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Investigating most appropriate method for estimating suspended sediment load based on error criterias in arid and semi-arid areas (case study of Kardeh Dam watershed stations)

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Abstract

The present study findings indicated that the sedimentation problem is severe. The most obvious impact of sedimentation in a reservoir is the cumulative loss of its storage capacity, affecting both the operational plan and economic investments based on reservoir use, especially in the drinking sector. To determine the most appropriate method for estimating suspended sediment in the Kardeh Dam reservoir located in a semi-arid region, measured flow discharge and suspended sediment load data at two hydrometric stations (Kardeh and Koshakabad) were investigated. To select an optimal model (with the best adaptation to hydrography operation results), the amount of suspended sediment transport by applying 6 models based on sediment rating curve equations and 14 individual and compound error criterias were estimated. By combining error criterias, 6 methods and 8 sub-methods were examined. It was found that the use of numerous individual or compound error criterias approximately has the same results, but using mean scores of individual/compound error criterias or only compound error criterias can improve the results. According to the results of statistics and hydrographic operations, a model of sediment rating curve equation is determined as the optimal model (model F). In this model, sediment discharge data can be divided into four categories according to hydrological conditions, and for each category, the equation of sediment rating curve was determined. It is suggested to conduct similar research in different climatic areas in order to investigate the effects of climatic conditions on data classification and selection of the most suitable sediment transport estimation model.

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Notes

  1. Agricultural Modern-Era Retrospective analysis for Research and Applications

  2. Coordination of information on the environment

References

  • Alizadeh A (2020) Principles of applied hydrology, 42nd edn. University of Imam Reza (AS) press (In Persian)

    Google Scholar 

  • Asselman NEM (2000) Fitting and interpretation of sediment rating curves. J Hydrol 234(3-4):228–248. https://doi.org/10.1016/S0022-1694(00)00253-5

    Article  Google Scholar 

  • Bahadori F (2001) Basic Principles To Taking Sand And Gravel From Rivers. Ministry of Energy of the Islamic Republic of Iran Publications

  • Bahrami M, Bazrkar S, Zarei R (2018) Modeling, prediction and trend assessment of drought in Iran using standardized precipitation index. J Water Climate Chan 10:181–196. https://doi.org/10.2166/wcc.2018.174

    Article  Google Scholar 

  • Balamurugan G (1989) The use of suspended sediment rating curves in Malaysia: some preliminary considerations. Pertanika 12(3):367–376

    Google Scholar 

  • Bashar KE, ElTahir EO, Fattah SA, Ali AS, Osman M (2010) Nile Basin reservoir sedimentation prediction and mitigation. Nile Basin Capacity Building Network. Cairo, Egyp

    Google Scholar 

  • Bellocchi G, Acuit M, Fila G, Donatelli M (2002) An indicator of solar radiation model performance based on a fuzzy expert system. Agron J 94:1222–1233

    Article  Google Scholar 

  • Benisi Ghadim H, Salarijazi M, Ahmadianfar I, Heydari M, Zhang T (2020) Developing a sediment rating curve model using the curve slope. Pol J Environ Stud 29(2):1151–1159. https://doi.org/10.15244/pjoes/103470

    Article  Google Scholar 

  • Benselama O, Hasbaia M, Djoukbala O, Boutaghane H, Ferhati A, Djerbouai S (2021) Suspended sedimentary dynamics under Mediterranean semi-arid environment of Wadi El Maleh watershed. Algeria Model Earth Syst Environ. https://doi.org/10.1007/s40808-021-01133-4

  • Chen XY, Chau KW (2016) A hybrid double feedforward neural network for suspended sediment load estimation. Water Resour Manag 30:2179–2194

    Article  Google Scholar 

  • Cloke HL, Pappenberger F (2008) Evaluating forecasts of extreme events for hydrological applications: an approach for screening unfamiliar performance measures. Meteorol Appl 15:181–197. https://doi.org/10.1002/met.58

    Article  Google Scholar 

  • Dawson CW, Mount NJ, Abrahart RJ, Shamseldin AY (2012) Ideal point error for model assessment in data-driven river flow forecasting. J Hydro Earth Syst Sci 16:3049–3060. https://doi.org/10.5194/hess-16-3049-2012

    Article  Google Scholar 

  • De Girolamo AM, Pappagallo G, Lo Porto A (2015) Temporal variability of suspended sediment transport and rating curves in a Mediterranean river basin: the Celone (SE Italy). J Catena 128:135–143. https://doi.org/10.1016/j.catena.2014.09.020

    Article  Google Scholar 

  • De Girolamo AM, Di Pillo R, Lo Porto A, Todisco MT, Barca E (2018) Identifying a reliable method for estimating suspended sediment load in a temporary river system. J Catena 165:442–453. https://doi.org/10.1016/j.catena.2014.09.020

    Article  Google Scholar 

  • Demirci M, Baltaci A (2013) Prediction of suspended sediment in river using fuzzy logic and multilinear regression approaches. Neural Comput & Applic 23:145–151

    Article  Google Scholar 

  • Efthimiou N (2019) The role of sediment rating curve development methodology on river load modeling. Environ Monit Assess 191(108):108. https://doi.org/10.1007/s10661-018-7167-4

  • Elshorbagy A, Corzo G, Srinivasulu S, Solomatine D (2010) Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology – part 1: concepts and methodology. Hydrol Earth Syst Sci 14:1931–1941. https://doi.org/10.5194/hess-14-1931-2010

    Article  Google Scholar 

  • European Environment Agency (2005) CORINE land cover. EEA Publications about Europe's environment. https://www.eea.europa.eu/publications/COR0-landcover

  • Feranec J, Hazeu G, Christensen S, Jaffrain G (2007) Corine land cover change detection in Europe (case studies of the Netherlands and Slovakia). Land Use Policy 24(1):234–247. https://doi.org/10.1016/j.landusepol.2006.02.002

    Article  Google Scholar 

  • Ferdowsi University of Mashhad (1987) Sixth report of the Kardeh Dam catchment studies -pasture and livestock. Iran (In Persian)

  • Jung BM, Fernandes EH, Möller OO, García-Rodríguez F (2020) Estimating Suspended sediment concentrations from river discharge data for reconstructing gaps of information of long-term variability studies. Water 12(9):2382. https://doi.org/10.3390/w12092382

    Article  Google Scholar 

  • Fox DG (1981) Judging air quality model performance. Bull Am Meteorol Soc 62:599–609

    Article  Google Scholar 

  • Ghernaout R, Remini B (2014) Impact of suspended sediment load on the silting of SMBA reservoir (Algeria). Environ Earth Sci 72:915–929

    Article  Google Scholar 

  • Ghorghi JH, Habibnejad M, Soleymani K, Khaledi Darvishan A (2011) Examination of solutions for enhancement of accuracy and precision of sediment rating curve in Telvar and Chamsur rivers located in Kordestan Province, Iran. Proceeding of 7th National Seminar on Watershed Management Sciences and Engineering, Isfahan University of Technology, Esfahan, Iran. (In Persian)

  • Grubbs FE, Beck G (1972) Extension of sample sizes and percentage points for significance tests of outlying observations. Technometrics 14(4):847–854

    Article  Google Scholar 

  • Gulinck H, Mugica M, Lucio JV, Atauri JA (2001) A framework for comparative landscape analysis and evaluation based on land cover data, with an application in the Madrid region (Spain). Landsc Urban Plan 55:257–270. https://doi.org/10.1016/S0169-2046(01)00159-1

    Article  Google Scholar 

  • Hall MJ (2001) How well does your model fit the data? J Hydroinf 3:49–55. https://doi.org/10.2166/hydro.2001.0006

    Article  Google Scholar 

  • Han KS, Champeaux JL, Roujean JL (2004) A land cover classification product over France at 1 km resolution using SPOT4/VEGETATION data. Remote Sens Environ 92:52–66. https://doi.org/10.1016/j.rse.2004.05.005

    Article  Google Scholar 

  • Hapsari D, Onishi T, Imaizumi F, Noda K, Senge M  (2019) The Use of Sediment Rating Curve under its Limitations to Estimate the Suspended Load. Rev Agri Sci 7(0):88–101. https://doi.org/10.7831/ras.7.0_88

  • Heydarnejad M, Golmaei S, Mosaedi A, Ahmadi MZ (2004) Optimized sediment load estimation model (case study: inlet and outlet of Karaj Hydrometric stations). Bull Khazar Agricult Sci Natural Resour 2(6):54–67 (In Persian)

    Google Scholar 

  • Hicks DM, Gomez B, Trustrum NA (2000) Erosion thresholds and suspended sediment yields, Waipaoa River Basin, New Zealand. Water Resour Res 36(4):1129–1142. https://doi.org/10.1029/1999WR900340

    Article  Google Scholar 

  • Hong Y, Hsu KL, Sorooshian S, Gao X (2005) Improved representation of diurnal variability of rainfall retrieved from the Tropical Rainfall Measurement Mission microwave imager adjusted Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) system. J Geophys Res Atmos 110(D6)

  • Horowitz AJ (2002) The use of rating (transport) curves to predict suspended sediment concentration: a matter of temporal resolution. Turbidity and Other Sediment Surrogates Workshop, April 30 – May 2, 2002, Reno, NV. U.S. Geological Survey.3 pp. Access in 5 Feb 2020 in https://www.comm-tec.com/library/Technical_Papers/Various/horowitz.pdf.

  • Hosseini SM, Mosaedi A, Golkarian A, Nasseri K (2015) Modeling some factors of affecting rill erosions using fuzzy inference system. J Water Soil Conserva 22(4):103–120 (In Persian)

    Google Scholar 

  • Huffman GJ, Bolvin DT, Nelkin EJ, Wolff DB, Adler RF, Gu G, Stocker EF (2007) The TRMM Multisatellite Precipitation Analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol 8(1):38–55

    Article  Google Scholar 

  • Iwalewa TM, Elamin AS, Kaka SI (2016) A coupled model simulation assessment of shallow water-table rise in a Saudi Arabian coastal city. J Hydro Environ Res 12:46–58

    Article  Google Scholar 

  • Karaushev AV (1973) Computation of reservoirs sedimentation. AISH Publi 108:199–205

    Google Scholar 

  • Khanchoul K, Boukhrissa ZEA, Acidi A, Altschul A (2010) Estimation of suspended sediment transport in the Kebir drainage basin, Algeria. Quat Int 3:1–7. https://doi.org/10.1016/j.quaint.2010.08.016

    Article  Google Scholar 

  • Khorasan Razavi Regional Water Company (2018) Information System of Reservoir Dams in Operation Report. (In Persian)

  • Kokpinar MA, Altan-Sakarya AB, Kumcu SY, Gogus M (2014) Assessment of sediment yield estimations for large watershed areas: a case study for the Seyhan, Demirköprü, and Hirfanlı reservoirs in Turkey. Hydrol Sci J 60(12):2189–2203. https://doi.org/10.1080/02626667.2014.959954

  • Latifi A, Hassanzadeh Y (2007) The comparison of different methods of estimating the suspended sediment load in rivers and choosing the most appropriate method (case study: Gamasiab River). Proceedings of the 7th International River Engineering Conference. Shahid Chamran University, Ahvaz, Iran. (In Persian)

  • Legates DR, McCabe GJ Jr (1999) Evaluating the use of “goodness of fit” measures in hydrologic and hydroclimatic model validation. Water Resour Res 35(1):233–241

    Article  Google Scholar 

  • Mahmood K (1987) Reservoir sedimentation: impact, extent, and mitigation, Technical paper No PB-88-113964/XAB; WORLD-BANK-WTP-71, International Bank for Reconstruction and Development, Washington, DC

  • Maidment DR, Mays LW, Chow VT (1998) Applied hydrology. McGraw – Hill Book Company, New York

    Google Scholar 

  • Melesse AM, Ahmad S, Mcclina ME, Wang X, Limd YH (2011) Suspended sediment load prediction of river systems: an artificial neural network approach. Agric Water Manag 98:855–866. https://doi.org/10.1016/j.agwat.2010.12.012

    Article  Google Scholar 

  • Mirzaei M (2002) Comparison of statistical method of suspended load estimation in rivers (case study: Gorganrood River). Dissertation, University of Tehran (In Persian)

  • Moges M, Abay D, Engidayehu H (2018) Investigating reservoir sedimentation and its implications to watershed sediment yield: the case of two small dams in data scarce upper Blue Nile Basin, Ethiopia. Lakes Reservoi 23(3):217–229. https://doi.org/10.1111/lre.12234

    Article  Google Scholar 

  • Mohamadrezapour OB (2005) Comparison of estimated rates of sediment load using different models against rates of sedimentation volume in two storage dam. Dissertation, Mazandaran University. (In Persian)

  • Mohammadi A, Mosaedi A, Heshmatpour A (2007) Determination of the best model to estimate suspended sediment loads in Ghazaghly water gauge, Gorganrood river, Iran. J Agricult Sci Natural Resour 14(4):232–240 (In Persian)

    Google Scholar 

  • Mosaedi A (1998) Hydrological sizing of sediment reservoir system for irrigation and water supply. Ph.D. Dissertation, Technical University of Budapest. Hungary

  • Mosaedi A, Ghabaei Sough M (2013) Evaluation of different empirical equations of reference crop evapotranspiration in different conditions lacking measured meteorological parameters in some climatic regions of Iran. J Water Soil Conserva 20(3):27–50 (In Persian)

    Google Scholar 

  • Mosaedi A, Hashemin Najafi F, Heydarnejad M, Nabizade M, Meshkati MA (2009) Estimation of settling loads in Karaj and Dez Dam reservoirs. J Agricult Sci Natural Resour 16(2):261–272 (In Persian)

    Google Scholar 

  • Pedram I, Barani GA (2007) Evaluation of suspended sediment in dam's reservoirs with separation of wet and dry periods. (Case study: Zayanderood dam). proceeding of the 6th Iranian Hydraulic Conference, Shahrekord University, Iran. (In Persian)

  • Phillips JB, Walling WD, Leeks G (1999) Estimating the suspended sediment load of rivers in the LOIS study area using infrequent samples. Hydrol Process 13(7):1035–1050

    Article  Google Scholar 

  • Piri A (2003) Optimization of flow and sediment discharge relation in Emame Basin. Dissertation, Sari University of Agricultural Sciences and Natural Resources.(In Persian).

  • Pour Aghniaei Mj, Domiri Ganji M, Yousef Pour A, Ghermezcheshmeh B (2008) A review on estimation methods for suspended load (Case Study: Seydon Basin). Iran Water Resources Research 3(3):73–75. (In Persian)

  • Rahman M, Dustegir M, Karim K, Haque A, Nicholls RJ, Darby SE, Nakagawa H, Hossain M, Dunn FE, Akter M (2018) Recent sediment flux to the Ganges-Brahmaputra-Meghna delta system. Sci Total Environ 643:1054–1064. https://doi.org/10.1016/j.scitotenv.2018.06.147

    Article  Google Scholar 

  • Rajaee T (2011) Wavelet and ANN combination model for prediction of daily suspended sediment load in rivers. Sci Total Environ 409:2917–2928

    Article  Google Scholar 

  • Ramezanipoor E, Mosaedi A, Mesdaghi M (2017) Determination of the best model for estimation of suspended sediment by using statistical error criteria (case study: some sub-watersheds of Kashaf Roud). J Water Manag Resea 8(15):112–124. https://doi.org/10.29252/jwmr.8.15.112

    Article  Google Scholar 

  • Rienecker MM, Suarez MJ, Gelaro R, Todling R, Bacmeister J, Liu E, Woollen J (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Clim 24(14):3624–3648

    Article  Google Scholar 

  • Rostami M, Ardeshir A (2001) A suggestion method to improve suspended sediment load estimation in river. Proceedings of the 3rd Conference on Hydraulic of Sediment. Tehran University (In Persian)

  • Ruane AC, Goldberg R, Chryssanthacopoulos J (2015) Climate forcing datasets for agricultural modeling: merged products for gap-filling and historical climate series estimation. Agric For Meteorol 200:233–248

    Article  Google Scholar 

  • Sadeghi SHR, Mizuyama T, Miyata S, Gomi T, Kosugi K, Fukushima T, Mizugaki S, Onda Y (2008) Development, evaluation and interpretation of sediment rating curves for a Japanese small mountainous reforested watershed. Geoderma 144:198–211. https://doi.org/10.1016/j.geoderma.2007.11.008

    Article  Google Scholar 

  • Salahi B, Nohegar A, Behrouzi M (2016) The modeling of precipitation and future droughts of Mashhad plain using stochastic time series and Standardized Precipitation Index (SPI). Intern J Environ Rese 10(4):625–636

    Google Scholar 

  • Salehnia N, Alizadeh A, Sanaeinejad H, Bannayan M, Zarrin A, Hoogenboom G (2017) Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data. J Arid Land 9:797–809. https://doi.org/10.1007/s40333-017-0070-y

    Article  Google Scholar 

  • Schmidt KH, Morche D (2006) Sediment output and effective discharge in two small high mountain catchments in the Bavarian Alps Germany. Geomorphology 80:131–145. https://doi.org/10.1016/j.geomorph.2005.09.013

    Article  Google Scholar 

  • Shi ZH, Huangb XD, Ai L, Fang NF, Wu GL (2014) Quantitative analysis of factors controlling sediment yield in mountainous watersheds. Geomorphology 226:193–201. https://doi.org/10.1016/j.geomorph.2014.08.012

    Article  Google Scholar 

  • TAMAB (Water Resources Research Center of Iran) (1997) Report of hydrography and sediment assessment of Torogh and Kardeh dams. (In Persian)

  • Telvari AR (2003) Relationship between suspended sediment yield and some catchment characteristics in sub-catchments of Dez and Karkheh rivers in Lorestan province. Pajoh Sazan J 5657:56–61

    Google Scholar 

  • Thomas RB (1988) Monitoring baseline suspended sediment in forested basins: the effects of sampling on suspended sediment rating curves. Hydrol Sci J 33:499–514. https://doi.org/10.1080/02626668809491277

    Article  Google Scholar 

  • Walling DE, Fang D (2003) Recent trends in the suspended sediment loads of the world’s rivers. Glob Planet Chang 39(1-2):111–126. https://doi.org/10.1016/S0921-8181(03)00020-1

    Article  Google Scholar 

  • Walling DE, Webb BW (1982) Sediment availability and the prediction of storm-period sediment yields. Recent developments in the explanation and prediction of erosion and sediment yield. IAHS Publ 137:327–337

    Google Scholar 

  • Wang K, Gelda RK, Mukundan R, Steinschneider S (2021)Inter-model comparison of turbidity-discharge rating curves and the implications for reservoir operations management. J Ame Water Resour Asso On-line vers 57:1–19. https://doi.org/10.1111/1752-1688.12906

  • White JW, Hoogenboom G, Stackhouse PW Jr, Hoell JM (2008) Evaluation of NASA satellite- and assimilation model-derived long-term daily temperature data over the continental US. Agric For Meteorol 148(10):1574–1584

    Article  Google Scholar 

  • Willmott CJ (1982) Some comments on the evaluation of model performance. Bull Am Meteorol Soc 63:1309–1313

    Article  Google Scholar 

  • Wooldridge J M (2013) Introductory Econometrics, A Modern Approach, 5th Edition. South-Western Cengage Learning Press,USA. ISBN-10:1-111-53104-8Introductory econometrics: a modern approach. South-Western Cengage Learning Press.5th ed.

  • Yatagai A, Arakawa O, Kamiguchi K, Kawamoto H, Nodzu MI, Hamada A (2009) A 44-year daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Sola 5:137–140

    Article  Google Scholar 

  • Yılmaz B, Aras E, Nacar S (2016) Estimation of daily suspended sediment load with an artificial neural network. Proceedings of the 1st International Black Sea Congress on Environmental Sciences (IBCESS) Giresun, Turkey. 31 Aguest – 03 September 2016. available in: https://personel.klu.edu.tr/IBCESS_Abstract_Book.pdf

  • Youssef Vand F (2004) Suggestion of a method for estimation of suspended load in rivers (case study: Ghresoo river). M.Sc. thesis, Sari Agricultural Sciences and Natural Resources University. (In Persian)

  • Zeng C, Zhang F, Lu X, Wang G, Gong T (2018) Improving sediment load estimations: the case of the Yarlung Zangbo River (the upper Brahmaputra, Tibet Plateau). J Catena 160:201–211. https://doi.org/10.1016/j.catena.2017.09.023

    Article  Google Scholar 

  • Zhang HY, Shi ZH, Fang NF, Gua MH (2015) Linking watershed geomorphic characteristics to sediment yield: evidence from the Loess Plateau of China. Geomorphology 234(1):19–27. https://doi.org/10.1016/j.geomorph.2015.01.014

    Article  Google Scholar 

  • Zhang J, Zhang X, Li R, Chen L, Lin P (2017) Did streamflow or suspended sediment concentration changes reduce sediment load in the middle reaches of the Yellow River?. J Hydrol 546: 357-369. https://doi.org/10.1016/j.jhydrol.2017.01.002

  • Zheng M (2018) A spatially invariant sediment rating curve and its temporal change following watershed management in the Chinese Loess Plateau. Sci Total Environ 630:1453–1463. https://doi.org/10.1016/j.scitotenv.2018.02.323

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Geology, International Campus, Ferdowsi University of Mashhad, Mashhad, 91779-48978, Iran

    Hoda Mousazadeh

  2. Water Science and Engineering Department, Ferdowsi University of Mashhad, Mashhad, 91779-48978, Iran

    Abolfazl Mosaedi

  3. Department of Geology, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, 91779-48978, Iran

    Mohamad Hosein Mahmudy Gharaie & Reza Moussavi Harami

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  1. Hoda Mousazadeh
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Mousazadeh, H., Mosaedi, A., Mahmudy Gharaie, M.H. et al. Investigating most appropriate method for estimating suspended sediment load based on error criterias in arid and semi-arid areas (case study of Kardeh Dam watershed stations). Arab J Geosci 14, 2133 (2021). https://doi.org/10.1007/s12517-021-08414-3

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