Skip to main content

Advertisement

Log in

Discharge estimation and rating curve derivation, using satellite geometry data and isovel contours at Karun River, Iran

  • Research Article - Hydrology
  • Published:
Acta Geophysica Aims and scope Submit manuscript

Abstract

Determining discharge and stage–discharge curves in fluvial environments without hydrometric gauges is a critical challenge in hydrologic studies and river hydraulics. This issue will be more evident in managing flood hazards in the rivers of arid areas without flow measurement gauges, where the reaction time is the critical factor. Researchers and designers have always tried to access simpler, cheaper methods to estimate discharge and rating curves. This research aims to facilitate the determination of the discharge and stage–discharge relationship by applying remote sensing techniques and the concept of isovel contours. For this purpose, the geometry of the river cross section is determined using remotely sensed data from the images of the Sentinel-1 and two satellites, and then discharge passed through the cross section is estimated by the single point velocity measurement method. The observed data were collected from the Mollasani station in Karun River, Iran, to confirm this method. The obtained discharges and stage–discharge relationship curves are used to evaluate the accuracy of the proposed methodology. Statistical analyses showed that the mean value of the normalized percentage error and mean absolute percentage error (MAPE) calculated based on the difference between the estimated and observed discharges are limited to 6.3 and 8.36%, respectively. Also, the stage–discharge curves in these studies were estimated with a maximum MAPE of 9.5%, which is considered a good initial approximation considering the minimum required data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Availability of data and materials

Data and material are available upon request to the corresponding author.

Abbreviations

A :

Cross-sectional area of flow

B :

Open-channel width

c, c 1 , c 2, c 2 :

Proportionality constant

C :

Normalized velocity

du :

Differential velocity deviation between an element of the boundary and an arbitrary point in the flow field

f ():

A function of

H :

Water depth along y-axis at a cross section

k s :

Equivalent Nikuradse sand roughness

m :

Constant; exponent of power formula

P :

Wetted perimeter

Q :

Discharge

Q 0 :

Observed discharge

Q e :

Estimated discharge

r :

Position vector of arbitrary point in field

r :

Subscripts, represents the referenced value

e :

Subscripts, represents the estimated value

u m :

Measured velocity component in the streamwise direction

u :

Local velocity

U :

Average cross-sectional velocity

u :

Boundary shear velocity

du SPM :

Effect of ds from the wetted perimeter on the velocity at an arbitrary point with the coordinates of \((y,z)\)

n :

Manning roughness equivalent

y :

Normal distance from the wall (left bank)

\(\theta\) :

Angle between the positional vector r and the boundary element vector ds

T max :

Maximum width of the water surface

\(\tau_{0}\) :

Boundary shear stress

u SPM :

Local point velocity

\((y,z)\) :

An arbitrary position in the channel section

σ ° :

Output radar backscatter bands

References

  • Al-Khudhairy D, Leemhuis C, Hoffmann V, Shepherd IM, Calaon R (2002) Monitoring wetland ditch water levels using Landsat TM and ground-based measurements. Photogramm Eng Remote Sens 68(8):809–818

    Google Scholar 

  • Bjerklie DM, Moller D, Smith LC, Dingman SL (2005) Estimating discharge in rivers using remotely sensed hydraulic information. J Hydrol 309(1):191–209. https://doi.org/10.1016/j.jhydrol.2004.11.022

    Article  Google Scholar 

  • Boothroyd RJ, Williams RD, Hoey TB, Barrett B, Prasojo OA (2021) Applications of google earth engine in fluvial geomorphology for detecting river channel change. Wiley Interdiscip Rev: Water 8(1):e21496

    Article  Google Scholar 

  • Cavallo C, Nicolina PM, Gargiulo M, Palau-Salvador G, Vezza P, Ruello G (2021a) Continuous Monitoring of the flooding dynamics in the albuferawetland (Spain) by Landsat-8 and Sentinel-2 datasets. Remote Sens 2021(13):3525. https://doi.org/10.3390/rs13173525

    Article  Google Scholar 

  • Cavallo C, Nones M, Nicolina Papa M, Gargiulo M, Ruello G, (2021b) Monitoring the morphological evolution of a reach of the Italian Po River using multispectral satellite imagery and stage data. Geocarto International, Taylor & Francis Onlinehttps://doi.org/10.1080/10106049.2021.2002431

  • Chen C-L (1991) Unified theory on power laws for flow resistance. J Hydraul Eng 117(3):371–389. https://doi.org/10.1061/(ASCE)0733-9429(1991)117:3(371)

    Article  Google Scholar 

  • Coe MT, Birkett CM, (2004) Calculation of river discharge and prediction of lake height from satellite radar altimetry: Example for the Lake Chad Basin. Water Resour Res, 40(10), https://doi.org/10.1029/2003WR002543

  • Farnoush H, Maghrebi MF (2021) Application of surface velocimetry in estimating rating curves in compound channels. Flow Meas Instrum 82:402–409. https://doi.org/10.1016/j.flowmeasinst,2021.102049

    Article  Google Scholar 

  • Genç O, Ardıçlıoğlu M, Ağıralioğlu N (2015) Calculation of mean velocity and discharge using water surface velocity in small streams. Flow Meas Instrum 41:115–120

    Article  Google Scholar 

  • Gilvear DJ, Bryant R (2016) Analysis of remotely sensed data for fluvial geomorphology and river science. In: Kondolf M, Piegay H (eds) Tools in fluvial geomorphology. Wiley, Chichester, England, pp 103–132

    Chapter  Google Scholar 

  • Gleason C, Smith L, Lee J (2014) Retrieval of river discharge solely from satellite imagery and at-many-stations hydraulic geometry: sensitivity to river form and optimisation parameters. AGU Water Resour Res 50(12):9604–9619

    Article  Google Scholar 

  • Jiang H, Feng M, Zhu Y, Lu N, Huang J, Xiao T (2014) An automated method for extracting rivers and lakes from Landsat imagery. Remote Sens 6(6):5067–5089

    Article  Google Scholar 

  • Maghrebi MF (2006) Application of the single-point measurement in discharge estimation. Adv Water Resour 29(10):1504–1514. https://doi.org/10.1016/j.advwatres.2005.11.007

    Article  Google Scholar 

  • Maghrebi MF, Ahmadi A (2017) Stage-discharge prediction in natural rivers using an innovative approach. J Hydrol 545:172–181

    Article  Google Scholar 

  • Maghrebi MF, Ball JE (2006) New method for estimation of discharge. J Hydraul Eng 132(10):1044–1051. https://doi.org/10.1061/(ASCE)0733-9429(2006)132:10(1044),1044-1051

    Article  Google Scholar 

  • Maghrebi MF, Kavousizadeh A, Maghrebi RF, Ahmadi A (2017) Stage–discharge estimation in straight compound channels using isovel contours. Hydrol Process 31:3859–3870. https://doi.org/10.1002/hyp.11299

    Article  Google Scholar 

  • Maghrebi MF (2003) Discharge estimation in flumes using a new technique for the production of isovel contours, In: Proceeding Int. Conf. Civ. Environ. Eng. ICCEE: pp. 147–156

  • Matgen P, Schumann G, Henry JB, Hoffmann L, Pfister L (2007) Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management. Int J Appl Earth Obs Geoinf 9(3):247–263

    Google Scholar 

  • McFeeters SK (1996) The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. Int J Remote Sens 17:1425–1432

    Article  Google Scholar 

  • Paris A, Paiva R, Silva J, Moreira M, Calmant S, Garambois P, Collischonn W, Bonnet M, Seyler F (2016) Stage-discharge rating curves based on satellite altimetry and modeled discharge in the Amazon Basin. Water Resour Res. https://doi.org/10.1002/2014WR016618

    Article  Google Scholar 

  • Schumann G, Bates PD, Horritt MS, Matgen P, Pappenberger F. (2009) Progress in integration of remote sensing–derived flood extent and stage data and hydraulic models. Rev Geophys, 47(4). https://doi.org/10.1029/2008RG000274.

  • Smith LC, Isacks B, Forster R, Bloom A, Preuss I (1995) Estimation of discharge from braided glacial rivers using ERS 1 synthetic aperture radar: first results. Water Resour Res 31(5):1325–1329

    Article  Google Scholar 

  • Smith LC, Isacks BL, Bloom AL, Murray AB (1996) Estimation of discharge from three braided rivers using synthetic aperture radar satellite imagery: Potential application to ungauged basins. Water Resour Res 32(7):2021–2034

    Article  Google Scholar 

  • Smith LC, Pavelsky TM (2008) Estimation of river discharge, propagation speed, and hydraulic geometry from space: Lena River, Siberia. Water Resour Res, 44(3) https://doi.org/10.1029/2007WR006133

  • Tarpanelli A, Brocca L, Lacava T, Melone F, Moramarco T, Faruolo M, Pergola N, Tramutoli V (2013) Toward the estimation of river discharge variations using MODIS data in ungauged basins. Remote Sens Environ 136:47–55. https://doi.org/10.1016/j.rse.2013.04.010

    Article  Google Scholar 

  • Tian H, Li W, Wu M, Huang N, Li G, Li X, Niu Z (2017) Dynamic Monitoring of the largest freshwater lake in china using a newwater index derived from high spatiotemporal resolution sentinel-1A data. Remote Sens 9(6):521. https://doi.org/10.3390/rs9060521

    Article  Google Scholar 

  • Xu H (2006) Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens 27(14):3025–3033

    Article  Google Scholar 

  • Xu K, Zhang J, Watanabe M, Sun C (2004) Estimating river discharge from very high-resolution satellite data: a case study in the Yangtze RiverChina. Hydrol Process 18(10):1927–1939. https://doi.org/10.1002/hyp.1458

    Article  Google Scholar 

  • Yen BC (2002) Open channel flow resistance. J Hydraul Eng 128(1):20–39. https://doi.org/10.1061/(ASCE)0733-9429(2002)128:1(20)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mahmoud F. Maghrebi.

Ethics declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Edited by Dr. Michael Nones (CO-EDITOR-IN-CHIEF).

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Farnoush, H., Maghrebi, M.F. Discharge estimation and rating curve derivation, using satellite geometry data and isovel contours at Karun River, Iran. Acta Geophys. 71, 2825–2838 (2023). https://doi.org/10.1007/s11600-022-00965-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11600-022-00965-7

Keywords

Navigation