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Estimation of monthly snowmelt contribution to runoff using gridded meteorological data in SWAT model for Upper Alaknanda River Basin, India

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Abstract

The purpose of hydrologic modeling of a watershed is to gain valuable information about the processes occurring within watershed. With increasing temperature of the earth atmosphere, the snow fed mountainous river basins are going to get impacted severely. Lack of adequate weather station limits the scope of researches in these mountainous basins which are critical source of water resource for the country. However, improvement of satellite-based weather products has been able to nullify this barrier to great extent. In this study, a semi distributed hydrologic model of Upper Alaknanda river basin has been developed using gridded meteorological input data sourced from India Meteorological Department (IMD), National Aeronautics and Space Administration (NASA) Power, and The SWAT (Soil and water Assessment Tool) model. The calibration and validation of the model reflected satisfactory performance with the validation period (2013–2017) showing better match between simulated and observed flow than calibration period (2005–2012). The values of Nash-Sutcliffe efficiency, coefficient of determination, and Percent of bias for calibration period are 0.65, 0.67, and 14% respectively. Adoption of semi distributed approach for modeling enables to analyze the basin while preserving the heterogeneous nature of the basin. The spatiotemporal evaluation of snowmelt reveals that highest snowmelt was generated during month of April which also causes highest snowmelt contribution to runoff for April (59.76 %). The outcomes of this study reveals that satellite-based meteorological product can be adopted satisfactorily with SWAT model for estimation of snowmelt in upper Himalayan regions which gives a new direction of research in SWAT diaspora.

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References

  • Aawar, T., & Khare, D. (2020). Assessment of climate change impacts on streamflow through hydrological model using SWAT model: A case study of Afghanistan. Modeling Earth Systems and Environment, 6(3), 1427–1437. https://doi.org/10.1007/s40808-020-00759-0

    Article  Google Scholar 

  • Abbas, T., Hussain, F., Nabi, G., Boota, M. W., & Wu, R. (2019). Uncertainty evaluation of SWAT model for snowmelt runoff in a Himalayan watershed Uncertainty evaluation of SWAT model for snowmelt runoff in a Himalayan watershed, (June). https://doi.org/10.3319/TAO.2018.10.08.01

    Book  Google Scholar 

  • Abbaspour, K. C., Johnson, C. A., & van Genuchten, M. T. (2004). Estimating uncertain flow and transport parameters using a sequential uncertainty fitting procedure. Vadose Zone Journal, 3(4), 1340–1352. https://doi.org/10.2136/vzj2004.1340

    Article  Google Scholar 

  • Abbaspour, K. C., Rouholahnejad, E., Vaghefi, S., 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. Journal of Hydrology, 524, 733–752. https://doi.org/10.1016/j.jhydrol.2015.03.027

    Article  Google Scholar 

  • Abbaspour, K. C., Vaghe, S. A., Yang, H., & Srinivasan, R. (2019). Global soil, landuse, evapotranspiration, historical and future weather databases for SWAT applications. Scientific Data, 1–11,. https://doi.org/10.1038/s41597-019-0282-4

  • Abbaspour, K. C., Yang, J., Maximov, I., Siber, R., Bogner, K., Mieleitner, J., et al. (2007). Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. Journal of Hydrology, 333(2–4), 413–430. https://doi.org/10.1016/j.jhydrol.2006.09.014

    Article  Google Scholar 

  • Abbott, M. B., Bathurst, J. C., Cunge, J. A., O’Connell, P. E., & Rasmussen, J. (1986). An introduction to the E u r o p e a n hydrological system - - Systeme hydrologique E u r o p e e n , “ SHE ”, 2 : MODELLING SYSTEM The Syst ~ me Hydrologique Europ ~ en , or European Hydrological System ( SHE ), is an advanced , physically-based , distri. Journal of Hydrology, 87, 61–77.

    Article  Google Scholar 

  • Aggarwal, S. P., Thakur, P. K., Nikam, B. R., & Garg, V. (2014). Integrated approach for snowmelt run-off estimation using temperature index model, remote sensing and GIS. Current Science, 106(3), 397–407.

    Google Scholar 

  • Akhter, M., Iqbal, M., Tabish, M., Atufa, M., Shah, F., & Ahmad, S. (2022). Runoff modelling of Aripal watershed using SWAT model. Arabian Journal of Geosciences. https://doi.org/10.1007/s12517-022-10708-z

  • Al-Khafaji, M., Saeed, F. H., & Al-Ansari, N. (2020). The interactive impact of land cover and DEM Resolution on the accuracy of computed streamflow using the SWAT model. Water, Air, and Soil Pollution, 231(8). https://doi.org/10.1007/s11270-020-04770-0

  • Al-Kubaisi, M. H. D., & Al-Kubaisi, Q. Y. S. (2023). Using SWAT model to estimate the water balance of Wadi Al-Mohammadi Basin, Western Iraq. Iraqi Journal of Science, 64(3), 1245–1267. https://doi.org/10.24996/ijs.2023.64.3.21

    Article  Google Scholar 

  • Alawi, S. A., & Özkul, S. (2023). Evaluation of satellite-based precipitation data sets in hydrological modeling using Soil & Water Assessment Tool (SWAT). Arabian Journal of Geosciences, 16(5). https://doi.org/10.1007/s12517-023-11434-w

  • Ambroise, B., Beven, K., & Freer, J. (1996). Toward a generalization of the TOPMODEL concepts: Topographic indices of hydrological similarity. Water Resources Research, 32(7), 2135–2145. https://doi.org/10.1029/95WR03716

    Article  Google Scholar 

  • Arnold, J. G., Allen, P. M., Volk, M., Williams, J. R., & Bosch, D. D. (2010). Swat M, 53(5), 1433–1443.

    Google Scholar 

  • Arnold, J. G., Kiniry, J. R., Srinivasan, R., Williams, J. R., Haney, E. B., & Neitsch, S. L. (2012). Soil & water assessment tool. Version 2012 (p. 654). http://swat.tamu.edu/media/69296/SWAT-IODocumentation-2012.pdf. Retrieved 20 February 2013

  • Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Williams, J. R. (1998). Large area hydrologic modeling and assessment Part I : Model development. Basin scale model called SWAT soil and water development of large area hydrologic modeling speed and storage, advanced software debugging policy to meet the needs, and the mana. JAWRA Journal of the American Water Resources Association, 34(1), 73–89.

  • Awotwi, A., Yeboah, F., & Kumi, M. (2015). Assessing the impact of land cover changes on water balance components of White Volta Basin in West Africa. Water and Environment Journal, 29(2), 259–267. https://doi.org/10.1111/wej.12100

    Article  Google Scholar 

  • B. Dixon and J. Earls. (2010). Resample or not?! Effects of resolution of DEMs in watershed modeling. HYDROLOGICAL PROCESSES Hydrol. Process. 23, 1714–1724 (2009) Published online 20 April 2009 in Wiley InterScience (www.interscience.wiley.com) DOI: https://doi.org/10.1002/hyp.7306 , 2274(November 2008), 2267–2274. https://doi.org/10.1002/hyp

  • Bajracharya, A. R., Bajracharya, S. R., Shrestha, A. B., & Maharjan, S. B. (2018). Climate change impact assessment on the hydrological regime of the Kaligandaki Basin. Nepal. Science of the Total Environment, 625, 837–848. https://doi.org/10.1016/j.scitotenv.2017.12.332

    Article  CAS  Google Scholar 

  • Bárdossy, A., & Singh, S. K. (2008). Robust estimation of hydrological model parameters. Hydrology and Earth System Sciences, 12(6), 1273–1283. https://doi.org/10.5194/hess-12-1273-2008

    Article  Google Scholar 

  • Bennour, A., Jia, L., Menenti, M., Zheng, C., Zeng, Y., Barnieh, B. A., & Jiang, M. (2022). Calibration and validation of SWAT Model by using hydrological remote sensing observables in the Lake Chad Basin. Remote Sensing, 14(6). https://doi.org/10.3390/rs14061511

  • Biggs, T. W., & Whitaker, T. M. (2012). Critical elevation zones of snowmelt during peak discharges in a mountain river basin. Journal of Hydrology, 438-439, 52–65. https://doi.org/10.1016/j.jhydrol.2012.02.048

    Article  Google Scholar 

  • Bosilovich, M. G., Lucchesi, R., & Suarez, M. (2016). MERRA-2: File Specification. Earth, 9(9), 73 http://gmao.gsfc.nasa.gov/pubs/office_notes

    Google Scholar 

  • Braunschweig, F., Leitao, P. C., Fernandes, L., Pina, P., & Neves, R. J. J. (2004). The object-oriented design of the integrated water modelling system MOHID. In Developments in water science (Vol. 55, pp. 1079–1090). Elsevier. https://doi.org/10.1016/S0167-5648(04)80126-6

  • Caracciolo, D., Arnone, E., & Noto, L. V. (2014). Influence of spatial precipitation sampling on hydrological response at the catchment scale. Journal of Hydrologic Engineering, 19(3), 544–553. https://doi.org/10.1061/(asce)he.1943-5584.0000829

    Article  Google Scholar 

  • Chiphang, N., Bandyopadhyay, A., & Bhadra, A. (2020). Assessing the effects of snowmelt dynamics on streamflow and water balance components in an Eastern Himalayan River basin using SWAT model. Environmental Modeling and Assessment, 25(6), 861–883. https://doi.org/10.1007/s10666-020-09716-8

    Article  Google Scholar 

  • Cristiano, E., ten Veldhuis, M.-c., & van de Giesen, N. (2017). Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – A review. Hydrology and Earth System Sciences, 51(1), 209–211. https://doi.org/10.1016/0006-3002(61)91045-9

    Article  Google Scholar 

  • Daggupati, P., Yen, H., White, M. J., Srinivasan, R., Arnold, J. G., Keitzer, C. S., & Sowa, S. P. (2015). Impact of model development, calibration and validation decisions on hydrological simulations in West Lake Erie Basin. Hydrological Processes, 29(26), 5307–5320. https://doi.org/10.1002/hyp.10536

    Article  Google Scholar 

  • Debele, B., Srinivasan, R., & Gosain, A. K. (2010). Comparison of process-based and temperature-index snowmelt modeling in SWAT. Water Resources Management, 24(6), 1065–1088. https://doi.org/10.1007/s11269-009-9486-2

    Article  Google Scholar 

  • Dhami, B., Himanshu, S. K., Pandey, A., & Gautam, A. K. (2018). Evaluation of the SWAT model for water balance study of a mountainous snowfed river basin of Nepal. Environmental Earth Sciences, 77(1), 1–20. https://doi.org/10.1007/s12665-017-7210-8

    Article  Google Scholar 

  • Di Luzio, M., Srinivasan, R., Arnold, J. G., & Neitsch, S. L. (2002). ArcView interface for SWAT2000: User’s guide. TWRI Report TR-193. Texas Water Resources Institute.

  • Douinot, A., Roux, H., Garambois, P. A., Larnier, K., Labat, D., & Dartus, D. (2016). Accounting for rainfall systematic spatial variability in flash flood forecasting. Journal of Hydrology, 541, 359–370. https://doi.org/10.1016/j.jhydrol.2015.08.024

    Article  Google Scholar 

  • Earls, J., & Dixon, B. (2005). A comparative study of the effects of input resolution on the SWAT model. WIT Transactions on Ecology and the Environment, 83,. https://doi.org/10.2495/RM050211

  • Ficklin, D. L., & Zhang, M. (2013). A comparison of the curve number and Green-Ampt models in an agricultural watershed. Transactions of the ASABE, 56(1), 61–69. https://doi.org/10.13031/2013.42590

    Article  Google Scholar 

  • Ficklin, D. L., & Barnhart, B. L. (2014). SWAT hydrologic model parameter uncertainty and its implications for hydroclimatic projections in snowmelt-dependent watersheds. Journal of Hydrology, 519(PB), 2081–2090. https://doi.org/10.1016/j.jhydrol.2014.09.082

    Article  Google Scholar 

  • Fisher, J. R. B., Acosta, E. A., Dennedy-Frank, P. J., Kroeger, T., & Boucher, T. M. (2018). Impact of satellite imagery spatial resolution on land use classification accuracy and modeled water quality. Remote Sensing in Ecology and Conservation, 4(2), 137–149. https://doi.org/10.1002/rse2.61

    Article  Google Scholar 

  • Fontaine, T. A., Cruickshank, T. S., Arnold, J. G., & Hotchkiss, R. H. (2002). Development of a snowfall–snowmelt routine for mountainous terrain for the soil water assessment tool (SWAT). Journal of Hydrology, 262(1–4), 209–223. https://doi.org/10.1016/S0022-1694(02)00029-X

    Article  Google Scholar 

  • Fuka, D. R., Easton, Z. M., Brooks, E. S., Boll, J., Steenhuis, T. S., & Walter, M. T. (2012). A simple process-based snowmelt routine to model spatially distributed snow depth and snowmelt in the SWAT model. Journal of the American Water Resources Association, 48(6), 1151–1161. https://doi.org/10.1111/j.1752-1688.2012.00680.x

    Article  Google Scholar 

  • Gaddam, V. K., Myneni, T. K., Kulkarni, A. V., & Zhang, Y. (2022). Assessment of runoff in Chandra river basin of Western Himalaya using remote sensing and GIS techniques. Environmental Monitoring and Assessment, 194(3). https://doi.org/10.1007/s10661-022-09795-y

  • Gassman, P. W., Sadeghi, A. M., & Srinivasan, R. (2014). Applications of the SWAT model special section: Overview and insights. Journal of Environmental Quality, 43(1), 1–8. https://doi.org/10.2134/jeq2013.11.0466

    Article  CAS  Google Scholar 

  • Geza, M., & McCray, J. E. (2008). Effects of soil data resolution on SWAT model stream flow and water quality predictions. Journal of Environmental Management, 88(3), 393–406. https://doi.org/10.1016/j.jenvman.2007.03.016

    Article  CAS  Google Scholar 

  • Green, W. H., & Ampt, G. A. (1911). The flow of air and water through soils. The Journal of Agriculture Science. British Birds, 21(2), 11–12. https://doi.org/10.1007/978-1-4614-7990-1

    Article  Google Scholar 

  • Her, Y., Frankenberger, J., Chaubey, I., & Srinivasan, R. (2015). Threshold effects in HRU definition ofthe soil and water assessment tool. Transactions of the ASABE, 58(2), 367–378. https://doi.org/10.13031/trans.58.10805

    Article  Google Scholar 

  • Hock, R. (2003). Temperature index melt modelling in mountain areas. Journal of Hydrology, 282(1–4), 104–115. https://doi.org/10.1016/S0022-1694(03)00257-9

    Article  Google Scholar 

  • Ibrahim, G. R. F., Rasul, A., Hamid, A. A., Ali, Z. F., & Dewana, A. A. (2019). Suitable site selection for rainwater harvesting and storage case study using Dohuk governorate. Water (Switzerland), 11(4). https://doi.org/10.3390/w11040864

  • Jain, S. (2015). Hydrological modelling over Ganga basin with focus on snowmelt runoff (p. 70). M.Tech. Thesis.

    Google Scholar 

  • Johanson, R. C., Imhoff, J. C., Kittle, J. L., & Donigan, A. S. (1984). Hydrological simulation program--FORTRAN(HSPF): Users manual for release 8. 0. EPA-600/3-84-006 June 1984. Environmental Protection Agency, Athens, GA. 767 p, 138 p, 49 Ref, 5 Append. Contract/Grant, (68-01).

  • Kang, K., & Lee, J. H. (2014). Hydrologic modelling of the effect of snowmelt. Journal of Earth System Science, 4, 705–713.

    Article  Google Scholar 

  • Kannan, N., Santhi, C., White, M. J., Mehan, S., Arnold, J. G., & Gassman, P. W. (2019). Some Challenges in hydrologic model calibration for large-scale studies: a case study of SWAT model application to Mississippi-Atchafalaya river basin. Hydrology, 6(1), 1–23. https://doi.org/10.3390/hydrology6010017

    Article  Google Scholar 

  • Karakoyun, E., & Kaya, N. (2022). Hydrological simulation and prediction of soil erosion using the SWAT model in a mountainous watershed: A case study of Murat River Basin, Turkey. Journal of Hydroinformatics, 24(6), 1175–1193. https://doi.org/10.2166/hydro.2022.056

    Article  Google Scholar 

  • Kayastha, R. B., Steiner, N., Kayastha, R., Mishra, S. K., & McDonald, K. (2020). Comparative study of hydrology and icemelt in three Nepal river basins using the glacio-hydrological degree-day model (GDM) and observations from the advanced scatterometer (ASCAT). Frontiers in Earth Science, 7(January), 1–13. https://doi.org/10.3389/feart.2019.00354

    Article  Google Scholar 

  • Khadka, M., Kayastha, R. B., & Kayastha, R. (2020). Future projection of cryospheric and hydrologic regimes in Koshi River basin, Central Himalaya, using coupled glacier dynamics and glacio-hydrological models. Journal of Glaciology, 66(259), 831–845. https://doi.org/10.1017/jog.2020.51

    Article  Google Scholar 

  • Kimaru, A. N., Gathenya, J. M., & Cheruiyot, C. K. (2019). The temporal variability of rainfall and streamflow into Lake Nakuru, Kenya, assessed using swat and hydrometeorological indices. Hydrology, 6(4). https://doi.org/10.3390/HYDROLOGY6040088

  • Kolluru, V., Kolluru, S., & Konkathi, P. (2020). Evaluation and integration of reanalysis rainfall products under contrasting climatic conditions in India. Atmospheric Research, 246(May), 105121. https://doi.org/10.1016/j.atmosres.2020.105121

    Article  Google Scholar 

  • Koren, V. I., Finnerty, B. D., Schaake, J. C., Smith, M. B., Seo, D. J., & Duan, Q. Y. (1999). Scale dependencies of hydrologic models to spatial variability of precipitation. Journal of Hydrology, 217(3–4), 285–302. https://doi.org/10.1016/S0022-1694(98)00231-5

    Article  Google Scholar 

  • Koycegiz, C., & Buyukyildiz, M. (2019). Calibration of SWAT and two data-driven models for a data-scarce mountainous headwater in semi-arid Konya closed basin. Water, 11(1), 147. https://doi.org/10.3390/w11010147

    Article  Google Scholar 

  • Kumar, D., & Bhattacharjya, R. K. (2021). Change in rainfall patterns in the hilly region of Uttarakhand due to the impact of climate change. Applied Environmental Research, 43(1), 1–13. https://doi.org/10.35762/AER.2021.43.1.1

    Article  Google Scholar 

  • Kumar, M., Marks, D., Dozier, J., Reba, M., & Winstral, A. (2013). Evaluation of distributed hydrologic impacts of temperature-index and energy-based snow models. Advances in Water Resources, 56, 77–89. https://doi.org/10.1016/j.advwatres.2013.03.006

    Article  Google Scholar 

  • Kustas, W. P., Rango, A., & Uijlenhoet, R. (1994). A simple energy budget algorithm for the snowmelt runoff model. Water Resources Research, 30(5), 1515–1527. https://doi.org/10.1029/94WR00152

    Article  Google Scholar 

  • Larbi, I., Nyamekye, C., Dotse, S. Q., Danso, D. K., Annor, T., Bessah, E., et al. (2022). Rainfall and temperature projections and the implications on streamflow and evapotranspiration in the near future at the Tano River Basin of Ghana. Scientific African, 15, e01071. https://doi.org/10.1016/j.sciaf.2021.e01071

    Article  CAS  Google Scholar 

  • Lévesque, É., Anctil, F., Van Griensven, A., & Beauchamp, N. (2008). Evaluation of streamflow simulation by SWAT model for two small watersheds under snowmelt and rainfall. Hydrological Sciences Journal, 53(5), 961–976. https://doi.org/10.1623/hysj.53.5.961

    Article  Google Scholar 

  • Marahatta, S., Devkota, L., & Aryal, D. (2021). Hydrological modeling: A Better alternative to empirical methods for monthly flow estimation in ungauged basins. Journal of Water Resource and Protection, 13(03), 254–270. https://doi.org/10.4236/jwarp.2021.133015

    Article  Google Scholar 

  • Merwade, V., & Rajib, A. (2014). Setting up a SWAT Model with ArcSWAT. School of Civil Engineering: Purdue University.

    Google Scholar 

  • Mishra, Y., Nakamura, T., Babel, M. S., Ninsawat, S., & Ochi, S. (2018). Impact of climate change on water resources of the Bheri River Basin, Nepal. Water (Switzerland), 10(2), 1–21. https://doi.org/10.3390/w10020220

    Article  CAS  Google Scholar 

  • Moriasi, D. N., Gitau, M. W., Pai, N., & Daggupati, P. (2015). Hydrologic and water quality models: Performance measures and evaluation criteria. Transactions of the ASABE, 58(6), 1763–1785. https://doi.org/10.13031/trans.58.10715

    Article  Google Scholar 

  • Narsimlu, B., Gosain, A. K., & Chahar, B. R. (2013). Assessment of future climate change impacts on water resources of upper Sind River Basin, India using SWAT model. Water Resources Management, 27(10), 3647–3662. https://doi.org/10.1007/s11269-013-0371-7

    Article  Google Scholar 

  • Natumanya, E., Ribeiro, N., Mwanjalolo, M. J. G., & Steinbruch, F. (2022). Using SWAT model and field data to determine potential of NASA-POWER data for modelling rainfall-runoff in Incalaue River Basin. Computational Water, Energy, and Environmental Engineering, 11(02), 65–83. https://doi.org/10.4236/cweee.2022.112004

    Article  Google Scholar 

  • Neitsch, S., Arnold, J., Kiniry, J., & Williams, J. (2011). Soil & Water Assessment Tool Theoretical Documentation Version 2009. Texas Water Resources Institute, 1–647. https://doi.org/10.1016/j.scitotenv.2015.11.063

  • Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Srinivasan, R., & Williams, J. R. (2002). Soil and Water Assessment Tool User’s Manual. TWRI Report TR, 192, 412 http://swat.tamu.edu/media/1294/swatuserman.pdf

    Google Scholar 

  • Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Williams, J. R., & King, K. W. (2005). Soil and water assessment tool theoretical documentation version 2005. In Grassland, soil and water research laboratory (Vol. 1, p. 494). Agricultural Research Service, Blackland Research Center, Texas Agricultural Experiment Station, Texas.

  • Nyeko, M., D’Urso, G., & Immerzeel, W. W. (2013). Adaptive simulation of the impact of changes in land use on water resources in the lower Aswa basin. Journal of Agricultural Engineering, 43(4), 24. https://doi.org/10.4081/jae.2012.e24

    Article  Google Scholar 

  • Omani, N., Srinivasan, R., Karthikeyan, R., & Smith, P. K. (2017). Hydrological modeling of highly glacierized basins (Andes, Alps, and Central Asia). Water (Switzerland), 9(2). https://doi.org/10.3390/w9020111

  • Pathak, S., Ojha, C. S. P., Shukla, A. K., & Garg, R. D. (2019). Assessment of annual water-balance models for diverse Indian watersheds. Journal of Sustainable Water in the. Built Environment, 5(3). https://doi.org/10.1061/jswbay.0000881

  • Pignotti, G., Rathjens, H., Cibin, R., Chaubey, I., & Crawford, M. (2017). Comparative analysis of HRU and grid-based SWAT models. Water (Switzerland), 9(4), 272. https://doi.org/10.3390/w9040272

    Article  Google Scholar 

  • Prakash, A. (2020). Retreating Glaciers and water flows in the Himalayas: Implications for governance. Observer Research Foundation, 400, 14.

    Google Scholar 

  • Rahman, K., Maringanti, C., Beniston, M., Widmer, F., & Abbaspour, K. (2013). Streamflow modeling in a highly managed mountainous glacier watershed using SWAT : The Upper Rhone River watershed case in Switzerland (pp. 323–339). https://doi.org/10.1007/s11269-012-0188-9

    Book  Google Scholar 

  • Rahman, M. T., Aldosary, A. S., & Mortoja, G. (2017). Modeling Future Land Cover Changes and Their Effects on the Land Surface Temperatures in the Saudi Arabian Eastern Coastal City of Dammam. https://doi.org/10.3390/land6020036

    Book  Google Scholar 

  • Rango, A., & Martinec, J. (1995). Revisiting the degree-day method for snowmelt computations. JAWRA Journal of the American Water Resources Association, 31(4), 657–669. https://doi.org/10.1111/j.1752-1688.1995.tb03392.x

    Article  Google Scholar 

  • Rautela, K. S., Kumar, D., Rajeev Gandhi, B. G., Kumar, A., & Dubey, A. K. (2023). Long-term hydrological simulation for the estimation of snowmelt contribution of Alaknanda River Basin, Uttarakhand using SWAT. Aqua Water Infrastructure, Ecosystems and Society, 72(2), 139–159. https://doi.org/10.2166/aqua.2023.176

    Article  Google Scholar 

  • Riggs, G., Hall, D., & Salomonson, V. (2006). MODIS snow products user guide to collection 5. Digital Media, 6, 1–80 http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:MODIS+Snow+Products+User+Guide+to+Collection+5#0

    Google Scholar 

  • Samie, M., Ghazavi, R., Vali, A., & Pakparvar, M. (2019). Evaluation of the effect of land use change on runoff using supervised classified satellite data. Global Nest Journal, 21(2), 245–252. https://doi.org/10.30955/gnj.002631

    Article  Google Scholar 

  • Satriagasa, M. C., Tongdeenok, P., & Kaewjampa, N. (2023). Assessing the implication of climate change to forecast future flood using SWAT and HEC-RAS Model under CMIP5 Climate Projection in Upper Nan Watershed. Thailand. Sustainability, 15(6), 5276. https://doi.org/10.3390/su15065276

    Article  Google Scholar 

  • Şengül, S., & İspirli, M. N. (2022). Predicting snowmelt runoff at the source of the mountainous Euphrates river basin in Turkey for water supply and flood control issues using HEC-HMS modeling. Water, 14(3), 284. https://doi.org/10.3390/w14030284

    Article  Google Scholar 

  • Sharannya, T. M., Al-Ansari, N., Barma, S. D., & 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 (Switzerland), 12(9). https://doi.org/10.3390/w12092400

  • Shrestha, S., Shrestha, M., & Shrestha, P. K. (2018). Evaluation of the SWAT model performance for simulating river discharge in the himalayan and tropical basins of Asia. Hydrology Research, 49(3), 846–860. https://doi.org/10.2166/nh.2017.189

    Article  Google Scholar 

  • Shukla, A. K., Ojha, C. S. P., Mijic, A., Buytaert, W., Pathak, S., Garg, R. D., & Shukla, S. (2018a). Population growth, land use and land cover transformations, and water quality nexus in the Upper Ganga River basin. Hydrology and Earth System Sciences, 22(9), 4745–4770. https://doi.org/10.5194/hess-22-4745-2018

    Article  Google Scholar 

  • Shukla, A. K., Pathak, S., Pal, L., Ojha, C. S. P., Mijic, A., & Garg, R. D. (2018b). Spatio-temporal assessment of annual water balance models for upper Ganga Basin. Hydrology and Earth System Sciences, 22(10), 5357–5371. https://doi.org/10.5194/hess-22-5357-2018

    Article  Google Scholar 

  • Shukla, A. K., Ojha, C. S. P., Garg, R. D., Shukla, S., & Pal, L. (2020). Influence of spatial urbanization on hydrological components of the Upper Ganga River Basin, India. Journal of Hazardous, Toxic, and Radioactive Waste, 24(4), 1–19. https://doi.org/10.1061/(asce)hz.2153-5515.0000508

    Article  Google Scholar 

  • Shukla, A. K., Ojha, C. S. P., Mijic, A., Buytaert, W., Pathak, S., Garg, R. D., & Shukla, S. (2018). Population growth, land use and land cover transformations, and water quality nexus in the Upper Ganga River basin. Hydrology and Earth System Sciences, 22(9), 4745–4770. https://doi.org/10.5194/hess-22-4745-2018

    Article  Google Scholar 

  • Siderius, C., Biemans, H., Wiltshire, A., Rao, S., Franssen, W. H. P., Kumar, P., et al. (2013). Science of the Total Environment Snowmelt contributions to discharge of the Ganges. Science of the Total Environment, 468-469, S93–S101. https://doi.org/10.1016/j.scitotenv.2013.05.084

    Article  CAS  Google Scholar 

  • 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

    Article  Google Scholar 

  • Smith, M. B., Koren, V. I., Zhang, Z., Reed, S. M., Pan, J. J., & Moreda, F. (2004). Runoff response to spatial variability in precipitation: An analysis of observed data. Journal of Hydrology, 298(1–4), 267–286. https://doi.org/10.1016/j.jhydrol.2004.03.039

    Article  Google Scholar 

  • Stehr, A., Debels, P., Arumi, J. L., Romero, F., & Alcayaga, H. (2009). Combinaison du modèle SWAT et de l’imagerie MODIS pour estimer les débits mensuels dans un bassin disposant de peu de données des Andes Chiliennes. Hydrological Sciences Journal, 54(6), 1053–1067. https://doi.org/10.1623/hysj.54.6.1053

    Article  Google Scholar 

  • Storm, B., & Refsgaard, A. (1996). Distributed physically-based modelling of the entire land phase of the hydrological cycle. Distributed hydrological modelling (pp. 55–69). Dordrecht: Springer, Netherlands.

    Google Scholar 

  • Sun, H., Cornish, P. S., & Daniell, T. M. (2002). Spatial Variability in hydrologic modeling using rainfall-runoff model and digital elevation model. Journal of Hydrologic Engineering, 7(6), 404–412. https://doi.org/10.1061/(asce)1084-0699(2002)7:6(404)

    Article  Google Scholar 

  • Swain, S., Mishra, S. K., Pandey, A., Pandey, A. C., Jain, A., Chauhan, S. K., & Badoni, A. K. (2022). Hydrological modelling through SWAT over a Himalayan catchment using high-resolution geospatial inputs. Environmental Challenges, 8(July), 100579. https://doi.org/10.1016/j.envc.2022.100579

    Article  Google Scholar 

  • Taia, S., Erraioui, L., Arjdal, Y., Chao, J., El Mansouri, B., & Scozzari, A. (2023). The application of SWAT model and remotely sensed products to characterize the dynamic of streamflow and snow in a mountainous watershed in the High Atlas. Sensors, 23(3). https://doi.org/10.3390/s23031246

  • Thakur, A., Sharma, A., Thakural, L. N., & Chandra, P. (2021). Application of soil water assessment tool (SWAT) for hilly region of Tons river basin. Journal of Indian Water Resources Society, 41(3), 3–6.

    Google Scholar 

  • Udoh, I. Ben Eyoefen, I., & Ekpa, A. U. (2023). Journal OF ENVIRONMENTAL DESIGN (JED), (June).

  • USDA-SCS. (1972). Revisions by. National Engineering Handbook, (August), 172 https://directives.sc.egov.usda.gov/OpenNonWebContent.aspx?content=18393.wba

  • Venkatesh, K., Krakauer, N. Y., Sharifi, E., & Ramesh, H. (2020). Evaluating the performance of secondary precipitation products through statistical and hydrological modeling in a mountainous tropical basin of India. Advances in Meteorology, 2020. https://doi.org/10.1155/2020/8859185

  • Wang, X., & Melesse, A. M. (2005). Swat m, 48(4), 1359–1376.

    Google Scholar 

  • Wang, X., & Melesse, A. M. (2006). Effects of STATSGO and SSURGO as inputs on SWAT model’s snowmelt simulation. Journal of the American Water Resources Association, 42(5), 1217–1236. https://doi.org/10.1111/j.1752-1688.2006.tb05296.x

    Article  Google Scholar 

  • Wang, Y., Jiang, R., Xie, J., Zhao, Y., Yan, D., & Yang, S. (2019). Soil and water assessment tool (SWAT) model: A systemic review. Journal of Coastal Research, 93(sp1), 22–30. https://doi.org/10.2112/SI93-004.1

    Article  Google Scholar 

  • WMO. (2018). Guide to climatological practices 2018 edition.

  • Woldemeskel, F. M., Sivakumar, B., & Sharma, A. (2013). Merging gauge and satellite rainfall with specification of associated uncertainty across Australia. Journal of Hydrology, 499, 167–176. https://doi.org/10.1016/j.jhydrol.2013.06.039

    Article  Google Scholar 

  • Xie, H., Longuevergne, L., Ringler, C., & Scanlon, B. R. (2012). Calibration and evaluation of a semi-distributed watershed model of Sub-Saharan Africa using GRACE data. Hydrology and Earth System Sciences, 16(9), 3083–3099. https://doi.org/10.5194/hess-16-3083-2012

    Article  Google Scholar 

  • Yang, J., Reichert, P., Abbaspour, K. C., Xia, J., & Yang, H. (2008). Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China. Journal of Hydrology, 358(1–2), 1–23. https://doi.org/10.1016/j.jhydrol.2008.05.012

    Article  Google Scholar 

  • Yankey, B. E., Gyamfi, C., Arthur, E., Dekongmen, B. W., Asantewaa-Tannor, P., Tawiah, J. K., & Mends, L. G. (2023). Small hydropower development potential in the Densu River Basin, Ghana. Journal of Hydrology. Regional Studies, 45(November 2022), 101304. https://doi.org/10.1016/j.ejrh.2022.101304

    Article  Google Scholar 

  • Yapo, P. O., Gupta, H. V., & Sorooshian, S. (1996). Automatic calibration of conceptual rainfall-runoff models: Sensitivity to calibration data. Journal of Hydrology, 181(1–4), 23–48. https://doi.org/10.1016/0022-1694(95)02918-4

    Article  CAS  Google Scholar 

  • Yu, M., Chen, X., Li, L., Bao, A., & Paix, M. J. D. L. (2011). Streamflow simulation by SWAT using different precipitation sources in large arid basins with scarce raingauges. Water Resources Management, 25, 2669–2681. https://doi.org/10.1007/s11269-011-9832-z

    Article  Google Scholar 

  • Zhang, X., Srinivasan, R., Debele, B., & Hao, F. (2008). Runoff simulation of the headwaters of the yellow river using the SWAT model with three snowmelt algorithms. Journal of the American Water Resources Association, 44(1), 48–61. https://doi.org/10.1111/j.1752-1688.2007.00137.x

    Article  Google Scholar 

  • Zhao, H., Li, H., Xuan, Y., Li, C., & Ni, H. (2022). Improvement of the SWAT model for snowmelt runoff simulation in seasonal snowmelt area using remote sensing data. Remote Sensing, 14(22). https://doi.org/10.3390/rs14225823

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Acknowledgements

The authors are thankful for the Discharge data supplied by Central Water Commission, NASA, and USGS for providing freely available data for research. Also, the authors are thankful to the anonymous reviewers for their insights and guidance.

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  1. Department of Civil Engineering, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, West Bengal, India

    Soumyadip Biswas & Sujata Biswas

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Soumyadip Biswas conceived the problem, collected the data, prepared the methodology, conducted the formal analysis, and wrote the original draft.

Sujata Biswas contributed to collecting data, dictating research, editing the manuscript, and supervising.

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Biswas, S., Biswas, S. Estimation of monthly snowmelt contribution to runoff using gridded meteorological data in SWAT model for Upper Alaknanda River Basin, India. Environ Monit Assess 196, 86 (2024). https://doi.org/10.1007/s10661-023-12236-z

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