scholarly journals The Low Flow Assessment of Padma River in Bangladesh

2021 ◽  
pp. 11-20
Author(s):  
Md. Abu Sayed ◽  
Aysha Akter
Keyword(s):  
Frequency Analysis ◽  
Water Surface ◽  
Flow Simulation ◽  
Low Flow ◽  
Coefficient Of Determination ◽  
Field Observations ◽  
Distribution Method ◽  
Minimum Flow ◽  
Pearson Type ◽  
Padma River

Low flow or Environmental Flow (EF) assessment is vital to ensure the river and ecosystem remain healthy. Both natural and human interventions might alter a river. Therefore, this study presents EF requirements of the famous Hilsa breeding center in the Padma River, Bangladesh, by applying the Hydrologic Engineering Centers River Analysis System (HEC-RAS) for discharge and water surface levels simulations at different stations. The frequency analysis of 20 years of historical data, spanning 2000-2019, used the Log-Pearson Type III (LP-III) distribution method, while the one-dimensional unsteady flow simulation was performed for the last 10 years (i.e., 2012-2019). Subsequently, the HEC-RAS simulated water level values reasonably correlated with the field observations at four stations, namely Baruria Transit, Mawa, Tarpasha, Sureswar, with Coefficient of determination R2=0.86, 0.83, 0.92, and 0.74, alongside simulated minimum water surface levels of 1.57 m, 0.37 m, 0.30 m, and 0.27 m, respectively. Also, the Baruria Transit and Mawa had simulated flows that reasonably correlated with the field observations at R2=0.70 and 0.61, with a simulated minimum flow of 3849.51 m3/s and 3789.14 m3/s, respectively. The minimum flow according to the frequency analysis was 4017 m3/s, 3685 m3/s, 3449 m3/s, 3229 m3/s, and 3113 m3/s at Baruria Transit and 3304 m3/s, 2781 m3/s, 2438 m3/s, 2141 m3/s, 1992 m3/s at Mawa station in 5, 10, 20, 50 and 100 years return periods, respectively. This study overlooked to report the ongoing investigations into the water quality issues. Thus, this study is expected to guide the required EF quantity towards a healthy Hilsha fish habitat and surface water source for drinking purposes in this studied river. The stated method is also applicable to other similar rivers around the world.

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.

Regional low flow analysis in Sefidrood Drainage Basin, Iran using principal component regression

2014 ◽  
Vol 46 (1) ◽  
pp. 121-135 ◽  
Author(s):  
Kazem Nosrati ◽  
Gregor Laaha ◽  
Seyed Ali Sharifnia ◽  
Mojtaba Rahimi
Keyword(s):  
Catchment Area ◽  
Drainage Basin ◽  
Distribution Functions ◽  
Low Flow ◽  
Coefficient Of Determination ◽  
Flow Index ◽  
Size Factor ◽  
Regression Equations ◽  
Data Set ◽  
Pearson Type

Knowledge of low streamflow statistics is necessary for effective water management in regions prone to extreme hydrologic events such as Iran. This study employs a data set of 23 river flow time series from Sefidrood Drainage Basin, Iran, to examine regional hydrological drought based on the low flow index 7Q10. Hierarchical agglomerative cluster analysis was used to divide the 23 gauging stations into two homogeneous drought regions based on the similarity of the binary drought series. 7Q10 was determined using log-Pearson type-III and 2-parameter log-normal distributions selected as the best regional probability distribution functions in homogeneous drought region 1 and 2, respectively. The 7Q10 was related to principal components of catchment characteristics in each homogeneous drought region separately using backward stepwise regression. The resulting regression equations exhibit a coefficient of determination of 69 and 89%, respectively. The regression parameters are linked to a size factor related to catchment area, an elevation factor which is independent of catchment area, and geological formation variables, which can therefore be interpreted as important controls of low flow generation processes in the study area. The equations developed here are expected to provide robust estimates of 7Q10 values for watersheds in areas of similar geomorphology, geology and climate.

scholarly journals Application of Frequency Analysis on Peak River Discharge toward the Cumulative Floatable Litter Load at Log Boom Sungai Batu

2019 ◽  
Vol 266 ◽  
pp. 02002
Author(s):  
Nur Khaliesah Abdul Malik ◽  
Nor Rohaizah Jamil ◽  
Latifah Abd Manaf ◽  
Mohd Hafiz Rosli ◽  
Zulfa Hanan Ash’aari ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
River Discharge ◽  
Linear Regression Analysis ◽  
Gumbel Distribution ◽  
Environmental Issues ◽  
Decision Making Process ◽  
Rapid Urbanization ◽  
Distribution Method ◽  
Period 2

The accumulation of floatable litter in the river is mainly influenced by the increasing number of human population, rapid urbanization and development which indirectly lead to the changes of hydrological processes in river discharge, decreasing the water quality and aesthetical value of the river. The main objective of this paper is to determine the cumulative floatable litter load captured at the log boom during the extreme events by using the Gumbel distribution method for frequency analysis in river discharge of Sungai Batu. The annual maximum river discharge for a period of 35 years (1982 to 2016) was used in Gumbel distribution method to obtain the discharge for different return period (2, 5, 10, 25, 50, 100, and 200). The result shows that the estimated discharge (103.17 m³/s) can estimate the cumulative floatable litter load (53267.27 kg/day) at 50 years return period. The R2 value obtained from non – linear regression analysis is 0.9986 indicate that Gumbel distribution is suitable to predict the expected discharge of the river. This study is very crucial for the related agencies in highlighting this environmental issues for their future references which can be used as a guidelines during the decision making process in making better improvement.

scholarly journals Regional flood frequency analysis of Tripura based on L-moment

2012 ◽  
Vol 4 (1) ◽  
pp. 36-41 ◽  
Author(s):  
Abhijit Bhuyan ◽  
Munindra Borah
Keyword(s):  
Frequency Analysis ◽  
Regional Growth ◽  
Growth Curves ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Ungauged Catchments ◽  
Discharge Data ◽  
Pearson Type ◽  
Regional Flood Frequency Analysis ◽  
Regional Flood Frequency

The annual maximum discharge data of six gauging sites have been considered for L-moment based regional flood frequency analysis of Tripura, India. Homogeneity of the region has been tested based on heterogeneity measure (H) using method of L-moment. Based on heterogeneity measure it has been observed that the region consist of six gauging sites is homogeneous. Different probability distributions viz. Generalized extreme value (GEV), Generalized Logistic (GLO), Generalized Pareto (GPA), Generalized Normal (GNO), Pearson Type III (PE3) and Wakebay (WAK) have been considered for this investigation. PE3, GNO and GEV have been identified as the candidate distributions based on the L-moment ratio diagram and ZDIST -statistics criteria. Regional growth curves for three candidate distributions have been developed for gauged and ungauged catchments. Monte Carlo simulations technique has also been used to estimate accuracy of the estimated regional growth curves and quantiles. From simulation study it has been observed that PE3 distribution is the robust one.

scholarly journals Morphodynamic simulation of sediment deposition patterns on a recently stripped bedrock anastomosed channel

2018 ◽  
Vol 377 ◽  
pp. 51-56 ◽  
Author(s):  
David Milan ◽  
George Heritage ◽  
Neil Entwistle ◽  
Stephen Tooth
Keyword(s):  
National Park ◽  
Sediment Deposition ◽  
Low Flow ◽  
Field Observations ◽  
Deposition Patterns ◽  
High Magnitude ◽  
Vegetation Establishment ◽  
Olifants River ◽  
Flow Stage ◽  
Dryland Rivers

Abstract. Some mixed bedrock-alluvial dryland rivers are known to undergo cycles of alluvial building during low flow periods, punctuated by stripping events during rare high magnitude flows. We focus on the Olifants River, Kruger National Park, South Africa, and present 2-D morphodynamic simulations of hydraulics and sediment deposition patterns over an exposed bedrock anastomosed pavement. We examine the assumptions underlying a previous conceptual model, namely that sedimentation occurs preferentially on bedrock highs. Our modelling results and local field observations in fact show that sediment thicknesses are greater over bedrock lows, suggesting these are the key loci for deposition, barform initiation and island building. During peak flows, velocities in the topographic lows tend to be lower than in intermediate topographic areas. It is likely that intermediate topographic areas supply sediment to the topographic lows at this flow stage, which is then deposited in the lows on the falling limb of the hydrograph as velocities reduce. Subsequent vegetation establishment on deposits in the topographic lows is likely to play a key role in additional sedimentation and vegetation succession, both through increasing the cohesive strength of alluvial units and by capturing new sediments and propagules.

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 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.

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