Abstract
The hydrology of Himalayan region is influenced by temperature lapse rate (TLAPS) and precipitation lapse rate (PLAPS). Therefore, hydrological modeling considering TLAPS and PLAPS is crucial to manage the water resources in these terrains. In this research, Himalayan Gandak River basin is considered as the study area where TLAPS and PLAPS vary significantly due to high altitude of Himalayas. To assess the impact of TLAPS and PLAPS on water balance components, Soil Water Assessment Tool (SWAT) model was calibrated (2000–2007) and validated (2008–2014) on daily time step for three projects i.e., Reference Project (RP), Snowmelt Project (SP) and distributed elevation band snowmelt project (SWAT-ETISM). The analysis discloses that SWAT-ETISM model (which has TLAPS and PLAPS parameters) outperforms the RP and the SP models in predicting streamflow with improved statistical indicators R2 =0.88, NSE =0.84 and PBIAS = 11.9. Furthermore, it was observed that SWAT-ETISM model comprehensively improved the streamflow statistics by improving the snow water equivalent and water balance components through the consideration of TLAPS and PLAPS values for the region. Hence, the proposed SWAT-ETISM model can be used for estimation of the water budget at the high-altitude and data scarce alpine Himalayan regions and worldwide, where PLAPS and TLAPS are substantial due to altitudinal variation.
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References
Abbaspour KC (2015) SWAT-CUP 2012: SWAT calibration and uncertainty programs — A user manual. Eawag Swishs Fed Inst Aquat Sci Technol. https://swat.tamu.edu/media/114860/usermanual_swatcup.pdf
Andermann C, Longuevergne L, Bonnet S, et al. (2012) Impact of transient groundwater storage on the discharge of Himalayan rivers. Nat Geosci 5: 127–132. https://doi.org/10.1038/ngeo1356
Arnold JG, Kiniry JR, Srinivasan R, et al. (2013) Soil & Water Assessment Tool: Input/output documentation. version 2012. Texas Water Resour Institute, TR-439 650. https://swat.tamu.edu/media/69296/swat-io-documentation-2012.pdf
Brown L, Thorne R, Woo M (2008) Using satellite imagery to validate snow distribution simulated by a hydrological model in large northern basins. Hydrol Process 22(15): 2777–2787. https://doi.org/10.1002/hyp.6999
Brown ME, Racoviteanu AE, Tarboton DG, et al. (2014) An integrated modeling system for estimating glacier and snow melt driven streamflow from remote sensing and earth system data products in the Himalayas. J Hydrol 519: 1859–1869. https://doi.org/10.1016/j.jhydrol.2014.09.050
Brun F, Dumont M, Wagnon P, et al. (2015) Seasonal changes in surface albedo of Himalayan glaciers from MODIS data and links with the annual mass balance. Cryosph 9(1): 341–355. https://doi.org/10.5194/tc-9-341-2015
Chen JJ, Liao A, Cao X, et al. (2015) Global land cover mapping at 30 m resolution: A POK-based operational approach. ISPRS J Photogramm Remote Sens 103: 7–27. https://doi.org/10.1016/j.isprsjprs.2014.09.002
Dahal RK, Hasegawa S, Masuda T, et al. (2006) Roadside slope failures in nepal during torrential rainfall and their mitigation. Disaster Mitigation of Debris Flows, Slope Failures and Landslides. Universal Academy Press, Inc., Tokyo, Japan, pp. 503–514.
Debele B, Srinivasan R, Gosain AK (2010) Comparison of process-based and temperature-index snowmelt modeling in SWAT. Water Resour Manag 24(6): 1065–1088. https://doi.org/10.1007/s11269-009-9486-2
Devkota LP, Gyawali DR (2015) Impacts of climate change on hydrological regime and water resources management of the Koshi River Basin, Nepal. J Hydrol Reg Stud 4: 502–515. https://doi.org/10.1016/j.ejrh.2015.06.023
Dwyer J, Schmidt G (2006) The MODIS reprojection tool. Earth Science Satellite Remote Sensing, Springer, Berlin, Heidelberg. pp 162–177. https://doi.org/10.1007/978-3-540-37294-3_9
Gerlitz L, Bechtel B, Böhner J, et al. (2016) Analytic Comparison of Temperature Lapse Rates and Precipitation Gradients in a Himalayan Treeline Environment: Implications for Statistical Downscaling. In: Singh, R., Schickhoff, U., Mal, S. (eds.), Climate Change, Glacier Response, and Vegetation Dynamics in the Himalaya. Springer, Cham. pp 49–64 https://doi.org/10.1007/978-3-319-28977-9_3
GFCC (2015) Summary Recommendations of Comprehensive Master Plans. Available online at: http://gfcc.gov.in/sites/default/files/SR-CMP-2015.pdf (Accessed on 6 June 2019)
Grunewald T, Buhler Y, Lehning M (2014) Elevation dependency of mountain snow depth. Cryosphere 8(6): 2381–2394. https://doi.org/10.5194/tc-8-2381-2014
Grusson Y, Sun X, Gascoin S, Sauvage S, Raghavan S, Anctil F, et al. (2015) Assessing the capability of the SWAT model to simulate snow, snow melt and streamflow dynamics over an alpine watershed. J Hydrol 531: 574–588 https://doi.org/10.1016/j.jhydrol.2015.10.070
Hock R (2003) Temperature index melt modelling in mountain areas. J Hydrol 282: 104–115. https://doi.org/10.1016/S0022-1694(03)00257-9
Immerzeel WW, Petersen L, Ragettli S, et al. (2014) The importance of observed gradients of air temperature and precipitation for modeling runoff from a glacierized watershed in the Nepalese Himalayas. Water Resour Res 50(3): 2212–2226. https://doi.org/10.1002/2013WR014506
Jain SK (2015) Assessment of environmental flow requirements for hydropower projects in India. Curr Sci 108(10): 1815–1825. https://www.currentscience.ac.in/Volumes/108/10/1815.pdf
Jain SK, Goswami A, Saraf AK (2008) Accuracy assessment of MODIS, NOAA and IRS data in snow cover mapping under Himalayan conditions. Int J Remote Sens 29(20): 5863–5878. https://doi.org/10.1080/01431160801908129
Jarvis A, Reuter HI, Nelson A, et al. (2008) Hole-filled SRTM for the globe version 4. http://srtm.csi.cgiar.org (Accessed on 6 June 2019)
Kattel DB, Yao T, Yang K, et al. (2013) Temperature lapse rate in complex mountain terrain on the southern slope of the central Himalayas. Theor Appl Climatol 113: 671–682. https://doi.org/10.1007/s00704-012-0816-6
Klein AG, Barnett AC (2003) Validation of daily MODIS snow cover maps of the Upper Rio Grande River Basin for the 2000–2001 snow year. Remote Sens Environ 86(2): 162–176. https://doi.org/10.1016/S0034-4257(03)00097-X
Kumar B, Lakshmi V (2018) Accessing the capability of TRMM 3B42 V7 to simulate streamflow during extreme rain events: Case study for a Himalayan River Basin. J Earth Syst Sci 127(2): 1–15. https://doi.org/10.1007/s12040-018-0928-1
Kumar B, Lakshmi V, Patra KC (2017a) Evaluating the uncertainties in the SWAT model outputs due to DEM grid size and resampling techniques in a large Himalayan river basin. J Hydrol Eng 22(9): 1–12. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001569
Kumar B, Patra KC, Lakshmi V (2017b). Error in digital network and basin area delineation using d8 method: A case study in a sub-basin of the Ganga. J Geol Soc India 89(1): 65–70. https://doi.org/10.1007/s12594-017-0559-1
Kumar B, Patra KC, Lakshmi V (2016) Daily rainfall statistics of TRMM and CMORPH: A case for trans-boundary Gandak River basin. J Earth Syst Sci 125(5): 919–934. https://doi.org/10.1007/s12040-016-0710-1
Kushwaha A, Jain MK (2013) Hydrological simulation in a forest dominated watershed in Himalayan Region using SWAT model. Water Resour Manag 27(8): 3005–3023. https://doi.org/10.1007/s11269-013-0329-9
Lambert L, Chitrakar BD (1989) Variation of potential evapotranspiration with elevation in Nepal. Mt Res Dev 9(2): 145–152. https://doi.org/10.2307/3673477
Luo Y, Arnold J, Liu S, et al. (2013) Inclusion of glacier processes for distributed hydrological modeling at basin scale with application to a watershed in Tianshan Mountains, northwest China. J Hydrol 477: 72–85. https://doi.org/10.1016/j.jhydrol.2012.11.005
Martinec J (1975) Snowmelt — Runoff model for stream flow forecasts. Hydrol Res 6(3): 145–154. https://doi.org/10.2166/nh.1975.0010
Maskey S, Uhlenbrook S, Ojha S (2011) An analysis of snow cover changes in the Himalayan region using MODIS snow products and in-situ temperature data. Clim Change 108: 391–400. https://doi.org/10.1007/s10584-011-0181-y
McKay MD, Beckman RJ, Conover WJ (1979) A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 21(2): 239–245. https://doi.org/10.2307/1268522
Meng XY, Yu DL, Liu ZH (2015) Energy balance-based SWAT model to simulate the mountain snowmelt and runoff taking the application in Juntanghu watershed (China) as an example. J Mt Sci 12(2): 368–381. https://doi.org/10.1007/s11629-014-3081-6
Mishra P, Zaphu VV, Monica N, et al. (2016) Accuracy assessment of MODIS fractional snow cover product for eastern Himalayan catchment. J Indian Soc Remote Sens 44(6): 977–985 https://doi.org/10.1007/s12524-016-0548-7
Neitsch S, Arnold J, Kiniry J, et al. (2011) Soil & Water Assessment Tool Theoretical Documentation Version 2009. Texas Water Resour. Institute, TR-406 1–647. https://swat.tamu.edu/media/99192/swat2009-theory.pdf
Parajka J, Blöschl G (2008) Spatio-temporal combination of MODIS images — potential for snow cover mapping. Water Resour Res 44(3): W03406. https://doi.org/10.1029/2007WR006204
Pellicciotti F, Buergi C, Immerzeel WW, et al. (2012) Challenges and uncertainties in hydrological modeling of remote Hindu Kush-Karakoram-Himalayan (HKH) basins: Suggestions for calibration strategies. Mt Res Dev 32(1): 39–50. https://doi.org/10.1659/MRD-JOURNAL-D-11-00092.1
Pradhanang SM, Anandhi A, Mukundan R, et al. (2011) Application of SWAT model to assess snowpack development and streamflow in the Cannonsville watershed, New York, USA. Hydrol Process 25(21): 3268–3277. https://doi.org/10.1002/hyp.8171
Rahman K, Maringanti C, Beniston M, et al. (2013) Streamflow modeling in a highly managed mountainous glacier watershed using SWAT: The upper Rhone River watershed case in Switzerland. Water Resour Manag 27(2): 323–339. https://doi.org/10.1007/s11269-012-0188-9
Rex VC, Hideo H, Murari L, et al. (2007) Asia. In: Parry, M., Canziani, O., Palutikof, J. (Ed.), Climate Change 2007: Impacts, Adaptation and Vulnerability. Cambridge University Press, New York. pp 469–506. https://www.ipcc.ch/site/assets/uploads/2018/03/ar4_wg2_full_report.pdf
Rohrer M, Salzmann N, Stoffel M, et al. (2013) Missing (in-situ) snow cover data hampers climate change and runoff studies in the Greater Himalayas. Sci Total Environ 468–469: S60–S70. https://doi.org/10.1016/j.scitotenv.2013.09.056
Saha S, Moorthi S, Wu X, et al. (2014) The NCEP climate forecast system version 2. J Clim 27(6): 2185–2208. https://doi.org/10.1175/JCLI-D-12-00823.1
Sen Gupta A., Tarboton DG, Hummel P, et al. (2015) Integration of an energy balance snowmelt model into an open source modeling framework. Environ Model Softw 68: 205–218. https://doi.org/10.1016/j.envsoft.2015.02.017
Shrestha M, Wang L, Koike T, et al. (2012) Modeling the spatial distribution of snow cover in the dudhkoshi region of the Nepal Himalayas. J Hydrometeorol 13(1): 204–222. https://doi.org/10.1175/JHM-D-10-05027.1
Siderius C, Biemans H, Wiltshire A, et al. (2013) Snowmelt contributions to discharge of the Ganges. Sci Total Environ 468: S93–S101. https://doi.org/10.1016/j.scitotenv.2013.05.084
Wen R, Tian LD, Weng YB, et al. (2012) The altitude effect of δ18 O in precipitation and river water in the Southern Himalayas. Chinese Sci Bull 57(14): 1693–1698. https://doi.org/10.1007/s11434-012-4992-7
Yang J, Gong P, Fu R, et al. (2013) The role of satellite remote sensing in climate change studies. Nat Clim Chang 3: 875–883. https://doi.org/10.1038/nclimate1908
Yang J, Reichert P, Abbaspour KC, et al. (2008) Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China. J Hydrol 358: 1–23. https://doi.org/10.1016/j.jhydrol.2008.05.012
Yatagai A, Kamiguchi K, Arakawa O, et al. (2012) Aphrodite constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bull Am Meteorol Soc 93(9): 1401–1415. https://doi.org/10.1175/BAMS-D-11-00122.1
Zhang F, Zhang H, Hagen SC, et al. (2015) Snow cover and runoff modelling in a high mountain catchment with scarce data: effects of temperature and precipitation parameters. Hydrol Process 29(1): 52–65. https://doi.org/10.1002/hyp.10125
Acknowledgements
Authors would like to acknowledge Central Water Commission (CWC), India and Department of Hydrology and Metrology (DHM), Nepal for providing the necessary data for this research work. Also, this research has received no grant from any funding agency in the public, commercial, or not-forprofit sectors.
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Kumar, B., Roy, D. & Lakshmi, V. Impact of temperature and precipitation lapse rate on hydrological modelling over Himalayan Gandak River Basin. J. Mt. Sci. 19, 3487–3502 (2022). https://doi.org/10.1007/s11629-020-6602-5
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DOI: https://doi.org/10.1007/s11629-020-6602-5