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Projected Discharge of Dudhnai River: A Tributary of the Brahmaputra River

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Abstract

The present study assessed the impact of climate change on the discharge of a mountainous watershed—Dudhnai, India, using the Soil and Water Assessment Tool (SWAT). First, the SWAT model was calibrated and validated using rainfall and observed discharge data. Then, bias-corrected meteorological data from four climate models (CCSM4, CNRM-CM5, MPI-ESM-LR, and NorESM1-M) from two emission scenarios (RCPs 4.5 & 8.5) were used to predict future discharge. The model efficiencies and per cent bias indicated that the SWAT model was subpar (NSE = 0.54) at daily timescale, however, performed better at monthly timescale with an NSE of 0.70. According to the ensemble of climate models, in comparison with the baseline discharge scenario, the discharge in the watershed was projected to increase towards the end of the century by about 16.6% under RCP 4.5 and 27.5% under RCP 8.5. The mean monthly variation of discharge in the Dudhnai indicated that monsoonal discharge would increase in the future, while cases of a decrease in discharge were observed during lean flow periods, particularly during November to March. The rate of increase in the surface flow component was found significantly greater than the lateral and groundwater flow components. Results imply that the Dudhnai watershed would be subjected to severe hydrological events in the future. Despite the potential growth of water resources, their distribution patterns may cause water scarcity in the watershed, especially during dry seasons.

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References

  • Abbaspour, K. C. (2015). SWAT-CUP: SWAT calibration and uncertainty programs—a user manual. Eawag, Swiss Federal Institute of Aquatic Science and Technology.

    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 

  • Afshar, A. A., Hasanzadeh, Y., Besalatpour, A. A., & Pourreza-Bilondi, M. (2017). Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways. Theoritical and Applied Climatology, 129, 683–699. https://doi.org/10.1007/s00704-016-1908-5

    Article  Google Scholar 

  • Agyekum, J., Annor, T., Lamptey, B., Quansah, E., & Agyeman, R. Y. K. (2018). Evaluation of CMIP5 global climate models over the Volta Basin: Precipitation. Advances in Meteorology. https://doi.org/10.1155/2018/4853681

    Article  Google Scholar 

  • Ahmed, K., Sachindra, D. A., Shahid, S., Demirel, M. C., & Chung, E. S. (2018). Selection of multi-model ensemble of GCMs for the simulation of precipitation based on spatial assessment metrics. Hydrology and Earth Syestem Sciences, 23, 4803–4824. https://doi.org/10.5194/hess-23-4803-2019

    Article  Google Scholar 

  • Ahmed, K., Shahid, S., Sachindra, D. A., Nawaz, N., & Chung, E. S. (2019). Fidelity assessment of general circulation model simulated precipitation and temperature over Pakistan using a feature selection method. Journal of Hydrology, 573, 281–298. https://doi.org/10.1016/j.jhydrol.2019.03.092

    Article  Google Scholar 

  • Anand, V., & Oinam, B. (2019). Future climate change impact on hydrological regime of river basin using SWAT model. Global Journal of Environmental Science and Management, 5(4), 471–484. https://doi.org/10.22034/GJESM.2019.04.07

    Article  Google Scholar 

  • Apurv, T., Mehrotra, R., Sharma, A., Goyal, M. K., & Dutta, S. (2015). Impact of climate change on floods in the Brahmaputra basin using CMIP5 decadal predictions. Journal of Hydrology, 527, 281–291. https://doi.org/10.1016/j.jhydrol.2015.04.056

    Article  Google Scholar 

  • Arabi, M., Frankenberger, J. A., Engel, B. A., & Arnold, J. G. (2008). Representation of agricultural conservation practices with SWAT. Hydrological Processes, 22, 3042–3055. https://doi.org/10.1002/hyp.6890

    Article  Google Scholar 

  • Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Williams, J. R. (1998). Large-area hydrologic modeling and assessment: Part I: Model development. Journal of the American Water Resources Association, 34(1), 73–89. https://doi.org/10.1111/j.1752-1688.1998.tb05961.x

    Article  Google Scholar 

  • Bannister, D., Herzog, M., Graf, H. F., Hosking, J. S., & Short, C. A. (2017). An assessment of recent and future temperature change over the Sichuan Basin, China, using CMIP5 climate models. Journal of Climate, 30, 6701–6722. https://doi.org/10.1175/JCLI-D-16-0536.1

    Article  Google Scholar 

  • Basheer, A. K., Haishen, L., Omer, A., Ali, A. B., & Abdelgader, M. S. A. (2015). Impacts of climate change under CMIP5 RCP scenarios on the streamflow in the Dinder River and ecosystem habitats in Dinder National Park, Sudan. Hydrology and Earth System Sciences, 20, 1331–1353. https://doi.org/10.5194/hess-20-1331-2016

    Article  Google Scholar 

  • Bhatta, B., Shrestha, S., Shrestha, P. K., & Talchabhadel, R. (2019). Evaluation and application of a SWAT model to assess the climate change impact on the hydrology of the Himalayan River Basin. CATENA, 181, 104082. https://doi.org/10.1016/j.catena.2019.104082

    Article  Google Scholar 

  • Bhattacharya, T., Khare, D., & Arora, M. (2019). A case study for the assessment of the suitability of gridded reanalysis weather data for hydrological simulation in Beas river basin of North Western Himalaya. Applied Water Science, 9, 110. https://doi.org/10.1007/s13201-019-0993-x

    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 & Assessment, 25, 861–883. https://doi.org/10.1007/s10666-020-09716-8

    Article  Google Scholar 

  • Chiphang, N., Bandyopadhyay, A., & Bhadra, A. (2022). Response assessment of hydrological processes to climate change using ArcSWAT in Mago basin of Eastern Himalaya. Journal of Earth System Science, 131, 252. https://doi.org/10.1007/s12040-022-02002-z

    Article  Google Scholar 

  • Dahal, V., Shakya, N. M., & Bhattarai, R. (2016). Estimating the impact of climate change on water availability in Bagmati basin, Nepal. Environmental Processes, 3, 1–17. https://doi.org/10.1007/s40710-016-0127-5

    Article  Google Scholar 

  • Das, B., Jain, S., Singh, S., & Thakur, P. (2019). Evaluation of multisite performance of SWAT model in the Gomti River basin, India. Applied Water Science, 9, 134. https://doi.org/10.1007/s13201-019-1013-x

    Article  Google Scholar 

  • Dutta, P., & Sarma, A. K. (2021). Hydrological modeling as a tool for water resources management of the data-scarce Brahmaputra basin. Journal of Water & Climate Change. https://doi.org/10.2166/wcc.2020.186

    Article  Google Scholar 

  • Eslamian, S. (2014). Handbook of engineering hydrology: Environmental hydrology and water management. CRC Press.

    Book  Google Scholar 

  • Fakhri, M., Dokouhaki, H., Eslamian, S. S., Fazeli Farsani, I., & Farzaneh, M. R. (2014). Flow and sediment transport modeling in rivers. In S. S. Eslamian (Ed.), Handbook of engineering hydrology, Ch. 13, Vol. 2: Modeling, climate change, and variability (pp. 233–267). Boca Raton: Taylor and Francis.

    Google Scholar 

  • Gassman, P. W., Reyes, M. R., Green, C. H., & Arnold, J. G. (2007). The soil and water assessment tool: Historical development, applications, and future research directions. American Society of Agricultural and Biological Engineers, 50(4), 1211–1250.

    Google Scholar 

  • Goyal, M. K., Panchariya, V. K., Sharma, A., & Singh, V. (2018). Comparative assessment of SWAT model performance in two distinct catchments under various DEM scenarios of varying resolution, sources and resampling methods. Water Resources Management, 32, 805–825. https://doi.org/10.1007/s11269-017-1840-1

    Article  Google Scholar 

  • Homsi, R., Shiru, M. S., Shahid, S., Ismail, T., Harun, S. B., Al-Ansari, N., Chau, K. W., & Yaseen, Z. M. (2020). Precipitation projection using a CMIP5 GCM ensemble model: A regional investigation of Syria. Engineering Applications of Computational Fluid Mechanics, 14, 90–106. https://doi.org/10.1080/19942060.2019.1683076

    Article  Google Scholar 

  • IPCC. (2007). Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. In S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, & H. L. Miller (Eds.), Cambridge University Press

  • Jena, P., Azad, S., & Rajeevan, M. N. (2016). CMIP5 projected changes in the annual cycle of Indian monsoon rainfall. Climate, 4, 14. https://doi.org/10.3390/cli4010014

    Article  Google Scholar 

  • Khwairakpam, E., Khosa, R., Gosain, A., Nema, A., Mathur, S., & Yadav, B. (2018). Modeling simulation of river discharge of loktak lake catchment in Northeast India. Journal of Hydrologic Engineering. https://doi.org/10.1061/(ASCE)HE.1943-5584.00016

    Article  Google Scholar 

  • Latif, M., Hannachi, A., & Syed, F. (2018). Analysis of rainfall trends over Indo-Pakistan summer monsoon and related dynamics based on CMIP5 climate model simulations. International Journal of Climatology, 38(S1), e577–e595. https://doi.org/10.1002/joc.5391

    Article  Google Scholar 

  • Le, T., & Bae, D. H. (2013). Evaluating the utility of IPCC AR4 GCMs for hydrological application in South Korea. Water Resources Management, 27, 3227–3246. https://doi.org/10.1007/s11269-013-0338-8

    Article  Google Scholar 

  • Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Binger, R. L., Harmel, R. D., & Veith, T. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the American Society of Agricultural and Biological Engineers, 50(3), 885–900.

    Google Scholar 

  • Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models. Part 1: A discussion of principles. Journal of Hydrology, 10(3), 282–290. https://doi.org/10.1016/0022-1694(70)90255-6

    Article  Google Scholar 

  • Ndomba, P. M., Mtalo, F. W., & Killingtveit, A. (2008). A guided swat model application on sediment yield modeling in pangani river basin: Lessons learnt. Journal of Urban and Environmental Engineering, 2(2), 53–62.

    Article  Google Scholar 

  • Ougahi, J. H., Karim, S., & Mahmood, S. A. (2022). Application of the SWAT model to assess climate and land use/cover change impacts on water balance components of the Kabul River basin, Afghanistan. Journal of Water and Climate Change, 13(11), 3977–3999. https://doi.org/10.2166/wcc.2022.261

    Article  Google Scholar 

  • Pai, D. S., Sridhar, L., Rajeevan, M., Sreejith, O. P., Satbhai, N. S., & Mukhopadhyay, B. (2014). Development of a new high spatial resolution (025° X 025°) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region. Mausam, 65(1), 1–18.

    Article  Google Scholar 

  • Pandey, B. K., Khare, D., Kawasaki, A., & Mishra, P. K. (2019). Climate change impact assessment on blue and green water by coupling of representative CMIP5 climate models with physical based hydrological model. Water Resources Management, 33, 141–158. https://doi.org/10.1007/s11269-018-2093-3

    Article  Google Scholar 

  • Panjwani, S., Naresh Kumar, S., Ahuja, L., & Islam, A. (2019). Prioritization of global climate models using fuzzy analytic hierarchy process and reliability index. Theoritical and Applied Climatology, 137, 2381–2392. https://doi.org/10.1007/s00704-018-2707-y

    Article  Google Scholar 

  • Quansah, J. E., Naliaka, A. B., Fall, S., Ankumah, R., & Afandi, G. E. (2021). Assessing future impacts of climate change on streamflow within the Alabama River basin. Climate, 9, 55. https://doi.org/10.3390/cli9040055

    Article  Google Scholar 

  • Roy, P. S., Meiyappan, P., Joshi, P. K., Kale, M. P., Srivastav, V. K., Srivasatava, S. K., Behera, M. D., Roy, A., Sharma, Y., Ramachandran, R. M., Bhavani, P., Jain, A. K., & Krishnamurthy, Y. V. N. (2016). Decadal Land use and land cover classifications across India, 1985, 1995, 2005. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1336

  • Ruan, Y., Yao, Z., Wang, R., & Liu, Z. (2018). Ranking of CMIP5 GCM skills in simulating observed precipitation over the Lower Mekong Basin, using an improved score-based method. Water, 10, 1868. https://doi.org/10.3390/w10121868

    Article  Google Scholar 

  • Saade, J., Atieh, M., Ghanimeh, S., & Golmohammadi, G. (2021). Modeling impact of climate change on surface water availability using SWAT model in a semi-arid basin: Case of El Kalb River, Lebanon. Hydrology, 8, 134. https://doi.org/10.3390/hydrology8030134

    Article  Google Scholar 

  • Singh, V., & Goyal, M. K. (2017). Curve number modifications and parameterization sensitivity analysis for reducing model uncertainty in simulated and projected streamflows in a Himalayan catchment. Ecological Engineering, 108, 17–29. https://doi.org/10.1016/j.ecoleng.2017.08.002

    Article  Google Scholar 

  • Singh, V. P., Jain, S. K., & Tyagi, A. (2007). Risk and reliability analysis: A handbook for civil and environmental engineers. American Society of Civil Engineers Press.

    Book  Google Scholar 

  • Srivastava, A. K., Rajeevan, M., & Kshirsagar, S. R. (2009). Development of high resolution daily gridded temperature data set (1969–2005) for the Indian region. Atmospheric Science Letters. https://doi.org/10.1002/asl.232

    Article  Google Scholar 

  • Tenagashaw, D. Y., Muluneh, M., Metaferia, G., & Mekonnen, Y. A. (2022). Land use and climate change impacts on streamflow using SWAT model, middle Awash Sub Basin, Ethiopia. Water Conservation Science and Engineering, 7, 183–196. https://doi.org/10.1007/s41101-022-00135-2

    Article  Google Scholar 

  • Wu, Y., Zhong, P., Xu, B., Zhu, F., & Fu, J. (2018). Evaluation of global climate model on performances of precipitation simulation and prediction in the Huaihe River basin. Theoritical and Applied Climatology, 133, 191–204. https://doi.org/10.1007/s00704-017-2185-7

    Article  Google Scholar 

  • Yang, Q., Zhang, X., Almendinger, J. E., Huang, M., Leng, G., Zhou, Y., Zhao, K., Asrar, G. R., Li, X., & Qiu, J. (2018). Improving the SWAT forest module for enhancing water resource projections: A case study in the St. Croix River basin. Hydrological Processes, 33(5), 864–875. https://doi.org/10.1002/hyp.13370

    Article  Google Scholar 

  • Zamani, R., & Berndtsson, R. (2019). Evaluation of CMIP5 models for west and southwest Iran using TOPSIS-based method. Theoritical and Applied Climatology, 137, 533–543. https://doi.org/10.1007/s00704-018-2616-0

    Article  Google Scholar 

  • Zang, C. F., Liu, J., van der Velde, M., & Kraxner, F. (2012). Assessment of spatial and temporal patterns of green and blue water flows under natural inland river basins in Northwest China. Hydrology and Earth System Sciences, 16, 2859–2870. https://doi.org/10.5194/hess-16-2859-2012

    Article  Google Scholar 

  • Zhang, W., Zha, X., Li, J., Liang, W., Ma, Y., Fan, D., & Li, S. (2014). Spatiotemporal change of blue water and green water resources in the Headwater of Yellow River Basin, China. Water Resources Management, 28(13), 4715–4732. https://doi.org/10.1007/s11269-014-0769-x

    Article  Google Scholar 

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Acknowledgements

The authors wish to show their appreciation to the Central Water Commission for providing the required hydrological data to carry out this research work.

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Correspondence to Swapnali Barman.

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Singh, W.R., Barman, S., Gogoi, S. et al. Projected Discharge of Dudhnai River: A Tributary of the Brahmaputra River. J Indian Soc Remote Sens 51, 2295–2309 (2023). https://doi.org/10.1007/s12524-023-01767-0

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