Skip to main content
Log in

Developing a New Artificial Intelligence Framework to Estimate the Thalweg of Rivers

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

Hydrographic operations to investigate the riverbed form throughout the entire length of a river are costly and time-consuming. This has made scholars use a wide range of alternative methods to address the issue. In the present study, however, a new framework using Artificial Intelligence (AI) based models is introduced to identify the thalweg of rivers, which provides an accurate estimate of a river thalweg via linking coordinates of their left and right banks. In this regard, we trained and tested the performance of two AI-based models, including Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models. The database of two rivers, namely the Qinhe River in China and the Gaz River in Iran was used to help evaluate the developed model. Outcomes of the two investigated case studies demonstrated that the values of the statistical error estimators, including the Root Mean Square Error (RMSE) of the ANFIS model were less than those of the ANN model. As a result, the ANFIS model can lead to more accurate results than the ANN model, and it is suitable for cases with less available data. Moreover, comparing the results from the developed models with those of the River Channel Morphology Model (RCMM) showed that AI-based models outdo numerical approaches in the identification of the thalweg of rivers. All in all, it is inferred that the proposed approach not only helps us achieve an accurate geometry of rivers but reduces the side costs and can be used as an effective alternative to field operations. The applicability of the proposed models to different river systems is also discussed as a potential direction for future research.

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

The codes are readily available from the authors on request.

References

  • Afzali Ahmadabadi S, Jafari-Asl J, Banifakhr E, Houssein EH, Ben Seghier MEA (2023) Risk-Based Design Optimization of Contamination Detection Sensors in Water Distribution Systems: Application of an Improved Whale Optimization Algorithm. Water 15(12):2217

    Article  Google Scholar 

  • Babaei M, Roozbahani A, Shahdany SMH (2018) Risk Assessment of Agricultural Water Conveyance and Delivery Systems by Fuzzy Fault Tree Analysis Method. Water Resour Manag 32(12):4079–4101

    Article  Google Scholar 

  • Bailly du Bois P et al. (2012) In-Situ database toolbox for short-term dispersion model validation in macro-tidal seas, application for 2D-model. Continental Shelf Research, 36:63–82

  • Ben Seghier MEA, Corriea JA, Jafari-Asl J, Malekjafarian A, Plevris V, Trung NT (2021) On the modeling of the annual corrosion rate in main cables of suspension bridges using combined soft computing model and a novel nature-inspired algorithm. Neural Comput Appl 33(23):15969–15985

    Article  Google Scholar 

  • Colbo K, Ross T, Brown C, Weber T (2014) A review of oceanographic applications of water column data from multibeam echosounders. Estuar Coast Shelf Sci 145:41–56

    Article  Google Scholar 

  • Dey S, Saksena S, Merwade V (2019) Assessing the effect of different bathymetric models on hydraulic simulation of rivers in data sparse regions. J Hydrol 575:838–851

    Article  Google Scholar 

  • Dikshit A, Pradhan B, Alamri AM (2020) Temporal Hydrological Drought Index Forecasting for New South Wales. Australia Using Machine Learning Approaches. Atmosphere 11(6):585

    Google Scholar 

  • Ebtehaj I, Bonakdari H, Safari MJS, Gharabaghi B, Zaji AH, Madavar HR et al (2020) Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes. Int J Sediment Res 35(2):157–170

    Article  Google Scholar 

  • Hardy RJ, Bates PD, Anderson MG (1999) The importance of spatial resolution in hydraulic models for floodplain environments. J Hydrol 216(1–2):124–136

    Article  Google Scholar 

  • Intelmann SS (2006) Comments on hydrographic and topographic LIDAR acquisition and merging with multibeam sounding data acquired in the Olympic Coast National Marine Sanctuary

  • Jafari-Asl J, Azizyan G, Monfared SAH, Rashki M, Andrade-Campos AG (2021) An enhanced binary dragonfly algorithm based on a V-shaped transfer function for optimization of pump scheduling program in water supply systems (case study of Iran). Eng Fail Anal 123:105323

  • Jafari-Asl J, Seghier MEAB, Ohadi S, van Gelder P (2021) Efficient method using Whale Optimization Algorithm for reliability-based design optimization of labyrinth spillway. Applied Soft Computing 101:107036

    Article  Google Scholar 

  • Lai R, Wang M, Yang M, Zhang C (2018) Method based on the Laplace equations to reconstruct the river terrain for two-dimensional hydrodynamic numerical modeling. Comput Geosci 111:26–38

    Article  Google Scholar 

  • Langridge M, Gharabaghi B, McBean E, Bonakdari H, Walton R (2020) Understanding the dynamic nature of time-to-peak in UK Streams. J Hydrol 583:124630

  • Larson M (2005) Numerical Modeling. In: Schwartz, M.L. (eds) Encyclopedia of Coastal Science. Encyclopedia of Earth Science Series. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3880-1_232

  • Li J, Heap AD (2011) A review of comparative studies of spatial interpolation methods in environmental sciences: Performance and impact factors. Ecol Inform 6(3–4):228–241

    Article  Google Scholar 

  • Liu et al. (2018) Reduced resilience as a potential early warning signal of forest mortality ecological society of America annual meeting 5(10)

  • Mai SH, Ben Seghier ME, Nguyen PL, Jafari-Asl J, Thai DK (2020) A hybrid model for predicting the axial compression capacity of square concrete-filled steel tubular columns. Eng Comp 1–18

  • Merwade VM, Maidment DR, Hodges BR (2005) Geospatial representation of river channels. J Hydrol Eng 10(3):243–251

    Article  Google Scholar 

  • Modaresi et al. (2018) An approach for improving the accuracy of monthly streamflow forecasting. J Hydroinformatics 20(4):917–933

  • Nittrouer JA, Allison MA, Campanella R (2008) Evaluation of bedload transport in the lower Mississippi River: implications for sand transport to the Gulf of Mexico. J Geophys Res Earth Surf 113:F03004

  • Noori N, Kalin L (2016) Coupling SWAT and ANN models for enhanced daily streamflow prediction. J Hydrol Eng 533:141–151

    Article  Google Scholar 

  • Ohadi S, Jafari-Asl J (2021) Multi-objective reliability-based optimization for design of trapezoidal labyrinth weirs. Flow Meas Instrum 77:101787

  • Podhorányi M, Unucka J, Bobál’ P, Říhová V (2013) Effects of LIDAR DEM resolution in hydrodynamic modelling: model sensitivity for cross-sections. Int J Digit Earth 6(1):3–27

    Article  Google Scholar 

  • Quarteroni A, Quarteroni S (2009) Numerical models for differential problems, vol 2. Springer, Milan

    Book  Google Scholar 

  • Rahmanshahi M, Jafari-Asl J, Shafai Bejestan M, Mirjalili S (2023) A Hybrid Model for Predicting the Energy Dissipation on the Block Ramp Hydraulic Structures. Water Resources Management 37(8):3187–3209

    Article  Google Scholar 

  • Raber GT, Jensen JR, Hodgson ME, Tullis JA, Davis BA, Berglund J (2007) Impact of LiDAR nominal post-spacing on DEM accuracy and flood zone delineation. Photogramm Eng Remote Sensing 73(7):793–804

    Article  Google Scholar 

  • Rad et al. (2022) A Radial Basis Function Neural Network Approach to Predict Preschool Teachers’ Technology, Acceptance Behavior, Frontiers in Psychology 13:880753

  • Riahi-Madvar H, Dehghani M, Memarzadeh R, Gharabaghi B (2021) Short to long-term forecasting of river flows by heuristic optimization algorithms hybridized with ANFIS. Water Resour Manag 35(4):1149–1166

    Article  Google Scholar 

  • Seo Y, Kim S, Kisi O, Singh VP (2015) Daily water level forecasting using wavelet decomposition and artificial intelligence techniques. J Hydrol 520:224–243

    Article  Google Scholar 

  • Sharifi H, Roozbahani A, Hashemy Shahdany SM (2021) Evaluating the performance of agricultural water distribution systems using FIS, ANN and ANFIS intelligent models. Water Resour Manag 35(6):1797–1816

    Article  Google Scholar 

  • Vogel, Marker (2010) Revised Modelling of the Post-Ad 79 Volcanic Deposits of Somma-Vesuvius to Reconstruct the Pre-Ad 79 Topography of the Sarno River Plain 5–16

  • Walton R, Binns A, Bonakdari H, Ebtehaj I, Gharabaghi B (2019) Estimating 2-year flood flows using the generalized structure of the group method of data handling. J Hydrol 575:671–689

    Article  Google Scholar 

  • Yongfei Fu, Liu Yuyu, Shiguo Xu, Zhenghe Xu (2022) Assessment of a Multifunctional River Using Fuzzy Comprehensive Evaluation Model in Xiaoqing River, Eastern China. Int J Environ Res Public Health 19:12264

Download references

Funding

No funding was received.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by Zohre Aghamolaei and Masoud-Reza Hesami Kermani. Zohre Aghamolaei: Writing - original draft. Masoud Reza Hesami Kermani: Writing - original draft, Project administration.

Corresponding author

Correspondence to Masoud-Reza Hessami-Kermani.

Ethics declarations

Competing Interests

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

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Case study I:

Left

Talweg

Right

x

y

z

X

Y

Z

X

Y

Z

238607.47

3878357.49

824.23

238794.24

3878324.99

801.10

238954.52

3878297.10

834.39

238591.26

3878365.05

823.81

238802.93

3878359.96

805.34

238946.04

3878335.94

834.99

238575.04

3878372.61

824.00

238810.18

3878395.26

811.82

238928.31

3878372.47

837.59

238558.83

3878380.18

824.20

238815.96

3878430.82

822.03

238910.57

3878409.00

840.91

238542.62

3878387.74

824.79

238820.26

3878466.60

830.83

238892.83

3878445.53

841.80

238526.41

3878395.30

826.04

238823.08

3878502.52

836.73

238875.10

3878482.06

844.03

238510.19

3878402.86

826.64

238824.41

3878538.53

840.60

238863.97

3878521.07

843.98

238493.98

3878410.43

826.67

238824.25

3878574.56

842.98

238853.43

3878560.28

846.80

238477.77

3878417.99

826.48

238822.60

3878610.56

844.76

238842.88

3878599.50

849.88

238461.56

3878425.55

824.58

238819.46

3878646.46

841.70

238840.69

3878639.86

849.37

238445.34

3878433.11

822.69

238814.84

3878682.19

835.63

238840.27

3878680.47

843.39

238429.13

3878440.67

822.93

238808.74

3878717.71

831.82

238839.85

3878721.08

837.03

238412.92

3878448.24

823.58

238801.19

3878752.94

828.32

238839.43

3878761.69

831.91

238396.71

3878455.80

824.43

238792.18

3878787.83

823.13

238840.73

3878802.27

830.24

238380.49

3878463.36

825.51

238781.73

3878822.31

819.69

238829.53

3878840.23

830.97

238364.28

3878470.92

826.53

238769.87

3878856.34

819.67

238812.24

3878876.98

833.84

238348.07

3878478.48

827.18

238756.61

3878889.84

820.36

238794.96

3878913.73

838.47

238331.85

3878486.05

827.83

238741.98

3878922.77

821.73

238777.68

3878950.48

842.58

238315.64

3878493.61

827.03

238726.00

3878955.07

825.47

238758.63

3878986.10

850.55

238299.43

3878501.17

825.75

238704.56

3878983.83

828.33

238732.70

3879017.36

850.62

238281.57

3878512.31

824.14

238670.82

3879018.47

831.33

238693.46

3879051.44

852.56

238264.40

3878524.47

822.34

238632.37

3879047.82

832.54

238651.97

3879083.20

854.59

238247.36

3878536.83

820.96

238590.06

3879071.25

826.39

238610.48

3879114.96

849.58

238230.33

3878549.18

821.63

238544.79

3879088.25

824.52

238563.14

3879136.52

838.86

238213.29

3878561.54

819.38

238497.52

3879098.47

822.85

238514.79

3879156.33

837.01

238196.25

3878573.90

821.34

238449.26

3879101.68

823.55

238466.34

3879175.88

842.96

238179.21

3878586.25

823.77

238401.05

3879097.82

824.95

238417.18

3879193.56

853.34

238162.17

3878598.61

824.83

238353.92

3879086.97

823.85

238367.99

3879211.16

861.32

238145.14

3878610.96

824.28

238308.88

3879069.36

824.04

238317.02

3879222.65

857.35

238128.10

3878623.32

823.08

238266.88

3879045.37

829.22

238266.00

3879233.45

851.22

238111.06

3878635.68

821.66

238228.84

3879015.51

829.32

238213.90

3879229.61

844.74

238094.02

3878648.03

821.09

238193.73

3878982.23

827.29

238162.90

3879219.25

837.94

238076.98

3878660.39

821.07

238156.93

3878950.78

824.65

238112.80

3879204.57

837.40

238059.95

3878672.74

821.26

238119.37

3878920.25

822.00

238063.99

3879185.93

835.66

238039.72

3878675.23

820.07

238081.07

3878890.66

821.10

238015.18

3879167.30

835.38

238018.67

3878675.16

819.14

238042.05

3878862.02

820.62

237966.66

3879147.95

836.37

237997.63

3878675.10

818.60

238002.33

3878834.34

820.78

237918.51

3879127.65

836.08

237976.58

3878675.03

818.14

237961.95

3878807.66

821.93

237870.37

3879107.35

830.96

237955.53

3878674.96

817.59

237920.92

3878781.97

821.43

237822.22

3879087.06

825.83

237923.82

3878674.87

818.10

237894.31

3878766.06

821.09

237806.35

3879086.11

825.03

237892.90

3878669.26

819.40

237867.21

3878750.99

820.12

237790.48

3879085.16

824.48

237862.42

3878660.48

819.57

237839.90

3878736.31

822.96

237774.61

3879084.21

825.34

237831.95

3878651.69

819.04

237812.58

3878721.62

821.44

237758.74

3879083.26

826.19

237801.48

3878642.91

821.33

237785.27

3878706.94

821.00

237742.88

3879082.30

826.12

237771.01

3878634.12

822.15

237757.96

3878692.25

821.55

237727.01

3879081.35

825.90

237740.54

3878625.34

821.66

237730.65

3878677.57

821.37

237711.14

3879080.40

825.53

237710.07

3878616.55

820.28

237703.34

3878662.89

819.11

237695.27

3879079.45

824.33

237679.01

3878610.16

819.38

237676.03

3878648.20

817.55

237679.66

3879081.18

823.02

237647.91

3878603.99

818.52

237648.10

3878634.77

819.78

237664.28

3879085.22

822.33

237616.80

3878597.81

818.82

237619.20

3878623.55

820.24

237648.91

3879089.26

821.70

237585.70

3878591.63

819.16

237589.62

3878614.26

820.62

237633.53

3879093.30

821.48

237554.59

3878585.46

819.15

237559.49

3878606.96

820.43

237618.16

3879097.34

822.18

237523.49

3878579.28

819.36

237528.94

3878601.66

819.99

237602.78

3879101.38

823.03

237492.38

3878573.10

818.38

237498.11

3878598.39

819.20

237587.40

3879105.42

825.43

237461.28

3878566.93

817.23

237467.13

3878597.16

817.30

237572.03

3879109.46

827.76

237430.25

3878570.56

817.92

237436.14

3878597.99

816.44

237556.65

3879113.51

828.62

237399.24

3878577.21

819.23

237405.27

3878600.86

817.22

237541.27

3879117.55

827.55

237368.23

3878583.87

819.99

237374.65

3878605.76

817.84

237525.90

3879121.59

826.06

237332.64

3878591.16

820.11

237338.48

3878614.29

818.56

237509.81

3879125.81

824.10

237297.04

3878598.46

819.35

237303.10

3878625.66

819.00

237493.72

3879130.04

822.12

237262.88

3878610.23

818.78

237268.73

3878639.80

818.28

237477.64

3879134.27

821.35

237229.73

3878625.11

818.64

237235.59

3878656.61

818.44

237461.55

3879138.50

821.46

237196.58

3878640.00

821.03

237209.04

3878679.89

819.84

237445.46

3879142.73

821.28

237163.43

3878654.88

823.81

237199.14

3878715.72

820.62

237429.37

3879146.95

821.27

237130.28

3878669.77

825.22

237190.98

3878751.98

822.19

237413.29

3879151.18

821.38

237097.13

3878684.65

826.16

237184.61

3878788.60

820.98

237399.20

3879158.70

821.27

237064.32

3878700.15

831.14

237180.01

3878825.48

818.52

237388.02

3879171.02

821.30

237034.21

3878720.50

827.97

237177.22

3878862.55

812.35

237376.84

3879183.34

821.11

237004.10

3878740.84

826.10

237176.40

3878899.69

804.77

237365.66

3879195.65

821.18

236973.99

3878761.19

825.95

237180.03

3878936.68

802.28

237354.48

3879207.97

821.47

236943.88

3878781.54

825.94

237181.33

3878973.83

803.50

237343.30

3879220.29

822.13

236913.78

3878801.88

825.38

237180.30

3879010.98

809.14

237332.12

3879232.60

822.95

236883.67

3878822.23

826.40

237176.96

3879048.00

812.83

237320.94

3879244.92

823.31

236853.56

3878842.57

829.38

237171.30

3879084.73

815.18

237309.76

3879257.24

823.66

236824.95

3878864.82

830.15

237163.35

3879121.04

817.76

237298.58

3879269.55

824.01

236798.09

3878889.30

827.93

237141.86

3879148.46

819.68

237289.07

3879283.11

824.10

236771.23

3878913.78

825.69

237111.77

3879170.27

822.40

237280.53

3879297.38

824.78

236756.40

3878927.30

825.39

237101.09

3879178.52

823.61

237275.60

3879305.63

825.47

236741.56

3878940.81

824.82

237090.55

3879186.95

825.21

237270.67

3879313.88

825.56

236726.73

3878954.33

824.92

237080.15

3879195.55

826.80

237265.74

3879322.13

825.57

236711.89

3878967.85

824.84

237069.90

3879204.32

828.37

237260.80

3879330.37

825.70

236697.06

3878981.37

824.55

237059.79

3879213.25

828.82

237255.87

3879338.62

825.22

236682.22

3878994.89

824.40

237049.83

3879222.35

827.84

237250.94

3879346.87

825.73

236667.39

3879008.41

824.89

237040.02

3879231.62

826.86

237246.00

3879355.12

826.15

236652.56

3879021.93

825.38

237030.36

3879241.04

825.86

237241.07

3879363.37

825.29

236637.72

3879035.44

824.02

237020.86

3879250.63

824.66

237236.14

3879371.61

824.71

236622.89

3879048.96

822.32

237011.52

3879260.36

823.64

237231.20

3879379.86

824.28

236608.05

3879062.48

820.90

237002.34

3879270.25

822.64

237226.27

3879388.11

823.85

236593.22

3879076.00

821.36

236993.32

3879280.29

821.64

237221.34

3879396.36

823.42

236578.39

3879089.52

821.80

236984.47

3879290.48

820.80

237216.40

3879404.61

822.83

236563.55

3879103.04

821.72

236975.79

3879300.81

820.04

237211.47

3879412.85

822.81

236550.11

3879117.74

820.98

236967.28

3879311.28

819.27

237206.54

3879421.10

823.03

236539.22

3879134.59

820.25

236958.95

3879321.89

818.49

237201.61

3879429.35

823.25

236528.33

3879151.45

820.58

236950.79

3879332.64

817.83

237196.67

3879437.60

823.46

236517.44

3879168.31

820.90

236942.80

3879343.52

817.67

237191.74

3879445.85

823.51

236508.43

3879185.85

821.63

236935.00

3879354.53

817.36

237186.81

3879454.09

823.30

236498.28

3879266.27

821.23

236881.97

3879441.80

817.82

237142.55

3879533.61

822.40

236488.14

3879346.69

821.90

236840.20

3879534.98

816.35

237142.55

3879625.36

818.61

236477.99

3879427.11

822.59

236810.33

3879632.64

820.78

237142.43

3879717.10

826.62

236467.85

3879507.53

823.00

236792.84

3879733.25

819.39

237134.65

3879807.80

826.66

236457.70

3879587.95

824.74

236787.98

3879835.26

819.43

237104.64

3879894.50

824.00

236447.55

3879668.37

819.28

236795.84

3879937.07

819.85

237074.64

3879981.20

820.13

236443.84

3879749.32

815.33

236816.30

3880037.12

823.10

237044.63

3880067.90

825.16

236440.53

3879830.31

823.90

236849.03

3880133.86

821.11

237014.62

3880154.60

824.49

236437.22

3879911.30

824.47

236861.82

3880234.23

815.90

236987.30

3880242.17

816.60

236433.90

3879992.29

819.77

236867.49

3880336.26

830.57

236961.15

3880330.11

824.15

236430.59

3880073.28

813.44

236873.95

3880438.17

837.13

236935.01

3880418.05

829.97

236420.57

3880153.12

817.91

236840.62

3880533.06

827.55

236908.86

3880505.99

827.90

236396.78

3880230.60

817.30

236758.50

3880591.11

814.17

236875.72

3880590.77

834.95

236372.98

3880308.09

819.45

236657.93

3880590.86

818.88

236826.87

3880668.43

827.37

236349.18

3880385.57

826.33

236564.28

3880550.92

825.70

236778.02

3880746.08

833.31

236312.03

3880457.54

827.75

236463.19

3880539.14

821.00

236728.87

3880823.54

831.76

236274.20

3880529.23

820.84

236363.34

3880558.84

824.41

236674.79

3880897.65

835.14

236236.37

3880600.92

820.39

236274.29

3880608.12

823.53

236620.71

3880971.77

836.65

236184.88

3880662.49

822.60

236204.57

3880682.26

823.44

236566.63

3881045.88

830.64

Cas study II:

Left

Talweg

Right

x

y

z

x

y

z

x

y

z

513069.80

2924874.00

6.61

513092.00

2924909.00

1.97

513107.10

2924929.00

5.73

513062.69

2924878.00

6.70

513086.31

2924911.00

2.02

513102.05

2924931.00

5.72

513052.58

2924883.00

6.82

513080.47

2924913.00

2.08

513097.20

2924932.00

5.72

513045.00

2924887.00

6.91

513074.84

2924914.00

2.13

513089.98

2924934.00

5.71

513040.50

2924892.00

7.04

513070.00

2924916.00

2.18

513083.80

2924936.00

5.70

513035.60

2924897.00

7.18

513064.31

2924917.00

1.93

513077.14

2924938.00

5.69

513032.68

2924900.00

7.22

513057.90

2924919.00

1.66

513070.50

2924939.00

5.68

513028.79

2924905.00

7.26

513051.65

2924923.00

2.08

513065.25

2924944.00

5.69

513025.80

2924908.00

7.30

513046.52

2924926.00

2.41

513059.50

2924949.00

5.69

513022.25

2924912.00

7.24

513041.70

2924929.00

2.73

513052.84

2924954.00

5.70

513016.70

2924917.00

7.15

513037.10

2924932.00

3.03

513047.30

2924959.00

5.70

513012.95

2924921.00

7.01

513032.26

2924935.00

2.54

513041.10

2924964.00

5.71

513008.71

2924926.00

6.86

513027.99

2924938.00

2.11

513035.90

2924969.00

5.71

513002.30

2924933.00

6.64

513020.50

2924943.00

1.35

513030.06

2924974.00

5.72

512998.58

2924936.00

6.65

513013.89

2924949.00

2.41

513024.00

2924979.00

5.72

512993.31

2924941.00

6.68

513007.70

2924955.00

3.40

513019.97

2924982.00

5.72

512989.30

2924944.00

6.70

513000.99

2924962.00

2.61

513015.70

2924986.00

5.72

512983.97

2924948.00

6.67

512994.90

2924968.00

1.89

513011.64

2924989.00

5.73

512978.24

2924953.00

6.63

512992.19

2924971.00

1.86

513008.13

2924992.00

5.74

512973.10

2924957.00

6.59

512987.51

2924972.00

2.28

513006.90

2924993.00

5.74

512969.19

2924960.00

6.60

512986.27

2924976.00

1.79

513003.80

2924996.00

5.75

512966.01

2924963.00

6.60

512983.40

2924979.00

1.75

512999.79

2924999.00

5.72

512963.19

2924965.00

6.60

512980.99

2924983.00

1.91

512996.99

2925002.00

5.71

512960.36

2924967.00

6.60

512979.10

2924986.00

2.03

512993.19

2925005.00

5.69

512957.27

2924970.00

6.61

512973.01

2924989.00

1.95

512988.20

2925009.00

5.66

512954.40

2924972.00

6.61

512967.30

2924991.00

1.88

512985.01

2925012.00

5.64

512950.38

2924975.00

6.61

512962.82

2924994.00

1.87

512979.95

2925016.00

5.61

512947.99

2924977.00

6.61

512958.70

2924996.00

1.86

512974.50

2925021.00

5.58

512943.78

2924981.00

6.62

512954.00

2924999.00

1.94

512968.94

2925026.00

5.60

512940.20

2924984.00

6.62

512952.33

2925004.00

1.72

512965.94

2925028.00

5.61

512936.00

2924987.00

6.58

512950.40

2925010.00

1.47

512962.90

2925031.00

5.61

512930.35

2924992.00

6.53

512944.60

2925012.00

1.65

512960.40

2925033.00

5.62

512927.51

2924994.00

6.51

512939.77

2925014.00

1.78

512956.79

2925036.00

5.64

512924.60

2924996.00

6.48

512935.40

2925016.00

1.89

512952.40

2925040.00

5.65

512920.41

2924999.00

6.44

512930.70

2925018.00

2.01

512950.24

2925042.00

5.66

512916.12

2925002.00

6.41

512932.10

2925023.00

1.98

512947.99

2925044.00

5.67

512912.50

2925005.00

6.37

512928.90

2925027.00

1.88

512945.17

2925046.00

5.68

512908.42

2925008.00

6.35

512926.52

2925030.00

1.81

512942.51

2925048.00

5.69

512905.10

2925011.00

6.33

512924.42

2925032.00

1.74

512941.24

2925049.00

5.70

512902.34

2925013.00

6.33

512922.60

2925034.00

1.68

512937.10

2925053.00

5.71

512899.81

2925015.00

6.33

512919.34

2925037.00

1.70

512935.46

2925056.00

5.70

512896.70

2925017.00

6.33

512916.90

2925040.00

1.71

512934.17

2925058.00

5.70

512893.20

2925019.00

6.32

512912.50

2925043.00

1.70

512932.69

2925060.00

5.69

512889.65

2925024.00

6.30

512907.90

2925047.00

1.68

512931.01

2925063.00

5.68

512887.30

2925027.00

6.29

512904.01

2925050.00

1.68

512929.20

2925066.00

5.67

512883.79

2925031.00

6.29

512901.75

2925051.00

1.68

512926.68

2925070.00

5.65

512880.70

2925035.00

6.30

512898.75

2925053.00

1.68

512923.55

2925075.00

5.63

512878.33

2925038.00

6.30

512895.20

2925056.00

1.68

512920.39

2925080.00

5.61

512875.40

2925042.00

6.32

512890.66

2925059.00

1.78

512917.90

2925084.00

5.60

512872.17

2925046.00

6.31

512886.20

2925061.00

1.88

512915.48

2925088.00

5.58

512868.71

2925050.00

6.30

512883.53

2925065.00

2.04

512913.70

2925091.00

5.57

512865.90

2925054.00

6.29

512880.50

2925069.00

2.22

512911.62

2925095.00

5.55

512862.24

2925059.00

6.26

512875.15

2925071.00

2.11

512908.87

2925099.00

5.52

512860.20

2925066.00

6.00

512868.90

2925073.00

1.97

512906.70

2925103.00

5.50

512853.57

2925069.00

6.21

512865.53

2925077.00

2.44

512903.89

2925108.00

5.50

512850.40

2925073.00

6.21

512862.30

2925081.00

2.88

512901.45

2925112.00

5.51

512846.98

2925078.00

6.20

512858.87

2925085.00

2.69

512899.40

2925115.00

5.51

512844.80

2925081.00

6.20

512855.34

2925089.00

2.49

512897.68

2925118.00

5.51

512841.29

2925086.00

6.19

512852.70

2925092.00

2.34

512894.75

2925123.00

5.52

512837.17

2925092.00

6.18

512849.58

2925096.00

2.20

512891.80

2925128.00

5.52

512833.90

2925097.00

6.18

512846.15

2925100.00

2.04

512890.40

2925130.00

5.52

512830.03

2925102.00

6.17

512843.30

2925104.00

1.91

512888.69

2925136.00

5.50

512826.10

2925108.00

6.15

512839.96

2925108.00

2.12

512886.80

2925142.00

5.48

512823.44

2925114.00

6.12

512836.00

2925113.00

2.38

512884.90

2925149.00

5.46

512821.50

2925119.00

6.10

512831.50

2925118.00

1.73

512882.69

2925156.00

5.45

512817.22

2925129.00

5.65

512828.60

2925126.00

1.94

512880.90

2925162.00

5.43

512814.50

2925136.00

5.37

512825.60

2925134.00

2.08

512878.96

2925168.00

5.42

512812.19

2925142.00

4.81

512825.60

2925142.00

1.94

512877.96

2925172.00

5.42

512809.90

2925147.00

4.25

512825.60

2925148.00

1.82

512876.70

2925176.00

5.41

512807.30

2925156.00

3.93

512825.60

2925159.00

1.63

512875.78

2925179.00

5.41

512804.35

2925164.00

4.02

512821.60

2925167.00

1.67

512874.52

2925184.00

5.40

512802.69

2925168.00

4.07

512819.84

2925171.00

1.69

512873.20

2925189.00

5.39

512800.80

2925173.00

4.13

512817.50

2925176.00

1.71

512871.40

2925195.00

5.38

512800.30

2925181.00

4.29

512815.50

2925186.00

2.10

512870.99

2925198.00

5.38

512798.65

2925187.00

4.45

512813.81

2925193.00

2.41

512870.47

2925202.00

5.37

512797.11

2925193.00

4.61

512812.70

2925198.00

2.61

512869.70

2925207.00

5.37

512795.70

2925198.00

4.75

512812.09

2925201.00

2.52

512869.47

2925208.73

5.37

512794.45

2925203.00

4.89

512810.70

2925207.00

2.30

512869.08

2925212.00

5.36

512792.90

2925209.00

5.07

512809.95

2925215.00

2.51

512868.60

2925216.00

5.36

512791.91

2925213.00

5.19

512809.30

2925221.00

2.69

512867.90

2925221.00

5.36

512790.79

2925218.00

5.32

512808.61

2925228.00

2.56

512867.10

2925226.00

5.35

512789.90

2925222.00

5.42

512807.94

2925234.00

2.42

512866.46

2925231.00

5.37

512788.52

2925228.00

5.50

512807.40

2925239.00

2.31

512866.11

2925234.00

5.38

512787.18

2925233.00

5.58

512806.77

2925245.00

2.02

512865.70

2925237.00

5.39

512785.85

2925238.00

5.65

512806.20

2925251.00

1.75

512868.30

2925241.00

5.39

512784.74

2925243.00

5.72

512805.80

2925255.00

1.58

512871.00

2925246.00

5.39

512783.70

2925247.00

5.78

512805.80

2925261.00

1.77

512873.19

2925250.00

5.35

512782.25

2925253.00

5.82

512805.80

2925267.00

1.95

512875.20

2925254.00

5.32

512780.80

2925259.00

5.85

512805.80

2925271.00

2.08

512877.81

2925259.00

5.28

512779.23

2925266.00

5.89

512805.80

2925275.00

2.18

512880.54

2925264.00

5.23

512777.63

2925272.00

5.94

512805.50

2925277.00

2.29

512882.80

2925268.00

5.19

512776.10

2925279.00

5.97

512804.20

2925285.00

1.83

512885.90

2925273.00

5.15

512779.30

2925290.00

5.98

512803.30

2925291.00

1.84

512888.07

2925277.00

5.11

512781.01

2925296.00

5.98

512803.67

2925296.00

1.82

512890.00

2925280.00

5.08

512782.69

2925302.00

5.99

512804.00

2925300.00

1.80

512891.51

2925283.00

5.06

512784.10

2925307.00

5.99

512804.28

2925303.00

1.77

512892.92

2925285.00

5.03

512785.96

2925313.00

6.02

512804.73

2925307.00

1.72

512893.80

2925287.00

5.01

512787.91

2925320.00

6.06

512805.20

2925312.00

1.67

512896.11

2925288.00

5.02

512789.70

2925326.00

6.09

512805.75

2925316.00

1.63

512898.74

2925290.00

5.02

512792.00

2925334.00

5.96

512806.30

2925321.00

1.58

512900.99

2925291.00

5.03

512797.33

2925340.00

5.95

512808.36

2925325.00

2.10

512903.07

2925292.00

5.03

512800.07

2925343.00

5.94

512809.95

2925327.00

2.50

512905.30

2925293.00

5.04

512803.42

2925346.00

5.94

512813.20

2925333.00

3.32

512907.28

2925294.00

5.04

512806.90

2925350.00

5.93

512816.20

2925338.00

2.71

512910.20

2925295.00

5.05

512811.86

2925355.00

5.95

512818.20

2925342.00

2.30

512912.11

2925296.00

5.05

512813.50

2925357.00

5.96

512820.10

2925345.00

1.92

512913.64

2925297.00

5.05

512815.94

2925359.00

5.97

512827.05

2925348.00

2.00

512916.05

2925298.00

5.04

512818.08

2925362.00

5.97

512832.80

2925350.00

2.07

512917.19

2925299.00

5.04

512821.20

2925365.00

5.98

512837.57

2925352.00

2.21

512919.90

2925300.00

5.04

512825.20

2925369.00

5.99

512843.70

2925354.00

2.39

512921.89

2925301.00

5.03

512827.17

2925371.00

6.00

512850.37

2925357.00

2.03

512923.81

2925302.00

5.03

512831.90

2925376.00

6.01

512854.70

2925359.00

1.79

512926.60

2925303.00

5.02

512836.37

2925381.00

6.01

512863.40

2925360.00

1.74

512930.03

2925304.00

5.01

512838.44

2925383.00

6.02

512867.71

2925360.00

1.79

512933.00

2925305.00

5.00

512841.50

2925386.00

6.02

512872.10

2925361.00

1.83

512935.82

2925306.32

4.99

512848.10

2925388.00

6.04

512882.50

2925358.00

1.92

512937.70

2925307.00

4.98

512854.30

2925390.00

6.03

512890.90

2925356.00

2.10

512940.98

2925308.00

4.97

512857.80

2925390.00

6.03

512892.90

2925355.00

2.14

512944.85

2925309.00

4.96

512866.90

2925391.00

6.00

512898.50

2925353.00

2.17

512947.70

2925310.00

4.95

512873.40

2925394.00

6.01

512903.10

2925352.00

2.14

512953.90

2925312.00

4.67

512881.05

2925396.00

6.00

512911.40

2925349.00

2.09

512958.00

2925313.00

4.49

512886.60

2925397.00

5.99

512913.30

2925348.00

2.02

512961.70

2925314.00

4.32

512891.00

2925398.00

6.00

512917.60

2925349.00

2.13

512968.35

2925316.00

3.95

512894.44

2925399.00

6.01

512922.60

2925351.00

2.14

512972.40

2925318.00

3.73

512898.20

2925400.00

6.02

512931.80

2925354.00

2.25

512975.82

2925319.00

3.54

512908.40

2925398.00

6.13

512941.10

2925351.00

2.40

512979.17

2925320.00

3.35

512920.14

2925396.00

6.10

512951.30

2925348.00

2.58

512983.45

2925321.00

3.11

512931.22

2925395.00

6.08

512964.20

2925343.00

2.69

512986.40

2925322.00

2.95

512937.30

2925394.00

6.07

512970.90

2925341.00

2.51

512988.61

2925323.00

2.91

512952.20

2925391.00

6.10

512979.70

2925338.00

2.36

512992.21

2925324.00

2.85

512966.90

2925389.00

6.16

512984.90

2925339.00

1.94

512995.50

2925325.00

2.79

512984.11

2925387.00

6.16

512990.00

2925340.00

1.70

512997.39

2925326.00

2.84

512988.10

2925386.00

6.16

512994.50

2925343.00

1.50

513000.48

2925327.00

2.93

512991.50

2925385.00

6.17

512998.90

2925346.00

1.32

513002.80

2925328.00

2.99

512999.48

2925388.00

6.15

513008.20

2925349.00

1.57

513008.10

2925329.00

3.13

513004.20

2925389.00

6.14

513017.54

2925352.00

1.97

513016.19

2925330.00

3.39

513011.91

2925391.00

6.15

513025.10

2925355.00

2.30

513021.70

2925331.00

3.57

513019.68

2925393.00

6.15

513033.30

2925359.00

2.81

513028.12

2925332.00

3.78

513025.80

2925395.00

6.16

513040.40

2925362.00

3.03

513031.70

2925332.00

3.90

513032.46

2925397.00

6.18

513046.30

2925364.00

3.21

513036.98

2925333.00

4.07

513039.78

2925399.00

6.20

513053.10

2925367.00

1.36

513041.29

2925333.00

4.21

513045.20

2925400.00

6.21

513057.80

2925370.00

1.51

513048.20

2925334.00

4.43

513053.37

2925402.00

6.21

513062.00

2925374.00

1.65

513055.40

2925335.00

4.67

513060.20

2925404.00

6.21

513070.90

2925380.00

1.94

513062.70

2925336.00

4.90

513067.62

2925407.00

6.19

513077.90

2925380.00

1.75

513069.39

2925337.00

5.01

513073.39

2925409.00

6.17

513084.80

2925380.00

1.97

513078.00

2925338.00

5.15

513077.00

2925410.00

6.16

513095.10

2925386.00

1.56

513085.06

2925339.00

5.17

513090.50

2925415.00

6.12

513101.30

2925389.00

1.51

513092.60

2925340.00

5.20

513097.80

2925417.00

6.04

513107.72

2925393.00

1.60

513107.60

2925342.00

5.10

513104.73

2925420.00

5.96

513112.90

2925397.00

1.67

513115.70

2925343.00

5.08

513110.89

2925422.00

5.89

513115.10

2925398.00

1.62

513129.80

2925344.00

5.06

513115.20

2925423.00

5.85

513121.10

2925401.00

1.96

513139.20

2925346.00

5.05

513120.80

2925425.00

5.76

513127.20

2925404.00

2.30

513142.34

2925346.00

5.05

513128.80

2925427.00

5.93

513134.20

2925401.00

2.32

513147.68

2925347.00

5.05

513134.60

2925429.00

6.05

513141.20

2925397.00

2.26

513153.54

2925348.00

5.04

513141.65

2925431.00

6.09

513149.90

2925401.00

2.50

513157.18

2925348.00

5.04

513151.68

2925433.00

6.14

513157.30

2925405.00

2.60

513161.30

2925349.00

5.04

513156.20

2925434.00

6.17

513162.96

2925407.00

2.08

513165.82

2925350.00

5.03

513163.69

2925436.00

6.13

513166.50

2925409.00

1.76

513170.16

2925350.00

5.03

513172.99

2925438.00

6.09

513175.00

2925406.00

1.62

513172.81

2925351.00

5.03

513178.00

2925439.00

6.07

513183.50

2925403.00

1.61

513176.10

2925351.00

5.02

513184.10

2925441.00

5.91

513189.90

2925403.00

1.54

513180.40

2925350.00

5.01

513190.63

2925441.00

5.82

513197.10

2925404.00

1.45

513184.37

2925349.00

4.99

513197.80

2925440.00

5.72

513205.70

2925404.00

1.38

513187.80

2925348.00

4.98

513211.50

2925439.00

5.81

513212.67

2925405.00

1.39

513194.90

2925347.00

4.96

513220.16

2925438.00

5.88

513217.40

2925406.00

1.40

513201.86

2925345.00

4.95

513228.30

2925438.00

5.93

513224.70

2925407.00

1.37

513208.06

2925344.00

4.94

513239.40

2925437.00

5.95

513230.90

2925408.00

1.34

513213.40

2925343.00

4.92

513245.97

2925437.00

5.93

513234.90

2925405.00

1.61

513217.79

2925342.00

4.91

513253.90

2925436.00

5.91

513241.20

2925400.00

1.65

513222.60

2925341.00

4.90

513258.57

2925434.00

5.93

513245.40

2925397.00

1.68

513226.34

2925340.00

4.90

513264.70

2925431.00

5.94

513250.84

2925396.00

1.56

513228.63

2925340.00

4.89

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

Aghamolaei, Z., Hessami-Kermani, MR. Developing a New Artificial Intelligence Framework to Estimate the Thalweg of Rivers. Water Resour Manage 37, 5893–5917 (2023). https://doi.org/10.1007/s11269-023-03632-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-023-03632-8

Keywords

Navigation