Skip to main content

Advertisement

Log in

Runoff modelling of Aripal watershed using SWAT model

  • Original Paper
  • Published:
Arabian Journal of Geosciences Aims and scope Submit manuscript

Abstract

Accuracy in watershed modelling has improved because of the use of continuous-time and distributed hydrologic models like SWAT (Soil and Water Assessment Tool). However, it has also significantly increased the amount of work required for users to parameterize the watershed in general and to accurately describe the watershed’s spatial variability in particular. Some of the challenges involved in maintaining geographical data have been eased by recent advancements in geographical information systems (GIS). This paper addresses the first ever research conducted in the Aripal watershed, which is significant due to its topography and remote accessibility issues. The Soil and Water Assessment Tool (SWAT) with an interface to ArcView GIS software was used to assess the runoff of the Aripal watershed, a sub-catchment of the Jhelum River, a significant Himalayan River situated in J&K, India. Soil map, land use-land-cover map, slope map, and historical weather and discharge data served as the primary inputs to the model giving runoff as the output from the watershed. Two statistical measures, coefficient of determination (R2) and Nash–Sutcliffe efficiency coefficient (NSE) were calculated for the purpose of assessing model performance. Calibration of model was done for runoff values between 2005 and 2013 and validation for the period 2014–2018.The value of R2 achieved was 0.904 for calibration period suggesting a good relation between observed/measured and predicted values, and for the validation period it was found to be 0.766. The value of NSE was found to be 0.718 for calibration period and 0.813 for the validation period. Thus, SWAT was found to be an appropriate tool for watershed runoff modelling. The extreme flood event that occurred in the catchment in 2014, on the other hand, was underestimated by the model. Sensitivity analysis was carried out to identify the most influential variables in the determination of runoff from the watershed.

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
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19

Similar content being viewed by others

Data availability

On reasonable request, the authors have no objection in providing the data findings of this study.

References

  • Adeogun AG, Sule BF, Salami AW (2015) Simulation of sediment yield at the upstream watershed of Jebba Lake in Nigeria using SWAT model. Malays J Civ Eng 27:25–40

    Google Scholar 

  • Anaba LA, Banadda N, Kiggundu N, Wanyama J, Engel B, Moriasi D (2016) Application of SWAT to assess the effects of land-use change in the Murchison Bay catchment in Uganda. CWEEE 6(01):24

    Article  Google Scholar 

  • Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment–Part 1: Model development. J Am Water Resour Assoc 34(1):73–89

    Article  Google Scholar 

  • Arnold JG, Moriasi DN, Gassman PW, Abbaspour KC, White MJ, Srinivasan R,Santhi C, Harmel RD, van Griensven A, Van Liew MW, Kannan N, Jha MK (2012) SWAT: model use, calibration, and validation, Transactions of ASABE 55(04):1491–1508

  • Chen F, Crow WT, Starks PJ, Moriasi DN (2011) Improving hydrologic predictions of a catchment model via assimilation of soil surface moisture. Adv Water Resour 34(01):526–536

    Article  Google Scholar 

  • Daggupati P, Pai N, Ale S, Douglas-Mankin KR, Zeckoski RW, Jeong J, Parajuli PB, Saraswat D, Youssef MA (2015) A recommended calibration and validation strategy for hydrologic and water quality models. Trans ASABE 58(6):1705–1719

    Article  Google Scholar 

  • Devi GK, Ganasri BP, Dwarakish GS (2015) A review on hydrological models. Aquatic Procedia 4(01):1001–1007. https://doi.org/10.1016/j.aqpro.2015.02.126

    Article  Google Scholar 

  • Fadil A, Rhinane H, Kaoukaya A, Kharchaf Y, Bachir OA (2011) Hydrologic modeling of the Bouregreg watershed (Morocco) using GIS and SWAT model. J Geogr Inf Syst 3(04):279–289

    Google Scholar 

  • Fatahi Nafchi R, Yaghoobi P, Reaisi Vanani H, Ostad-Ali-Askari K, Nouri J, Maghsoudlou B (2021) Eco-hydrologic stability zonation of dams and power plants using the combined models of SMCE and CEQUALW2. Appl Water Sci 11(7):1–7. https://doi.org/10.1007/s13201-021-01427-z

    Article  Google Scholar 

  • Geza M, McCray JE (2008) Effects of soil data resolution on SWAT model stream flow and water quality predictions. J Environ Manage 88(3):393–406

    Article  Google Scholar 

  • Joh HK, Lee JW, Park MJ, Shin HJ, Yi JE, Kim GS, Srinivasan R, Kim SJ (2011) Assessing climate change impact on hydrological components of a small forest watershed through SWAT calibration of evapotranspiration and soil moisture. Trans ASABE 54(5):1773–1781

    Article  Google Scholar 

  • Kokkonen T, Koivusalo H, Karvonen T (2001) A semi-distributed approach to rainfall runoff modelling—a case study in a snow affected catchment. Environ Model Softw 16(5):481–493. https://doi.org/10.1016/S1364-8152(01)00028-7

    Article  Google Scholar 

  • Mishra A, Kar S, Singh VP (2007) Determination of runoff and sediment yield from a small watershed in sub-humid subtropics using the HSPF model. Hydrol Process 21:3035–3045

    Article  Google Scholar 

  • Nafchi RF, Samadi-Boroujeni H, Vanani HR, Ostad-Ali-Askari K, Brojeni MK (2021) Laboratory investigation on erosion threshold shear stress of cohesive sediment in Karkheh Dam. Environ Earth Sci 80(19):1–15. https://doi.org/10.1007/s12665-021-09984-x

    Article  Google Scholar 

  • Neitsch SL, Arnold JG, Kiniry JR, Williams JR, King KW (2005) Soil and water assessment tool theoretical documentation. Grassland. Soil and Water Research Laboratory, Temple, TX

  • Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2011) Soil and Water Assessment Tool, (SWAT) – theoretical documentation: version 2009, USDA Agricultural Research Service and Texas A&M Blackland Research Centre, Temple, TX

  • Ostad-Ali-Askari K (2022) Investigation of meteorological variables on runoff archetypal using SWAT: basic concepts and fundamentals. Appl Water Sci 12(8):1–18. https://doi.org/10.1007/s13201-022-01701-8

    Article  Google Scholar 

  • Ostad-Ali-Askari K, Shayannejad M, Ghorbanizadeh-Kharazi H (2017) Artificial neural network for modeling nitrate pollution of groundwater in marginal area of Zayandeh-rood River, Isfahan, Iran. KSCE J Civ Eng 21(1):134–140. https://doi.org/10.1007/s12205-016-0572-8

    Article  Google Scholar 

  • Perlman H (2016) The water cycle- USGS Water Science School. Retrieved 5/18, 2017, from https://water.usgs.gov/edu/watercycle.html

  • Prodanovic D, Stanic M, Milivojevic V, Simic Z, Arsic M (2009) DEM-based GIS algorithms for automatic creation of hydrological models data. J Serb Soc Comput Mech 3(1):64–85

    Google Scholar 

  • Santhi C, Arnold JG, Williams JR, Dugas WA, Srinivasan R, Hauck LM (2001) Validation of the SWAT model on a large river basin with point and nonpoint sources. J Am Water Resour Assoc 37(05):1169–1188

    Article  Google Scholar 

  • Setegn SG, Srinivasan R, Dargahi B (2008) Hydrological modeling in the Lake Tana Basin, Ethiopia Using SWAT model. The Open Hydrology Journal 2(01):49–62

    Article  Google Scholar 

  • Simic Z, Milivojevic N, Prodanovic D, Milivojevic V, Perovic N (2009) SWAT-based runoff modeling in complex catchment areas–theoretical background and numerical procedures. J Serb Soc Comput Mech 3(1):38–63

    Google Scholar 

  • Singh VP (1995) Computer models of watershed hydrology highlands Ranch. Water Resources Publications, CO

    Google Scholar 

  • Srinivasan R, Ramanarayanan TS, Arnold JG, Bednarz ST (1998) Large area hydrologic modeling and assessment part II: model application. J Am Water Resour Assoc 34(1):91–101

    Article  Google Scholar 

  • Van Griensven A, Meixner T, Grunwald S, Bishop T, Diluzio M, Srinivasan R (2006) A global sensitivity analysis tool for the parameters of multi-variable catchment models. J Hydrol 324(1–4):10–23. https://doi.org/10.1016/j.jhydrol.2005.09.008

    Article  Google Scholar 

  • Xu CY (2002) Textbook of hydrologic models, Uppsala University Department of Earth Sciences Hydrology, Sweden 2(1)

Download references

Acknowledgements

The authors thank Department of Geo-informatics, University of Kashmir and SKUAST-K for providing the relevant data required for this paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mehnaza Akhter.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Responsible Editor: Broder J. Merkel

Rights and permissions

Springer Nature or its licensor 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

Akhter, M., Malik, M.I., Mehraj, T. et al. Runoff modelling of Aripal watershed using SWAT model. Arab J Geosci 15, 1419 (2022). https://doi.org/10.1007/s12517-022-10708-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-022-10708-z

Keywords

Navigation