Frequency analysis of maximum annual suspended sediment concentrations in North America / Analyse fréquentielle des maximums annuels de concentration en sédiments en suspension en Amérique du Nord

Tramblay, Yves; St‐Hilaire, André; Ouarda, Taha B. M. J.

doi:10.1623/hysj.53.1.236

Cited by 36 publications

(18 citation statements)

References 40 publications

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“…Using the fitted probability distribution, it is possible to predict the probability of exceedence for a specified magnitude (i.e. quantile) or the magnitude associated with a specific exceedence probability (Tramblay et al 2008). …”

Section: Methodsmentioning

confidence: 99%

“…Annual SSC variation is a key practice for planning and management of water resources and dam regulations such as the time of water storage into and water release from dam. Suspended sediment concentration is therefore an important abiotic variable used to quantify water quality and habitat availability for some species of fish and invertebrate (Tramblay et al 2008). From the above discussion, SSC is an important abiotic variable to quantify water quality.…”

Section: Introductionmentioning

confidence: 99%

“…However few studies attempted to apply this technique to predict sediment quantiles. Tramblay et al (2008) employed FA technique to predict annual extreme events of SSC. They tried to fit probability distributions to stations data recorded to estimate the return period for a specific concentration or the concentration for a given return period.…”

Section: Introductionmentioning

confidence: 99%

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Annual suspended sediment concentration frequency analysis in Sefidroud basin, Iran

Kavian

Dodangeh

Abdollahi

2016

Model. Earth Syst. Environ.

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Estimation of suspended sediment concentration (SSC) is crucial for water quality management, locating potential sites for fish habitat and reservoir dam regulations. This study aims at representing frequency analysis of annual SSC by applying several cumulative distributions in Sefidroud basin. Three preliminary tests were used to assess whether the data set comply with the hypothesis of homogeneity, stationary and randomness of the investigated time series. Then, frequency analysis of annual SSC carried out by applying different cumulative distribution functions. Goodness-of-fit tests indicated that 2-parameter distributions fit to annual SSC time series. Among the others, LN2, EV1, Logistic, GPAR distributions were the best fit distributions according to the Goodness-of-fit tests. The greatest values of SSC calculated for Ghareguni and YengiKand stations with quantities of 111,711.81 and 32,308.23 gr/L for 2 and 833,095.26 and 158,412.37 gr/L for 10 years return period respectively which should be considered for integrated erosion control projects.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Annual suspended sediment concentration frequency analysis in Sefidroud basin, Iran

Kavian

Dodangeh

Abdollahi

2016

Model. Earth Syst. Environ.

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“…Based on our observations regarding the linear relationship between annual flow volumes in intermediate, high and peak flow stages and annual SLs, we also argue that years with high average daily discharge and annual flow would produce high annual sand loads within the given return periods and vice-versa. Previous studies have analyzed several year peaks for suspended sediment loads and concentrations [65,66] and even for river flows and stages [67,68] in different rivers around the world. However, to the best of our knowledge, maximum and minimum DSLs and annual SLs for short-and long-term return periods have not been analyzed for any river location to date.…”

Section: Future Likelihood Of Sand Transport In the Lmmrmentioning

confidence: 99%

Assessment of Suspended Sand Availability under Different Flow Conditions of the Lowermost Mississippi River at Tarbert Landing during 1973–2013

Joshi

2015

Water

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Rapid land loss in the Mississippi River Delta Plain has led to intensive efforts by state and federal agencies for finding solutions in coastal land restoration in the past decade. One of the proposed solutions includes diversion of the Mississippi River water into drowning wetland areas. Although a few recent studies have investigated flow-sediment relationships in the Lowermost Mississippi River (LmMR, defined as the 500 km reach from the Old River Control Structure to the river's Gulf outlet), it is unclear how individual sediment fractions behave under varying flow conditions of the river. The information can be especially pertinent because the quantity of coarse sands plays a critical role for the Mississippi-Atchafalaya River deltaic development. In this study, we utilized long-term (1973-2013) records on discharge and sediments at Tarbert Landing of the LmMR to assess sand behavior and availability under different river flow regimes, and extreme sand transport events and their recurrence. We found an average annual sand load (SL) of 27.2 megatonnes (MT) during 1973 and 2013, varying largely from 3.37 to 52.30 MT. For the entire 41-year study period, a total of approximately 1115 MT sand were discharged at Tarbert Landing, half of which occurred during the peak 20% flow events. A combination of intermediate, high and peak flow stages (i.e., river discharge was ě18,000 cubic meter per second) produced about 71% of the total annual SL within approximately 120 days of a year. Based on the long-term sediment assessment, we predict that the LmMR has a high likelihood to transport 4 to 446 thousand tonnes of sand every day over the next 40 years, during which annual sand loads could reach a maximum of 51.68 MT. Currently, no effective plan is in place to utilize this considerably high sand quantity and we suggest that river engineering and sediment management in the LmMR consider practices of hydrograph-based approach for maximally capturing riverine sediments.

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“…At the catchment outlets, it is very likely that there is lag-time between R and SSL as well as Q and SSL due to clockwise hysteretic effect [22][23][24]. Hence, consideration of R and Q from previous time step could improve the model accuracy.…”

Section: Datamentioning

confidence: 99%

Coupling Singular Spectrum Analysis with Artificial Neural Network to Improve Accuracy of Sediment Load Prediction

Heng¹,

Suetsugi²

2013

JWARP

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Sediment load estimation is generally required for study and development of water resources system. In this regard, artificial neural network (ANN) is the most widely used modeling tool especially in data-constraint regions. This research attempts to combine SSA (singular spectrum analysis) with ANN, hereafter called SSA-ANN model, with expectation to improve the accuracy of sediment load predicted by the existing ANN approach. Two different catchments located in the Lower Mekong Basin (LMB) were selected for the study and the model performance was measured by several statistical indices. In comparing with ANN, the proposed SSA-ANN model shows its better performance repeatedly in both catchments. In validation stage, SSA-ANN is superior for larger Nash-Sutcliffe Efficiency about 24% in Ban Nong Kiang catchment and 7% in Nam Mae Pun Luang catchment. Other statistical measures of SSA-ANN are better than those of ANN as well. This improvement reveals the importance of SSA which filters noise containing in the raw time series and transforms the original input data to be near normal distribution which is favorable to model simulation. This coupled model is also recommended for the prediction of other water resources variables because extra input data are not required. Only additional computation, time series decomposition, is needed. The proposed technique could be potentially used to minimize the costly operation of sediment measurement in the LMB which is relatively rich in hydrometeorological records.

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Frequency analysis of maximum annual suspended sediment concentrations in North America / Analyse fréquentielle des maximums annuels de concentration en sédiments en suspension en Amérique du Nord

Cited by 36 publications

References 40 publications

Annual suspended sediment concentration frequency analysis in Sefidroud basin, Iran

Annual suspended sediment concentration frequency analysis in Sefidroud basin, Iran

Assessment of Suspended Sand Availability under Different Flow Conditions of the Lowermost Mississippi River at Tarbert Landing during 1973–2013

Coupling Singular Spectrum Analysis with Artificial Neural Network to Improve Accuracy of Sediment Load Prediction

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