Determining the best discharge-suspended sediment relationship based on different time classifications and correction coefficients (Case study: Bashar River)

Document Type : Research Article

Authors

1 Graduated Student in Water Structures, Agricultural Sciences and Natural Resources University of Khuzestan, Khuzestan, Iran

2 Assistant Professor, Department of Water Engineering, Agricultural Sciences and Natural Resources University of Khuzestan, Khuzestan, Iran

Abstract

Using complex hydraulic equations to estimate river sedimentation requires a lot of data that is not available in many rivers. Therefore, simpler equations such as the Sediment rating curve (SRC) are used to estimate river sediment load. In some cases, rating curves are not accurate enough. To solve this problem, applying correction coefficients and temporal classification of discharge and sediment data based on the different factors. The present study was conducted with the aim of evaluating the effect of different correction methods and data classification to increase the accuracy of SRC in the Bashar river, southwest of Iran. The models were examined by 7 statistical criteria. The results showed that any temporal classification of the data increases the accuracy of sediment estimation and applying monthly and seasonal models, on average, increased the accuracy of estimates by 36 and 61 percent. Although using the middle of the classes model had 70% more points than the annual model. However, using the FAO correction method caused a 22% decrease in the accuracy of the estimates. In general, despite the positive effect of climatic, hydrological and vegetation models on increasing the accuracy of SRC, by 35, 28 and 20%, respectively, none of the models were superior. The results confirmed that the production and transfer of suspended sediment in the river are influenced by various factors such as climatic factors and especially the presence of vegetation. Paying attention to these changes in the use of discharge-sediment equations increases the accuracy of SRCs.

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Main Subjects

References

  • Vanmaercke M, Poesen J, Broeckx J, Nyssen J. Sediment yield in Africa. Earth-Science Rev. 2014;136:350–68.
  • Zhang HY, Shi ZH, Fang NF, Guo MH. Linking watershed geomorphic characteristics to sediment yield: Evidence from the Loess Plateau of China. Geomorphology. 2015;234:19–27.
  • Kasir H, Naserin A, Jafari A,... Field Evaluation of Some of the Grain-size Analysis Methods for Determining Hydraulic Conductivity of Streambed. Iran J Soil … [Internet]. 2020; Available from: https://ijswr.ut.ac.ir/mobile/article_76422_1f4d629fe61251e2ed9e4bbc69077692.pdf
  • Valipour L, Naserin A, Jalily S. Investigating the Relationship between Hydrological Drought and the Electrical Conductivity of the River in the Downstream Stations of the Karkheh River. Iran J Ecohydrol. 2023;9(4):815–31.
  • Raeesi M, Najafinejad A, Azim Mohseni M. Investigation of Temporal Phenomena of Sediment Rating Curve and Comparison of it with the Some Statistical Methods for Estimating Suspended Sediment Load (Case Study: Gamasiab Watershed). J Watershed Manag Res. 2019;10(20):83–96.
  • Horowitz AJ. An evaluation of sediment rating curves for estimating suspended sediment concentrations for subsequent flux calculations. Hydrol Process. 2003;17(17):3387–409.
  • Ahn KH, Yellen B, Steinschneider S. Dynamic linear models to explore time-varying suspended sediment-discharge rating curves. Water Resour Res. 2017;53(6):4802–20.
  • Eassa Kia, Eassa; Emadi A. Comparison of Statistical Methods for Long-Term Suspended Sediment Yield Estimation (Case Study: Babolrood River). J Watershed Manag Res. 2013;4(8):15–27.
  • Najafinezhad, Ali; Babaei, Akbar; Saniei, Ebrahim; Mahmoudi O. Comparison of seasonal suspended sediment measurement curves and monthly suspended load in a number of rivers in Golestan province. In: 4th national conference on erosion and sedimentation. 2010.
  • Fortesa J, Ricci GF, García-Comendador J, Gentile F, Estrany J, Sauquet E, et al. Analysing hydrological and sediment transport regime in two Mediterranean intermittent rivers. Catena. 2021;196.
  • Saghafian, Bahram; Ghermezcheshmeh, Bagher; Samiei M. Regional Analysis of Sediment in the southwestern Watersheds of Iran. 2007.
  • Jansson MB. Estimating a sediment rating curve of the Reventazon river at Palomo using logged mean loads within discharge classes. J Hydrol. 1996;183(3–4):227–41.
  • Jones, K.R; Berney, O.; Carr, O.p.; Barrett EC. Arid zone hydrology for agricultural development. Rome, Italy.; 1981. 271 p.
  • Arab-Khedri, Mahmoud; Hakimkhani, Shahrokh; Vardani J. Validity of extrapolation methods in estimating the average annual suspended sedimentation (17 hydrometric stations of the country). Q J Agric Sci Nat Resour. 2004;11(3):123–32.
  • Asselman NEM. Fitting and interpretation of sediment rating curves. J Hydrol. 2000;234(3–4):228–48.
  • Sun P, Wu Y, Gao J, Yao Y, Zhao F, Lei X, et al. Shifts of sediment transport regime caused by ecological restoration in the Middle Yellow River Basin. Sci Total Environ. 2020;698.

 

  • Tabatabaei M, Salehpour Jam A, Hosseini SA. Presenting a New Approach to Increase the Efficiency of the Sediment Rating Curve Model in Estimating Suspended Sediment Load in Watersheds (Case Study: Mahabad-Chai River, Lake Urmia Basin, West Azarbayejan Province, Iran). J Watershed Manag Res. 2019;10(19):181–93.
  • Ramezanipour, Elyas; Mosaedi, abolfazl; Mosadeghi M. Determination of the Best Model for Estimation of Suspended Sediment by using Statistical Error Criteria (Case study: Some Sub-Watersheds of Kashaf Roud). J Watershed Manag Res. 2017;8(15):112–24.
  • Mardian, Mehdi; Solaimani, Karim; Shahedi, Kaka; Kavian, Ataollah; Ghadimi F. Analysis of Temporal Variations for the Suspended Load Transport in the Marboreh River, Darreh-Takht, Lorestan Province, Iran. Watershed Manag Res. 2018;31(1)(118):60–72.
  • Ahmadi, Hassan; Malekian, Arash; Abedi R. The most Appropriate Statistical Method for Suspended Sediment Estimation of Rivers (Case Study: Roodak Station of the Jajrood Basin). Q J Environ Eros Res. 2012;2(1):78–88.
  • Yousefi, Mohsen; Barzegari F. Determining the most suitable measuring curve method and comparing it with artificial neural network in order to estimate suspended sediments (case study: Lorestan province). J Range Watershed Manag. 2015;68(2):413-426.
  • Oliveira KSS, Quaresma V da S. Temporal variability in the suspended sediment load and streamflow of the Doce River. J South Am Earth Sci. 2017;78:101–15.
  • Moslemzadeh M, Roueinian K, Salarijazi M. Improving the estimation of sedimentation in multi-purpose dam reservoirs, considering hydrography and time scale classification of sediment rating curve (case study: Dez Dam). Arab J Geosci. 2022;15(3).
  • Sobhani H. Application and comparison of statistical methods for estimation of suspended sediment load (case study: Hable Rood watershed). Semnan University; 2010.
  • Latifi, A; Hassanzadeh Y. The comparison of different methods of estimating the suspended sediment load in rivers and choosing the most appropriate method (case study: Gamasiab River). In: 7th International River Engineering Conference. Ahvaz; 2007. p. 9.
  • Zakwan M, Ahmad Z. Analysis of sediment and discharge ratings of Ganga River, India. Arab J Geosci. 2021;14(19).
  • Esfandiari, M; Moeini, M; Moqadasi A. Effect of land use and vegetation on erosion forms and sediment production(Case study: Vers Watershed Qazvin Province). Q Geogr J Territ. 2014;11(42):51–62.
  • Sadeghi SHR, Khazayi M, Mirnia SK. Effect of soil surface disturbance on overland flow, sediment yield, and nutrient loss in a hyrcanian deciduous forest stand in Iran. Catena. 2022;218.

 

Iranian journal of Ecohydrology
Volume 10, Issue 1
April 2023
Pages 113-125

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History

  • Receive Date: 01 January 2023
  • Revise Date: 31 January 2023
  • Accept Date: 03 March 2023
  • First Publish Date: 01 August 2023
  • Publish Date: 01 August 2023

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