Abstract
The current study uses remote sensing derived products, high resolution gridded rainfall and temperature, and SWAT inside a Geographic Information System (GIS) to assess the Kuttiyadi River's hydrological response and water balance components. As Kuttiyadi basin lacks a rainfall monitoring station, making hydrological studies difficult. Thus, we used satellite-based rainfall data as a solution to data shortages in the basin. The basin has separated into 104 numbers of hydrological response units (HRUs) based on unique land use, soil, and slope. The available streamflow data was divided for the calibration (2004–2013) and validation (2014–2017) for the modelling of both daily and monthly streamflow. The simulation of the streamflow was observed to be good on the daily time step (R2 = 0.65, NSE = 0.62 and R2 = 0.62, NSE = 0.60 for the calibration and validation respectively) which is further improved for the monthly time step (R2 = 0.90, NSE = 0.80 and R2 = 0.88, NSE = 0.85 for the calibration and validation respectively). During the monsoon, PBIAS value for the daily validations exceeded from the permissible limit due to the higher fluctuations in the daily streamflow. Our modelling results found that NE monsoon has a greater influence than the SW monsoon, generating almost 75% of total surface runoff in the basin. Study of the basin's water balance indicates that surface runoff is more prevalent, and contributes 35% to annual precipitation. The curve number, hydraulic conductivity of a channel and soil water capacity are highly sensitive parameters which showed rapid changes in land-use and hydraulic conductivity of the mainstream channel owing to the bi-directional interaction of the groundwater with the streamflow. The current study found that the PET and ET were fairly high, and that ET accounted for 24% of the total precipitation.
Article Highlights
-
SWAT model was used to calculate streamflow & water balance components.
-
Parameters CN2, ALPHA_BF, GWQMN, GE_REVAP, REVAPM, and ESCO were found most sensitive to peak flows.
-
During the monsoon, daily PBIAS values exceeded the permissible limit.
-
SWAT modelling proved potentially robust to understand stream hydrology for long-term management.








Similar content being viewed by others
Data availability
Not applicable.
References
Abbaspour KC (2015) SWAT Calibration and uncertainty programs—a user manual. Swiss Federal Institute of Aquatic Science and Technology: Eawag, Switzerland
Abbaspour KC, Yang J, Maximov I, Siber R, Bogner K, Mieleitner J, Srinivasan R (2007) Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. J Hydrol 333(2–4):413–430. https://doi.org/10.1016/j.jhydrol.2006.09.014
Abbaspour KC, Rouholahnejad E, Vaghefi SR, Srinivasan R, Yang H, Kløve B (2015) A continental-scale hydrology and water quality model for Europe: calibration and uncertainty of a high-resolution large-scale SWAT model. J Hydrol 1(524):733–752. https://doi.org/10.1016/j.jhydrol.2015.03.027
Abbaspour K, Vaghefi S, Srinivasan R (2017) A guideline for successful calibration and uncertainty analysis for soil and water assessment: a review of papers from the 2016 international SWAT conference. Water 10:6. https://doi.org/10.3390/w10010006
Aboelkhair H, Morsy M, El Afandi G (2019) Assessment of agroclimatology NASA POWER reanalysis datasets for temperature types and relative humidity at 2 m against ground observations over Egypt. Adv Space Res 64(1):129–142
Addis HK, Strohmeier S, Ziadat F, Melaku ND, Klik A (2016) Modeling streamflow and sediment using SWAT in Ethiopian highlands. Int J Agric Biol Eng 9(5):51–66
Arnold JG, Allen PM (1996) Estimating hydrologic budgets for three Illinois watersheds. J Hydrol 176(1–4):57–77. https://doi.org/10.1016/0022-1694(95)02782-3
Arnold JG, Allen PM (1999) Automated methods for estimating baseflow and ground water recharge from streamflow records. J Am Water Resour Assoc 35:411–424
Arnold JG, Moriasi DN, Gassman PW, Abbaspour KC, White MJ, Srinivasan R et al (2012) SWAT: model use, calibration, and validation. Trans ASABE 55:1491–1508. https://doi.org/10.13031/2013.42256
Bergstrom S (1992) The HBV model—its structure and applications. SMHI Rep Hydrol 4:35
Bhat SU, Khanday SA, Islam ST, Sabha I (2021) Understanding the spatiotemporal pollution dynamics of highly fragile montane watersheds of Kashmir Himalaya, India. Environ Pollut 1(286):117335
Borah DK, Arnold JG, Bera M, Krug EC, Liang XZ (2007) Storm event and continuous hydrologic modeling for comprehensive and efficient watershed simulations. J Hydrol Eng 12(6):605–616
Chakraborty S, Biswas S (2021) Simulation of flow at an ungauged river site based on HEC-HMS model for a mountainous river basin. Arab J Geosci 14(20):1–17
Daneshvar F, Frankenberger JR, Bowling LC, Cherkauer KA, Moraes AGDL (2021) Development of strategy for SWAT hydrologic modeling in data-scarce regions of Peru. J Hydrol Eng 26:05021016
dos Santos JC, de Andrade EM, Medeiros PH, Guerreiro MJ, de Queiroz Palácio HA (2017) Effect of rainfall characteristics on runoff and water erosion for different land uses in a tropical semiarid region. Water Resour Manag 31(1):173–185. https://doi.org/10.1007/s11269-016-1517-1
Ebert E, Janowiak JE, Kidd C (2007) Comparison of near-real-time precipitation estimates from satellite observations and numerical models. Bull Am Meteorol Soc 88:47–64
FAO (1974) FAO–UNESCO Soil Map of the World. Legend, vol 1. UNESCO, Paris
Fereidoon M, Koch M, Brocca L (2019) Predicting rainfall and runoff through satellite soil moisture data and SWAT modelling for a poorly gauged basin in Iran. Water 11:594
Grant EHC, Lynch HJ, Muneepeerakul R, Arunachalam M, Rodrı’guez-IturbeFagan IWF (2012) Interbasin water transfer, riverine connectivity, and spatial controls on fish biodiversity. PLoS ONE 7:e34170
Holvoet K, Griensven AV, Seuntjens P, Vanrolleghem PA (2005) Sensitivity analysis for hydrology and pesticide supply towards the river in SWAT. Phys Chem Earth 30:518–526
ICWE: International Conference on Water and the Environment (1992) Dublin, Ireland. http://www.wmo.int/pages/prog/hwrp/documents/english/icwedece.html
Imani S, Niksokhan MH, Jamshidi S, Abbaspour KC (2017) Discharge permit market and farm management nexus: an approach for eutrophication control in small basins with low-income farmers. Environ Monit Assess 189(7):1–14
Imani S, Delavar M, Niksokhan MH (2019) Identification of nutrients critical source areas with swat model under limited data condition. Water Resour 46(1):128–137
Jajarmizadeh M, Harun S, Ghahraman B, Mokhtari MH (2012) Modeling daily stream flow usingplant evapotranspiration method. Int J Water Resour Environ Eng 4(6):218–226
Johnston R, Smakhtin V (2014) Hydrological modeling of large river basins: how much is enough? Water Resour Manag 28(10):2695–2730
Katyaini S, Mukherjee M, Barua A (2021) Water–food nexus through the lens of virtual water flows: the case of India. Water 13(6):768
Krysanova V, Arnold JG (2008) Advances in ecohydrological modelling with SWAT—a review. Hydrol Sci J 53(5):939–947. https://doi.org/10.1623/hysj.53.5.939
Kumar D, Bhattacharjya RK (2020) Evaluating two GIS-based semi-distributed hydrological models in the Bhagirathi-Alkhnanda River catchment in India. Water Policy 22(6):991–1014
Kumar D, Bhattacharjya RK (2021) Change in rainfall patterns in the hilly region of Uttarakhand due to the impact of climate change. Appl Environ Res 43(1):1–3
Lal P, Prakash A, Kumar A (2020) Google Earth Engine for concurrent flood monitoring in the lower basin of Indo-Gangetic Brahmaputra plains. Nat Hazards 104:1947–1952
Liu X, Liu FM, Wang XX, Li XD, Fan YY, Cai SX, Ao TQ (2017) Combining rainfall data from rain gauges and TRMM in hydrological modelling of Laotian data-sparse basins. Appl Water Sci 7(3):1487–1496. https://doi.org/10.1007/s13201-015-0330-y
Malagò A, Pagliero L, Bouraoui F, Franchini M (2015) Comparing calibrated parameter sets of the SWAT model for the Scandinavian and Iberian peninsulas. Hydrol Sci J 6:949–967
Marahatta S, Devkota L, Aryal D (2021a) Hydrological modeling: a better alternative to empirical methods for monthly flow estimation in ungauged basins. J Water Resour Prot 254–270
Marahatta S, Devkota LP, Aryal D (2021b) Application of SWAT in hydrological simulation of complex mountainous river basin (Part I: Model Development). Water 11:1546. https://doi.org/10.3390/w13111546
Medhi H, Tripathi S (2015) On identifying relationships between the flood scaling exponent and basin attributes. Chaos Interdiscip J Nonlinear Sci 25:075405
Meng F, Sa C, Liu T, Luo M, Liu J, Tian L (2020) Improved model parameter transferability method for hydrological simulation with SWAT in ungauged mountainous catchments. Sustainability 12:3551
Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900
Murty PS, Pandey A, Suryavanshi S (2014) Application of semi-distributed hydrological model for basin level water balance of the Ken basin of Central India. Hydrol Process 28(13):4119–4129. https://doi.org/10.1002/hyp.9950
Nasiri S, Ansari H, Ziaei AN (2020) Simulation of water balance equation components using SWAT model in Samalqan Watershed (Iran). Arab J Geosci 13:1–15. https://doi.org/10.1007/s12517-020-05366-y
Neitsch SL, Arnold JG, Kiniry JR, Williams JR, King KW (2002) Soil and water assessment tool (SWAT): theoretical documentation, version 2000. Texas Water Resources Institute, College Station, Texas, TWRI Report TR-191
Rajeev Gandhi BG, Kumar D, Yadav HL (2020) An artificial neural network model for estimating the flood in Tehri Region of Uttarakhand using rainfall data. In: Soft computing: theories and applications. Springer, Singapore, pp 467–477
Rautela KS, Kumar M, Khajuria V, Alam MA (2022a) Comparative geomorphometric approach to understand the hydrological behaviour and identification of the Erosion prone areas of a coastal watershed using RS and GIS tools. Discov Water 2(1):1–16
Rautela KS, Kuniyal JC, Alam MA, Bhoj AJ, Kanwar N (2022b) Assessment of daily streamflow, sediment fluxes, and erosion rate of a pro-glacial stream basin, Central Himalaya, Uttarakhand. Water Air Soil Pollut 233:136. https://doi.org/10.1007/s11270-022-05567-z
Sharannya TM, Al-Ansari N, Deb Barma S, Mahesha A (2020) Evaluation of satellite precipitation products in simulating streamflow in a humid tropical catchment of India using a semi-distributed hydrological model. Water 12(9):2400. https://doi.org/10.3390/w12092400
Shrestha MK, Recknagel F, Frizenschaf J, Meyer W (2016) Assessing SWAT models based on single and multi-site calibration for the simulation of flow and nutrient loads in the semi-arid Onkaparinga catchment in South Australia. Agric Water Manag 175:61–71. https://doi.org/10.1016/j.agwat.2016.02.009
Singh L, Saravanan S (2020) Simulation of monthly streamflow using the SWAT model of the Ib River watershed, India. HydroResearch 3:95–105. https://doi.org/10.1016/j.hydres.2020.09.001
Singh R, Mishra V, Narasimhan B, Ghosh S, Sharma A, Dutta S, Mujumdar P (2020) Hydrological modeling in India. Proc Indian Natl Sci Acad 86:479–494. https://doi.org/10.16943/ptinsa/2020/49802
Singh VP (2018) Hydrologic modeling: progress and future directions. Geosci Lett 5(1):1–8. https://doi.org/10.1186/s40562-018-0113-z
Sofi MS, Bhat SU, Rashid I, Kuniyal JC (2020) The natural flow regime: a master variable for maintaining river ecosystem health. Ecohydrology 13(8):e2247
Sofi MS, Rautela KS, Bhat SU, Rashid I, Kuniyal J (2021) Application of geomorphometric approach for the estimation of hydro-sedimentological flows and cation weathering rate: towards understanding the sustainable land use policy for the Sindh Basin, Kashmir Himalaya. Water Air Soil Pollut 232(7):1–1
Swetha TV, Gopinath G (2020) Landslides susceptibility assessment by analytical network process: a case study for Kuttiyadi river basin (Western Ghats, southern India). SN Appl Sci 2(11):1–12. https://doi.org/10.1007/s42452-020-03574-5
Thokchom B (2020) Water-related problem with special reference to global climate change in India. In: Water conservation and wastewater treatment in BRICS nations. Elsevier, pp 37–60
Tramblay Y, Thiemig V, Dezetter A, Hanich L (2016) Evaluation of satellite-based rainfall products for hydrological modelling in Morocco. Hydrol Sci J 61(14):2509–2519
Tuppad P, Douglas-Mankin KR, Lee T, Srinivasan R, Arnold JG (2011) Soil and water assessment tool (SWAT) hydrologic/water quality model: extended capability and wider adoption. Trans ASABE 54(5):1677–1684
United Nations (2021) The United Nations World water development report 2021: valuing water. UNESCO, Paris. https://www.unwater.org/publications/un-world-water-development-report-2021/
USDA Soil Conservation Service (1972) National engineering handbook, section 4, hydrology
Vu TT, Li L, Jun KS (2018) Evaluation of multi-satellite precipitation products for streamflow simulations: a case study for the Han River Basin in the Korean Peninsula. East Asia Water 10(5):64
White KL, Chaubey I (2005) Sensitivity analysis, calibration, and validations for a multisite and multivariable SWAT model. J Am Water Resour Assoc 41:1077–1089
Wu K, Xu YJ (2006) Evaluation of the applicability of the SWAT model for coastal watersheds in Southeastern Louisiana. J Am Water Resour Assoc 42(5):1247–1260
Yuan Y, Nie W, Sanders E (2015) Problems and prospects of SWAT model application on an arid/semi-arid watershed in Arizona. In: Proceedings of the 2015 SEDHYD conference, Reno, NV, USA, pp 19–23
Zhang H, Wang B, Li Liu D, Zhang M, Leslie LM, Yu Q (2020) Using an improved SWAT model to simulate hydrological responses to land use change: a case study of a catchment in tropical Australia. J Hydrol 585:124822. https://doi.org/10.1016/j.jhydrol.2020.124822
Acknowledgements
The 1st and the 2nd author would like to thank Department of Water Resources, CED, Punjab Engineering College (Deemed to be University) for providing facilities without which the preparation of the manuscript would have been impossible. The 3rd and 5th author would like to thank Department of Environmental Science, University of Kashmir for providing facilities. The 4th author would like to thank Director, Govind Ballabh Pant National Institute of Himalayan Environment (NIHE), Kosi-Katarmal, Almora-263 643, Uttarakhand.
Funding
The author(s) received no specific funding for this work.
Author information
Authors and Affiliations
Contributions
Conceptualization: KSR, MK, MSS; methodology: KS, RMK, MSS; formal analysis and investigation: KSR, MK, MSS; writing—original draft preparation: KSR, MSS, SUB; writing—review and editing: KSR, MK, MSS, JCK, SUB; supervision: MK, JCK, SUB.
Corresponding author
Ethics declarations
Conflict of interest
All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.
Rights and permissions
About this article
Cite this article
Rautela, K.S., Kumar, M., Sofi, M.S. et al. Modelling of Streamflow and Water Balance in the Kuttiyadi River Basin Using SWAT and Remote Sensing/GIS Tools. Int J Environ Res 16, 37 (2022). https://doi.org/10.1007/s41742-022-00416-7
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s41742-022-00416-7