):  
Stream Water ◽  
Probability Distributions ◽  
Flow Characteristics ◽  
Statistical Modelling ◽  
Low Flow ◽  
General Level ◽  
Stream Water Quality ◽  
Type Iii ◽  
Pearson Type ◽  
Modelling Approach

Lkkj & ty vkiwfrZ dh ;kstuk vkSj fMtkbu cukus] i;kZoj.kh; vkSj vkfFkZd nq"izHkkoksa dk fo’ys"k.k djus] ty/kkjk ds ikuh dh xq.krk dk ekWMqyu djus] ty/kkjk ds mi;ksxksa dks fu;fer djus rFkk izkÑfrd vkSj fu;fer ty/kkjk ra=ksa dh tkudkjh ds lkekU; Lrj esa lq/kkj ykus ds fy, ty/kkjk ds fuEu izokg y{k.kksa dk mi;ksx fd;k x;k gSA rhu fHkUu unh csfluksa uker% egkunh] xksnkojh vkSj ueZnk ds fofHkUu izR;kxeu dky ds fuEu izokg y{k.kksa dk irk yxkus ds fy, lkaf[;dh; ekWMqyu i)fr dk mi;ksx fd;k x;k gS ftlesa ckWDl&dkWDl :ikarj.k ds ekud laHkkO;rk forj.k] ykWx ukWeZy] ykWx ihvjlu Vkbi III vkSj ihvjlu Vkbi III rFkk ohcqy 'kkfey gSaA fofHkUu ty/kkjkvksa ds fuEu izokg y{k.kksa dh rqyuk djus ds fy, dkbZ oxZ ¼c2½ tk¡p dk mi;ksx  fd;k x;k gSA bl 'kks/k i= ds vuqlkj ykWx ukWeZy] ohcqy vkSj ihvjlu Vkbi III forj.k Øe’k% ueZnk]  egkunh vkSj xksnkojh unh ds fuEu izokg y{k.kksa ds fy, mfpr ik, x, gSaA blesa fuEu nkc vko`fr oØksa dk Hkh fodkl fd;k x;k gS vkSj mUgsa izLrqr fd;k x;k gSA Low-flow characteristics of streams are used in planning and design of water supplies, analysing environmental and economic impacts, modelling stream water quality, regulating instream uses, and improving the general level of understanding of natural and regulated stream systems.  Statistical modelling approach involving standard probability distributions of Box-Cox Transformation, Lognormal, Log Pearson Type III and Pearson Type III and Weibull are used to determine low-flow characteristics for different return periods for three different river basins, namely, Mahanadi, Godavari and Narmada.  Chi-square (c2) test is used for comparison of low-flow characteristics of different stream.  The paper presents that Lognormal, Weibull and Pearson Type III distributions are found to be suitable for determination of low-flow characteristics for rivers Narmada, Mahanadi and Godavari respectively.  Low-flow frequency curves are also developed and presented.

scholarly journals Comparison of Distribution Methods of Low Flow Analysis for Bandar Segamat, Johor

2015 ◽  
Vol 773-774 ◽  
pp. 1266-1270
Author(s):  
Yuliarahmadila Erfen ◽  
Mohd Shalahuddin Adnan ◽  
Noorfathiah Che Ali ◽  
Nurul Farehah Amat ◽  
Zawani Mohd Zahudi
Keyword(s):  
Stream Flow ◽  
Transition Period ◽  
Monsoon Season ◽  
Flow Analysis ◽  
Gumbel Distribution ◽  
Low Flow ◽  
Flow Data ◽  
Type Iii ◽  
Pearson Type ◽  
Pearson Type Iii Distribution

During the monsoon season, certain areas in Malaysia are experiencing a flood. While during the transition period Malaysia is experiencing a drought. This phenomenon could lead to severe disaster and precaution monitoring is needed to avoid this occurrences. Low flow during the dry season could lead to several negative effects on the river ecosystem. Thus, this study was conducted to determine the low flow frequency and intensity for the Segamat city. The duration for 2 years to 100 years based on the previous 20 years of stream flow data were used to calculated. Stream flow data were obtained from the Department of Irrigation and Drainage (DID). Two prominent distribution analyses methods known as Gumbel Distribution and Log pearson Type III Distribution were applied. The distribution results were validated using Root Mean Square Error (RMSE) and California method and Weibull method are selected. Based on the analyses results, it clearly shows that the distibution of low flow are between 1 m3/s to 10 m3/s. The flow are significantly correlate with the rainfall intensity. RMSE was selected based on the lowest value of 0.721 for the Gumble Distribution and 1.831 for Log Pearson Type III Distribution. Chi-square test shows a good agreement for Gumble Distribution (7.615<12.59) and Log Pearson Type III(5.201<11.07) using 5% significant level. The confident level form both tests are valid (p>0.05), thus, this results could be used for further analyses to alleviate the low flow in the study area.

scholarly journals A best-fit probability distribution for the estimation of rainfall in northern regions of Pakistan

2016 ◽  
Vol 11 (1) ◽  
pp. 432-440 ◽  
Author(s):  
M. T. Amin ◽  
M. Rizwan ◽  
A. A. Alazba
Keyword(s):  
Probability Distribution ◽  
Goodness Of Fit ◽  
Probability Distributions ◽  
Future Research ◽  
Maximum Rainfall ◽  
Type Iii ◽  
Goodness Of Fit Tests ◽  
Pearson Type ◽  
Northern Regions ◽  
Best Fit

AbstractThis study was designed to find the best-fit probability distribution of annual maximum rainfall based on a twenty-four-hour sample in the northern regions of Pakistan using four probability distributions: normal, log-normal, log-Pearson type-III and Gumbel max. Based on the scores of goodness of fit tests, the normal distribution was found to be the best-fit probability distribution at the Mardan rainfall gauging station. The log-Pearson type-III distribution was found to be the best-fit probability distribution at the rest of the rainfall gauging stations. The maximum values of expected rainfall were calculated using the best-fit probability distributions and can be used by design engineers in future research.

Low flow frequency analysis for stream with mixed populations

2015 ◽  
Vol 42 (8) ◽  
pp. 503-509 ◽  
Author(s):  
Mike Hulley ◽  
Colin Clarke ◽  
Ed Watt
Keyword(s):  
Frequency Analysis ◽  
Worked Examples ◽  
Low Flow ◽  
Flow Estimation ◽  
Low Flows ◽  
Record Length ◽  
Mixed Populations ◽  
Flow Frequency ◽  
Recommendations For Assessment

A methodology is developed for the estimation of annual low-flow quantiles for streams with annual low flows occurring in both the summer and winter. Since the low flow generating processes are different in summer and winter, independent seasonal analyses are required. The methodology provides recommendations for assessment of record length, randomness, homogeneity, independence and stationarity, as well as guidelines for distribution selection and fitting for seasonal distributions. The seasonal distributions are then used to develop the combined distribution for annual low flow estimation. Four worked examples of long-term Canadian hydrometric stations are provided.

scholarly journals Hujan rancangan berdasarkan analisis frekuensi regional dengan metode tl-moment

2017 ◽  
Vol 12 (1) ◽  
pp. 1-16
Author(s):  
Segel Ginting ◽  
William M Putuhena
Keyword(s):  
Frequency Analysis ◽  
Probability Distributions ◽  
Large Error ◽  
Extreme Value ◽  
Regional Frequency Analysis ◽  
Generalized Extreme Value ◽  
Generalized Pareto ◽  
Moment Ratio ◽  
Moments Method ◽  
Regional Frequency

The designstorm wereestimated by applying the regional frequency analysis provides benefits to a datasetwith limited amount of data has many advantages. Minimum data used in calculating the amount of design stromhas a very large error for higherreturn period. Therefore, the regional frequency analysis was used based on TL-moments method. There arethree types of probability distributions used in this study, namely the Generalized Extreme Value (GEV), Generalized Pareto (GPA) and the Generalized Logistic (GLO). Two of the three typesprobability distributions are the best choice by the TL-moment ratio diagrams which are Generalized Extreme Value, and Generalized Logistic. Ananother analysis wasconducted by the Z test and the Generalized Extreme Value (GEV) gives the best results. Therefore, the designs strom which was estimated based on the regional frequency analysis in Jakarta watersheds using the Generalized Extreme Value (GEV) has been determined.

scholarly journals Regional analysis of maximum rainfall using L-moment and LH-moment: A comparative case study for the northeast India

MAUSAM ◽  
2021 ◽  
Vol 68 (3) ◽  
pp. 451-462
Author(s):  
DHRUBA JYOTI BORA ◽  
MUNINDRA BORAH ◽  
ABHIJIT BHUYAN
Keyword(s):  
Frequency Analysis ◽  
Moment Method ◽  
Probability Distributions ◽  
Northeast India ◽  
Extreme Value ◽  
Generalized Extreme Value ◽  
Generalized Pareto ◽  
Rainfall Frequency ◽  
Best Fitting ◽  
Rainfall Frequency Analysis

Rainfall data of the northeast region of India has been considered for selecting best fit model for rainfall frequency analysis. The methods of L-moment has been employed for estimation of parameters five probability distributions, namely Generalized extreme value (GEV), Generalized Logistic(GLO), Pearson type 3 (PE3), 3 parameter Log normal (LN3) and Generalized Pareto (GPA) distributions. The methods of LH-moment of four orders (L1 L2, L3 & L4-moments) have also been used for estimating the parameters of three probability distributions namely Generalized extreme value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distributions. PE3 distribution has been selected as the best fitting distribution using L-moment, GPA distribution using L1-moment and GLO distribution using L2, L3 & L4-moments. Relative root mean square error (RRMSE) and RBIAS are employed to compare between the results found from L-moment and LH-moment analysis. It is found that GPA distribution designated by L1-moment method is the most suitable and the best fitting distribution for rainfall frequency analysis of the northeast India. Also the L1-moment method is significantly more efficient than L-moment and other orders of LH-moment for rainfall frequency analysis of the northeast India.

Flood Frequency Analysis of the Mahi Basin by Using Log Pearson Type III Probability Distribution

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Uttam Pawar ◽  
Pramodkumar Hire
Keyword(s):  
Probability Distribution ◽  
Frequency Analysis ◽  
Return Period ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Series Data ◽  
Period Range ◽  
Type Iii ◽  
Pearson Type ◽  
Data Points

Flood frequency analysis is one of the techniques of examination of peak stream flow frequency and magnitude in the field of flood hydrology, flood geomorphology and hydraulic engineering. In the present study, Log Pearson Type III (LP-III) probability distribution has applied for flood series data of four sites on the Mahi River namely Mataji, Paderdi Badi, Wanakbori and Khanpur and of three sites on its tributaries such as Anas at Chakaliya, Som at Rangeli and Jakham at Dhariawad. The annual maximum series data for the record length of 26-51 years have been used for the present study. The time series plots of the data indicate that two largest ever recorded floods were observed in the year 1973 and 2006 on the Mahi River. The estimated discharges of 100 year return period range between 3676 m3/s and 47632 m3/s. The return period of the largest ever recorded flood on the Mahi River at Wankbori (40663 m3/s) is 127-yr. The recurrence interval of mean annual discharges (Qm) is between 2.73-yr and 3.95-yr, whereas, the return period of large floods (Qlf) range from 6.24-yr to 9.33-yr. The magnitude-frequency analysis curves represent the reliable estimates of the high floods. The fitted lines are fairly close to the most of the data points. Therefore, it can be reliably and conveniently used to read the recurrence intervals for a given magnitude and vice versa.

A Method Based on Taking the Average of Probabilities to Compute the Flow Duration Curve

2000 ◽  
Vol 31 (3) ◽  
pp. 187-206 ◽  
Author(s):  
Hikmet Kerem Cigizoglu
Keyword(s):  
Probability Distributions ◽  
Maximum Flow ◽  
Exceedance Probability ◽  
Flow Duration Curve ◽  
Marginal Probability ◽  
Lognormal Distributions ◽  
Type Iii ◽  
Flow Duration ◽  
Pearson Type ◽  
Flow Duration Curves

In this study a method based on taking the average of the probabilities is presented to obtain flow duration curve. In this method the exceedance probability for each flow value is computed repeatedly for all time periods within a year. The final representing exceedance is just simply the average of all these probabilities. The applicability of the method to daily mean flows is tested assuming various marginal probability distributions like normal, Pearson type III, log-Pearson type III, 2-parameter lognormal and 3-parameter lognormal distributions. It is seen that the observed flow duration curves were quite well approximated by the 2-parameter lognormal average of probabilities curves. In that case the method requires the computation of the daily mean and standard deviation values of the observed flow data. The method curve enables extrapolation of the available data providing the exceedance probabilities for the flows higher than the observed maximum flow. The method is applied to the missing data and ungauged site problems and the results are quite satisfactory.

scholarly journals Theoretical derivation for the exceedance probability of corresponding flood volume of the equivalent frequency regional composition method in hydrology

2020 ◽  
Vol 51 (6) ◽  
pp. 1274-1292
Author(s):  
Yixin Huang ◽  
Zhongmin Liang ◽  
Yiming Hu ◽  
Binquan Li ◽  
Jun Wang
Keyword(s):  
Extreme Value ◽  
Low Flow ◽  
Exceedance Probability ◽  
Type I ◽  
Design Flood ◽  
Theoretical Derivation ◽  
Monte Carlo Experiments ◽  
Flood Volume ◽  
Pearson Type ◽  
The Relationship

Abstract The equivalent frequency regional composition (EFRC) method is an important and commonly used tool to determine the design flood regional composition at various sub-catchments in natural conditions. One of the cases in the EFRC method assumes that the exceedance probabilities of design flood volume at upstream and downstream sites are equal, and the corresponding flood volume at intermediate catchment equals the gap between the volumes of upstream and downstream floods. However, the relationship between the exceedance probability of upstream and downstream flood volumes P and that of corresponding intermediate flood volume C has not been clarified, and whether P&gt;C or P ≤ C has not been theoretically proven. In this study, based on the normal, extreme value type I and Logistic distributions, the relationship between C and P is deduced via theoretical derivations, and based on the Pearson type III, two-parameter lognormal and generalized extreme value distributions, the relationship between C and P is investigated using Monte Carlo experiments. The results show that C is larger than P in the context of the design flood, whereas P is larger than C in the context of low-flow runoff. Thus, the issue of exceedance probability corresponding flood is further theoretically clarified using the EFRC method.

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