scholarly journals Applicability of Lindley Distribution for Hydroelectric Dam Operations in the Dry Season

2020 ◽  
Vol 20 (6) ◽  
pp. 291-299
Author(s):  
Hongjoon Shin ◽  
Hyunjun Ahn ◽  
Changsam Jeong
Keyword(s):  
Frequency Analysis ◽  
Estimation Method ◽  
Low Flow ◽  
Distribution Model ◽  
Distribution Models ◽  
Recording Time ◽  
Lindley Distribution ◽  
Hydroelectric Dam ◽  
Flow Frequency ◽  
Dam Inflow

The long-term low-flow data are necessary for efficient planning of water resources and for estimating accurate quantiles via runoff data analysis at point. However, the short recording time period, low confidence, inconsistent distribution model, and parameter estimation method, make it difficult to estimate a proper low-flow quantile for each return period. In this study, the Lindley distribution model, which is a mix of the exponential and the gamma distribution models and has been verified as efficient by previous studies, was used to analyze the low-flow frequency using dam inflow data. We studied its applicability via comparison with statistics of observed data and other models already used for low-flow frequency analysis. For this, we carried out a performance analysis through a low-flow frequency analysis of inflow data from the hydroelectric dam and the reappearance capacity assessment of observed data at the Han river watershed. As a result, the hydrological applicability of the Lindley distribution model and its relative qualitative and quantitative excellence compared to the existing model were verified.

scholarly journals A Study on Low-flow Frequency Analysis Using Dam Inflow

2012 ◽  
Vol 32 (6B) ◽  
pp. 363-371 ◽  
Author(s):  
Younghun Jung ◽  
Woo Sung Nam ◽  
Hongjoon Shin ◽  
Jun-Haeng Heo
Keyword(s):  
Frequency Analysis ◽  
Low Flow ◽  
Flow Frequency ◽  
Dam Inflow

scholarly journals Multiple causes of nonstationarity in the Weihe annual low-flow series

2018 ◽  
Vol 22 (2) ◽  
pp. 1525-1542 ◽  
Author(s):  
Bin Xiong ◽  
Lihua Xiong ◽  
Jie Chen ◽  
Chong-Yu Xu ◽  
Lingqi Li
Keyword(s):  
Frequency Analysis ◽  
Driving Forces ◽  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Base Flow ◽  
Low Flow ◽  
Distribution Model ◽  
Flow Index ◽  
Explanatory Variables ◽  
Distribution Parameters

Abstract. Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into low-flow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, through a nonstationary frequency analysis framework with the generalized linear model (GLM) to consider time-varying distribution parameters, the multiple explanatory variables were incorporated to explain the variation in low-flow distribution parameters. These variables are comprised of the three indices of human activities (HAs; i.e., population, POP; irrigation area, IAR; and gross domestic product, GDP) and the eight measuring indices of the climate and catchment conditions (i.e., total precipitation P, mean frequency of precipitation events λ, temperature T, potential evapotranspiration (EP), climate aridity index AIEP, base-flow index (BFI), recession constant K and the recession-related aridity index AIK). This framework was applied to model the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China (also known as the Wei He River). The results from stepwise regression for the optimal explanatory variables show that the variables related to irrigation, recession, temperature and precipitation play an important role in modeling. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that the nonstationary distribution model with any one of all explanatory variables is better than the one without explanatory variables, the nonstationary gamma distribution model with four optimal variables is the best model and AIK is of the highest relative importance among these four variables, followed by IAR, BFI and AIEP. We conclude that the incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial to analyze future occurrences of low-flow extremes in similar areas.

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.

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