Performance evaluation and parameters sensitivity of a distributed hydrological model for a semi-arid catchment in India

  • V D Loliyana
  • P L Patel


In present study, a distributed physics based hydrological model, MIKE SHE coupled with MIKE 11, is calibrated using multi-objective approach, i.e., minimization of error in prediction of stream flows and groundwater levels, using the data of eight years from 1991 to 1998 of Yerli sub-catchment \((\hbox {area} = 15{,}881\,\hbox {km}^{2})\) of upper Tapi basin in India. The sensitivity analyses of thirteen model parameters related with overland flow, unsaturated and saturated zones have been undertaken while simulating the runoff volume, peak runoff at catchment outlet and groundwater levels within the catchment with wide variations \((\pm 50\%)\) in the model parameters. The calibrated model has also been validated for prediction of stream flow and groundwater levels within the Yerli sub-catchment for period 1999–2004. The simulated results revealed that calibrated model is able to simulate hydrographs satisfactorily for Yerli sub-catchment (NSE \(=\) 0.65–0.89, \(r=0.80{-}0.95\)) at daily and monthly time scales. The ground water levels are predicted reasonably satisfactorily for the plain area (RMSE \(=\) 0.50–6.50 m) in the study area. The results of total water balance indicated that about 78% of water is lost from the system through evapotranspiration, out of which about 3.5% is contributed from the groundwater zone.


Distributed approach hydrological modelling calibration sensitivity analysis Yerli catchment 



Authors are thankful to MHRD-NPIU-TEQIP-II for providing the funding through Centre of Excellence (CoE) Project on ‘Water Resources and Flood Management Centre at SVNIT’ under which present investigation has been undertaken. Authors are also thankful to India Meteorological Department (IMD), National Remote Sensing Centre (NRSC), Hyderabad, National Bureau of Soil Survey and Land Use Planning (NBSS & LUP), Nagpur, Central Ground Water Board (CGWB), Nagpur, and Central Water Commission (CWC), Tapi division for providing the data for present study.


  1. Allen R G, Pereira L S, Raes D and Smith M 1998 Crop evapotranspiration: Guidelines for computing crop water requirements; FAO Irrigation and Drainage Paper 56, Rome, Italy.Google Scholar
  2. CGWB 2013 Amravati, Akola and Buldana districts profiles, Central Ground Water Board report, New Delhi, India.Google Scholar
  3. Chow V T, Maidment D R and Mays L W 1988 Applied Hydrology; Mcgraw Hill, New York.Google Scholar
  4. Chu M L, Knouft J H, Ghulam A, Guzman J A and Pan Z 2013 Impacts of urbanization on river flow frequency: A controlled experimental modelling-based evaluation approach; J. Hydrol. 495 1–12.CrossRefGoogle Scholar
  5. Clausen B and Biggs B J F 2000 Flow variables for ecological studies in temperate streams: Groupings based on covariance; J. Hydrol. 237(3) 184–197.CrossRefGoogle Scholar
  6. Dai Z, Li C, Trettin C, Sun G, Amatya D and Li H 2010 Bi-criteria evaluation of the MIKE SHE model for a forested watershed on the South Carolina coastal plain; Hydrol. Earth Syst. Sci. 14 1033–1046.CrossRefGoogle Scholar
  7. DHI 2017 MIKE SHE User and Reference Manual; Denmark.Google Scholar
  8. El-Nasr A, Arnold J G and Berlamont J 2005 Modelling the hydrology of a catchment using a distributed and a semi-distributed model; Hydrol. Pros. 19 573–587.CrossRefGoogle Scholar
  9. Engman E T 1986 Roughness coefficients for routing surface runoff; J. Irri. Drain. Engg. 112(1) 39–53.CrossRefGoogle Scholar
  10. Foster S B and Allen D M 2015 Groundwater-surface water interactions in a mountain-to-coast watershed: Effects of climate change and human stressors; Adv. Meteorol. 861805 1–22.CrossRefGoogle Scholar
  11. GSDA 2004 Dynamic groundwater assessment report (DGAR), Groundwater Survey Development Authority, Maharashtra, India.Google Scholar
  12. Im S, Kim H, Kim C and Jang C 2009 Assessing the impacts of land use changes on watershed hydrology using MIKE SHE; Engg. Geol. 57 231–239.Google Scholar
  13. Jain S K, Agarwal P K and Singh V P 2007 Hydrology and Water Resources of India; Springer Science & Business Media, India.Google Scholar
  14. Jain P K and Tambe J A 2012 Inland salinity in parts of Purna alluvial basin, Amravati, Akola and Buldhana districts, Maharashtra; Central Ground Water Board report, Nagpur, India.Google Scholar
  15. Kaarlsson I B, Sonnenborg T O, Refsgaard J C, Trolle D, Borgesen C D, Olesen J E, Jeppesen E and Jensen K H 2016 Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change; J. Hydrol. 535 301–317.CrossRefGoogle Scholar
  16. Keilholz P, Disse M and Halik U 2015 Effects of land use and climate change on groundwater and ecosystems at the middle reaches of the Tarim river using the MIKE SHE integrated hydrological model; Water 7 3040–3056.CrossRefGoogle Scholar
  17. Kothyari U C, Raamsankaran Raaj, Satish Kumar D, Ghosh S K and Mendiratta N 2010 Geospatial based automated watershed modeling in Garhwal Himalaya; J. Hydroinfo. 12(4) 502–520.CrossRefGoogle Scholar
  18. Loliyana V D and Patel P L 2015 Lumped conceptual hydrological model for Purna river basin, India; Sadhana 40(8) 2411–2428.CrossRefGoogle Scholar
  19. Lorup J K, Christian R J and Mazvimavi D 1998 Assessing the effect of land use change on catchment runoff by combined use of statistical tests and hydrological modeling: Case study from Zimbabwe; J. Hydrol. 205 147–163.CrossRefGoogle Scholar
  20. Madsen H 2003 Parameter estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives; Adv. Water Res. 26 205–216.CrossRefGoogle Scholar
  21. Penman H L 1948 Natural evaporation from open water, bare soil, and grass; Proc. Roy. Soc. London 193 120–145.CrossRefGoogle Scholar
  22. Qin H, Cao G, Kristensen M, Refsgaard J C, Rasmussen M O, He X, Liu J, Shu Y and Zheng C 2013 Integrated hydrological modeling of the North China plain and implications for sustainable water management; Hydrol. Earth Syst. Sci. 17 3759–3778.CrossRefGoogle Scholar
  23. Refsgaard J C 1997 Parameterization, calibration and validation of distributed hydrological model; J. Hydrol. 198 69–97.CrossRefGoogle Scholar
  24. Refsgaard J C and Knudsen J 1996 Operational, validation and intercomparison of different types of hydrological models; Water Resour. Res. 32 2189–2202.CrossRefGoogle Scholar
  25. Refsgaard J C and Storm B 1995 MIKE SHE; In: Computer Models of Watershed Hydrology (ed.) Singh V P, Water Resources Publications, Highlands Ranch, CO, USA, pp. 809–846.Google Scholar
  26. Rahim B E A, Yusoff I, Jafri A M, Othman Z and Ghani A A 2012 Application of MIKE SHE modelling system to set up a detailed water balance computation; Water Environ. J. 26 490–503.CrossRefGoogle Scholar
  27. Sahoo G B, Ray C and De Carlo E H 2006 Calibration and validation of a physically distributed hydrological model, MIKE SHE, to predict streamflow at high frequency in a flashy mountainous Hawaii stream; J. Hydrol. 327 94–109.CrossRefGoogle Scholar
  28. Singh R, Subramanian K and Refsgaard J C 1999 Hydrological modeling of a small watershed using MIKE SHE for irrigation planning; Agr. Water Manag. 41(3) 149–166.CrossRefGoogle Scholar
  29. Spinoni J, Vogt J, Naumann G, Carrao H and Barbosa P 2015 Towards identifying areas at climatological risk of desertification using the Köppen–Geiger classification and FAO aridity index; Int. J. Climatol. 35(9) 2210–2222.CrossRefGoogle Scholar
  30. Swain J B and Patra K C 2017 Stream flow estimation in ungauged catchments using regional flow duration curve: Comparative study; J. Hydrol. Engg. 22(7), Scholar
  31. Thompson J R, Sorenson H R, Gavin H and Refsgaard A 2004 Application of the coupled MIKE SHE/MIKE 11 modelling system to a lowland wet grassland in southeast England; J. Hydrol. 293(1) 151–179.CrossRefGoogle Scholar
  32. UNEP 1992 World Atlas of Desertification; United Nations Environment Programme Edward Arnold, London.Google Scholar
  33. Vázquez R F, Beven K and Feyen J 2009 GLUE based assessment on the overall predictions of a MIKE SHE application; Water Resour. Manag. 23(7) 1325–1349.CrossRefGoogle Scholar
  34. Vieux B E 2001 Distributed Hydrologic Modelling Using GIS; Kluwer Academic Publishers, Dordrecht, The Netherlands.CrossRefGoogle Scholar
  35. Vo N D and Gourbesville P 2016 Application of deterministic distributed hydrological model for large catchment: A case study at Vu Gia Thu Bon catchment, Vietnam; J. Hydroinfor. 18(5) 885–904.CrossRefGoogle Scholar
  36. Wang S, Zhang Z, Sun G, Strauss P, Guo J, Tang Y and Yao A 2012 Multi-site calibration, validation, and sensitivity analysis of the MIKE SHE model for a large watershed in northern China; Hydrol. Earth Syst. Sci. 16 4621–4632.CrossRefGoogle Scholar
  37. Wijesekara G N, Farjad B, Gupta A, Qiao Y, Delaney P and Marceau D J 2014 A comprehensive land-use/hydrological modeling system for scenario simulations in the Elbow river watershed, Alberta, Canada; Environ. Manag. 53 357–381.CrossRefGoogle Scholar
  38. Yan J and Smith K R 1994 Simulations of integrated surface water and ground water systems – model formulation; J. Am. Water Resour. Assoc. 30(5) 879–890.CrossRefGoogle Scholar
  39. Zhang Z, Wang S, Sun Ge, McNulty S G, Zhang H, Li J, Zhang M, Klaghofer E and Strauss P 2008 Evaluation of the MIKE SHE model for application in the loess plateau, China; J. Am. Water Resour. Assoc. 44(5) 1108–1119.CrossRefGoogle Scholar

Copyright information

© Indian Academy of Sciences 2018

Authors and Affiliations

  1. 1.Department of Civil EngineeringSVNIT SuratSuratIndia

Personalised recommendations