Abstract
The impact of climate change on rainfall patterns and intensity necessitates an accurate estimation of runoff from rainfall to effectively manage water resources. This study utilized the MIKE HYDRO River software to evaluate rainfall-runoff in the upper Vaigai sub-basin. Input parameters, including rainfall, evaporation, and stream discharge data, were collected over a period of 16 years from 2000 to 2015. The auto-calibration capabilities of the software were employed to calibrate the model from 2000 to 2010, which was validated using data sets collected from 2011 to 2015. The optimal model and operating parameters were determined, and hydrographs were compared for simulated and observed runoff. The reliability and accuracy of the MIKE HYDRO River model were assessed using various goodness-of-fit indicators, including the coefficient of determination (R2), root-mean-square error (RMSE), and index of agreement. The R2 values demonstrated a strong correlation of 0.79 and 0.87 with the observed and simulated runoff for the calibration and validation period, respectively. The attainment of an RMSE of 4.05 m3/s and 2.20 m3/s and an index of agreement of 0.93 and 0.96 during the calibration and validation period, respectively, confirmed the model’s excellent performance. The results of the rainfall-runoff simulation indicate that the MIKE HYDRO River tool is suitable for rainfall-runoff studies and integrated water supply management in the upper Vaigai.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
All data generated or analysed during this study are included in the manuscript.
References
Agrawal N, Desmukh TS (2016) Rainfall runoff modeling using MIKE 11 Nam – a review. Int J Innov Sci Eng Technol 3:659–667
Aredo MR, Hatiye SD, Pingale SM (2021) Modeling the rainfall runoff using MIKE 11 NAM model in Shaya catchment, Ethiopia. Model Earth Syst Environ 7:2545–2551. https://doi.org/10.1007/s40808-020-01054-8
Balaji G, Thirumaran K (2019) Evaluating the impact of urbanization on the physiochemical parameters of the urban river system: a study on Vaigai River, Madurai. Environ Urban ASIA 10:116–131. https://doi.org/10.1177/0975425318822337
CGWB (2007) Ministry of Water Resources, Government of India. http://cgwb.gov.in/documents/Manual%20on%20Artificial%20Recharge%20of%20Ground%20Water.pdf. Accessed 21 Jun 2012
Chellasamy R (1996) Hydrogeological studies in the Vaigai River basin Tamil Nadu. Thesis submitted to the Manonmaniam Sundaranar University for the award of degree of Doctor of Philosophy. pp 1-239.
COLUMBIA GSAPP (2016) Water urbanism: Madurai. Global Cities & Climate Change, India. https://www.arch.columbia.edu/books/reader/192-water-urbanism-madurai-india. Accessed 24 Dec 2024
Cosgrove WJ, Loucks DP (2015) Water management: current and future challenges and research directions. Water Resour Res 51(6):4823–4839. https://doi.org/10.1029/eo066i003p00017-03
DHI (2016) MIKE, Powered by DHI. 2016, 120. https://www.mikepoweredbydhi.com/. Accessed 2 Oct 2022
DHI (2017) MIKE HYDRO River User Guide 2017. DHI, Hørsholm, Denmark, pp 1–216
Dhote PR, Aggarwal SP, Thakur PK, Garg V (2019) Flood inundation prediction for extreme flood events: a case study of Tirthan River, North West Himalaya. Himal Geol 40:128–140
Doulgeris C, Georgiou P, Papadimos D, Papamichail D (2011) Evaluating three different model setups in the MIKE 11 NAM model. Springer eBooks, pp 241–249. https://doi.org/10.1007/978-3-642-19902-8_28
Doulgeris C, Georgiou P, Papadimos D, Papamichail D (2012) Ecosystem approach to water resources management using the MIKE 11 modeling system in the Strymonas River and Lake Kerkini. J Environ Manag 94:132–143. https://doi.org/10.1016/j.jenvman.2011.06.023
Ghosh A, Roy MB, Roy PK (2022) Evaluating the performance of MIKE NAM model on rainfall-runoff in lower Gangetic floodplain, West Bengal, India. Model Earth Syst Environ 8:4001–4017. https://doi.org/10.1007/s40808-021-01347-6
Ha DTT, Ghafouri-Azar M, Bae D-H (2019) Long-term variation of runoff coefficient during dry and wet seasons due to climate change. Water 11:2411. https://doi.org/10.3390/w11112411
Hafezparast M, Araghinejad S, Fatemi SE, Bressers H (2013) A conceptual rainfall-runoff model using the auto calibrated NAM models in the Sarisoo River. Hydrol Curr Res 4:148. https://doi.org/10.4172/2157-7587.1000148
Jahandideh-Tehrani M, Helfer F, Zhang H, Hong Z, Jenkins G, Yu Y (2020) Hydrodynamic modelling of a flood-prone tidal river using the 1D model MIKE HYDRO River: calibration and sensitivity analysis. Environ Monit Assess 192:97. https://doi.org/10.1007/s10661-019-8049-0
Jajarmizadeh M, Harun S, Abdullah R, Salarpour M (2012a) Using soil and water assessment tool for flow simulation and assessment of sensitive parameters applying SUFI-2 algorithm. Caspian J Applied Sci Res 2:37–44
Jajarmizadeh M, Harun S, Salarpour M (2012b) A review on theoretical consideration and types of models in hydrology. J Eng Sci Tech 5:249–261
Kaliraj S, Chandrasekar N, Magesh NS (2014) Identification of potential groundwater recharge zones in Vaigai upper basin, Tamil Nadu, using GIS-based analytical hierarchical process (AHP) technique. Arab J Geosci 7:1385–1401. https://doi.org/10.1007/s12517-013-0849-x
Kaliraj S, Chandrasekar N, Magesh NS (2015) Evaluation of multiple environmental factors for site-specific groundwater recharge structures in the Vaigai River upper basin, Tamil Nadu, India, using GIS-based weighted overlay analysis. Environ Earth Sci 74:4355–4380. https://doi.org/10.1007/s12665-015-4384-9
Kaltofen M, Muller F, Zabel A (2017) Application of MIKE basin in the Zayandeh Rud Catchment. In: Mohajeri S, Horlemann L (eds) Reviving the dying Giant. Springer, Cham, pp 253–268. https://doi.org/10.1007/978-3-319-54922-4_16
Kumar P, Lohani AK, Nema AK (2019) Rainfall runoff modeling using MIKE 11 NAM model. Current World. Environment 14:27–36. https://doi.org/10.12944/cwe.14.1.05
Lafdani EK, Nia AM, Pahlavanravi A, Ahmadi A, Jajarmizadeh M (2013) Daily rainfall-runoff prediction and simulation using ANN, ANFIS and conceptual hydrological MIKE11/NAM models. Inter J Engg Tech 1:32–50
Lv Z, Zuo J, Rodriguez D (2020) Predicting of runoff using an optimized SWAT-ANN: a case study. J Hydrol Reg Stud 29:100688. https://doi.org/10.1016/j.ejrh.2020.100688
Madsen H, Wilson G, Ammentorp HC (2002) Comparison of different automated strategies for calibration of rainfall-runoff models. J Hydrol 261(1-4):48–59. https://doi.org/10.1016/S0022-1694(01)00619-9
Makungo R, Odiyo JO, Ndiritu JG, Mwaka B (2010) Rainfall-runoff modelling approach for ungauged catchments: a case study of Nzhelele River sub-quaternary catchment. Phys Chem Earth 35:596–607. https://doi.org/10.1016/j.pce.2010.08.001
Mialhe F, Gunnell Y, Mering C (2008) Synoptic assessment of water resource variability in reservoirs by remote sensing general approach and application to the runoff harvesting systems of south India. Water Resour Res 44:W05411. https://doi.org/10.1029/2007WR006065
Nagalapalli S, Kundu A, Mall RK, Thattai D, Rangarajan S (2019) An appraisal of flood events using IMD, CRU, and CCSM4-derived meteorological data sets over the Vaigai River basin, Tamil Nadu (India). Sustain Water Resour Manag 5:1731–1744. https://doi.org/10.1007/s40899-019-00325-2
Odiyo JO, Phangisa JI, Makungo R (2012) Rainfall-runoff modelling for estimating Latonyanda River flow contributions to Luvuvhu River downstream of Albasini Dam. Phys Chem Earth 50:5–13. https://doi.org/10.1016/j.pce.2012.09.007
Prabu P, Baskaran R (2013) Drainage morphometry of upper Vaigai River sub-basin, Western Ghats, South India using remote sensing and GIS. J Geol Soc India 82:519–528. https://doi.org/10.1007/s12594-013-0183-7
Ramkumar M, Santosh M, Abdul Rahaman S, Balasundareshwaran A, Balasubramani K, Mathew MJ, Sautter B, Siddiqui SN, Usha K, Sreerhishiya K, Prithiviraj G, Nagarajan R, Thirukumaran V, Menier D, Kumaraswamy K (2019) Tectono-morphological evolution of the Cauvery, Vaigai and Thamirabarani River basins: implications on timing, stratigraphic markers, relative roles of intrinsic and extrinsic factors and transience of Southern Indian landscape. Geol J 54:2870–2911. https://doi.org/10.1002/gj.3520
Refsgaard JC, Knudsen J (1996) Operational validation and intercomparison of different types of hydrological models. Water Resour Res 32:2189–2202. https://doi.org/10.1029/96wr00896
Ritter A, Muñoz-Carpena R (2013) Performance evaluation of hydrological models: statistical significance for reducing subjectivity in goodness-of-fit assessments. J Hydrol 480:33–45. https://doi.org/10.1016/j.jhydrol.2012.12.004
Roy D, Kumari S (2019) Social actors in traditional tank rehabilitation: a case study of Tamil Nadu (India). Sustain Water Resour Manag 5:587–597. https://doi.org/10.1007/s40899-018-0221-0
Sankar K (2002) Evaluation of groundwater potential zones using remote sensing data in upper Vaigai River basin, Tamil Nadu, India. J ISRS 30:119–129. https://doi.org/10.1007/BF02990644
Shamsudin S, Hashim N, Supiah S, Hashim N (2002) Rainfall runoff simulation using MIKE 11 NAM. J Civ Eng 15:13. http://core.ac.uk/download/pdf/11783061.pdf. Accessed 7 Aug 2023
Shin M-J, Choi YS (2018) Combining an R-based evolutionary algorithm and hydrological model for effective parameter calibration. Water 10:1339. https://doi.org/10.3390/w10101339
Singh A, Singh S, Nema AK, Singh G, Gangwar A (2014a) Rainfall-Runoff modeling using mike 11 NAM model for Vinayakpur intercepted catchment, Chhattisgarh. Ind J Dryland Agri Res Develop 29:1. https://doi.org/10.5958/2231-6701.2014.01206.8
Singh RK, Kumar Villuri VG, Pasupuleti S, Nune R (2020) Hydrodynamic modeling for identifying flood vulnerability zones in lower Damodar River of eastern India. Ain Shams Eng J 11:1035–1046. https://doi.org/10.1016/j.asej.2020.01.011
Singh VP, Mishra AK, Chowdhary H, Khedun CP (2014b) Climate change and its impact on water resources. In: Handbook of environmental engineering: modern water resources engineering, vol 15. (Humana Press Edn). Springer, New York, pp 525–569. https://doi.org/10.1007/978-1-62703-595-8
Skahill BE, Doherty J (2006) Efficient accommodation of local minima in watershed model calibration. J Hydrol 329:122–139. https://doi.org/10.1016/j.jhydrol.2006.02.005
Slieman AA, Kozlov D (2023) Verification of MIKE 11-NAM Model for runoff modeling using АNN, FIS, and ARIMA methods in poorly studied basin. E3S Web Conf 401:01035 CONMECHYDRO-2023. https://doi.org/10.1051/e3sconf/202340101035
Stisen S, Koch J, Sonnenborg TO, Refsgaard JC, Bircher S, Ringgaard R, Jensen KH (2018) Moving beyond runoff calibration: multi-constraint optimization of a surface subsurface-atmosphere model. Hydrol Process 32(17):2654–2668. https://doi.org/10.1002/hyp.13177
Teshome FT, Bayabil HK, Thakural LN, Welidehanna FG (2020) Verification of the MIKE11-NAM model for simulating streamflow. J Environ Prot 11:152–167. https://doi.org/10.4236/jep.2020.112010
Tundisi GJ (2008) Water resources in the future: problems and solution. Estudos Avançado (Adv Stud) 22(63):7–16. https://doi.org/10.1175/1520-0477-47.4.275
Willmott CJ (1981) On the validation of models. Phys Geogr 2(2):184–194. https://doi.org/10.1080/02723646.1981.10642213
Acknowledgements
The authors are extremely grateful to the Management, Principal, Department Head, and staff members of Thiagarajar College of Engineering, Madurai’s Civil Engineering Department, and Assistant Engineer PWD Madurai for providing the data, vital support, and encouragement for the successful completion of this study. Dr. BP Bhaskar's assistance is greatly appreciated.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethical approval
It is certified that the study complied with all ethical standards.
Informed consent
Not applicable.
Conflict of interest
The authors declare no competing interests.
Additional information
Responsible editor: Broder J. Merkel
Supplementary information
Supplementary file 1
(DOCX 17 kb)
Supplementary file 2
(DOCX 36 kb)
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.
About this article
Cite this article
Keerthy, K., Chandran, S., Dhanasekarapandian, M. et al. MIKE HYDRO River model’s performance in simulating rainfall-runoff for Upper Vaigai sub-basin, Southern India. Arab J Geosci 17, 125 (2024). https://doi.org/10.1007/s12517-024-11930-7
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12517-024-11930-7