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Many reservoirs have been built throughout the globe to satisfy the various water demands and control floods. To represent the reservoirs in hydrological modelling, a reservoir module is developed based on the Concept of Storage Zoning (CSZ) and implemented in a newly developed National Hydrological Model-India (NHM-I). The developed reservoir module is calibrated and validated independently for the Sardar Sarovar dam over 2010-2014 and 2015-2020. Results show that the module can satisfactorily simulate the trend and temporal patterns of water levels and spills with observed inflows. The Nash Sutcliffe Efficiency (NSE) value is estimated as 0.90 and 0.91 for reservoir water level and 0.87 and 0.86 for reservoir spill-over during calibration and validation. Further, the integrated NHM-I model with the reservoir module is calibrated and validated for another catchment (Panchet catchment) in Damodar valley, India having Tenughat and Panchet reservoirs. Results demonstrate that the integrated model captures the reservoir inflows, outflows and storage levels satisfactorily with NSE values of 0.64, 0.89 and 0.88, respectively. Also, the model simulation results with and without the reservoir module show that the model performance improved by including the reservoir module. The integrated model will help assess the management practices adopted in a reservoir-regulated river basin for effective water management.
Słowa kluczowe
Wydawca
Czasopismo
Rocznik
Tom
Strony
2923--2940
Opis fizyczny
Bibliogr. 51 poz., rys., tab.
Twórcy
autor
- Department of Agricultural and Food Engineering, IIT Kharagpur, Kharagpur, West Bengal, 721302, India
autor
- Department of Agricultural and Food Engineering, IIT Kharagpur, Kharagpur, West Bengal, 721302, India
autor
- Department of Agricultural and Food Engineering, IIT Kharagpur, Kharagpur, West Bengal, 721302, India
autor
- Division of Water Resources Systems, National Institute of Hydrology, Roorkee, Uttarakhand, 247667, India
autor
- Department of Agricultural and Food Engineering, IIT Kharagpur, Kharagpur, West Bengal, 721302, India
Bibliografia
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- 2. Bellin A, Majone B, Cainelli O, Alberici D, Villa F (2016) A continuous coupled hydrological and water resources management model. Environ Model Softw 75:176–192. https://doi.org/10.1016/j.envsoft.2015.10.013
- 3. Biemans H, Haddeland I, Kabat P et al (2011) Impact of reservoirs on river discharge and irrigation water supply during the 20th century. Water Resour Res 47:W03509. https://doi.org/10.1029/2009WR008929
- 4. Burek P, van der Knijff J, de Roo A (2013) LISFLOOD distributed water balance and flood simulation model—revised user manual 2013. JRC Technical Reports, Joint Research Centre of the European Commission, Luxembourg.
- 5. Coerver HM, Rutten MM, van de Giesen NC (2018) Deduction of reservoir operating rules for application in global hydrological models. Hydrol Earth Syst Sci 22:831–851. https://doi.org/10.5194/hess-22-831-2018
- 6. Dai X, Yu Z, Yang G, Xu CY, Wan R (2021) Investigation of inner-basin variation: Impact of large reservoirs on water regimes of downstream water bodies. Hydrol Process 35(5):e14241. https://doi.org/10.1002/hyp.14241
- 7. Dang TD, Chowdhury AFM, Galelli S (2020) On the representation of water reservoir storage and operations in large-scale hydrological models: implications on model parameterisation and climate change impact assessments. Hydrol Earth Syst Sci 24:397–416. https://doi.org/10.5194/hess-24-397-2020
- 8. Demirel MC, Mai J, Mendiguren G, Koch J, Samaniego L, Stisen S (2018) Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model. Hydrol Earth Syst Sci 22(2):1299–1315. https://doi.org/10.5194/hess-22-1299-2018
- 9. Dong N, Yu Z, Yang C, Yang M, Wang W (2019) Hydrological impact of a reservoir network in the upper Gan River Basin. China Hydrol Process 33(12):1709–1723. https://doi.org/10.1002/hyp.13433
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- 20. Mauser W, Bach H (2009) PROMET–Large scale distributed hydrological modelling to study the impact of climate change on the water flows of mountain watersheds. J Hydrol 376:362–377. https://doi.org/10.1016/j.jhydrol.2009.07.046
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- 24. Omer A, Elagib NA, Zhuguo M, Saleem F, Mohammed A (2020) Water scarcity in the Yellow River Basin under future climate change and human activities. Sci Total Environ 749:141446. https://doi.org/10.1016/j.scitotenv.2020.141446
- 25. Paul PK, Kumari N, Panigrahi N, Mishra A, Singh R (2018) Implementation of cell-to-cell routing scheme in a large scale conceptual hydrological model. Environ Model Softw 101:23–33. https://doi.org/10.1016/j.envsoft.2017.12.003
- 26. Paul PK, Gaur S, Kumari B, Panigrahy N, Mishra A, Singh R (2019) Diagnosing credibility of a large-scale conceptual hydrological model in simulating streamflow. J Hydrol Eng 24(4):04019004. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001766
- 27. Paul PK, Kumari B, Gaur S, Mishra A, Panigrahy N, Singh R (2020) Application of a newly developed large-scale conceptual hydrological model in simulating streamflow for credibility testing in data scarce condition. Nat Resour Model 33(4):12283. https://doi.org/10.1111/nrm.12283
- 28. Ranjan A, Roshni T (2022) Analysis of hydrological alteration and environmental flow in Sone river basin. Acta Geophys. https://doi.org/10.1007/s11600-022-00946-w
- 29. Sapitang M, Ridwan W, Faizal Kushiar K, Najah Ahmed A, El-Shafie A (2020) Machine learning application in reservoir water level forecasting for sustainable hydropower generation strategy. Sustainability 12(15):6121
- 30. Sekhar M, Rasmi SN, Sivapullaiah PV, Ruiz L (2004) Groundwater flow modeling of Gundal sub-basin in Kabini river basin. India. Asian J Water Environ Pollut 1(1–2):65–77
- 31. Shin S, Pokhrel Y, Miguez-Macho G (2019) High-resolution modelling of reservoir release and storage dynamics at the continental scale. Water Resour Res 55:787–810. https://doi.org/10.1029/2018WR023025
- 32. Singh RK, Jain MK (2021) Complexity analyses of Godavari and Krishna river streamflow using the concept of entropy. Acta Geophys 69(6):2325–2338. https://doi.org/10.1007/s11600-021-00660-z
- 33. Sinha S, Hammond A, Smith H (2022) A comprehensive intercomparison study between a lumped and a fully distributed hydrological model across a set of 50 catchments in the United Kingdom. Hydrol Process 36(3):14544. https://doi.org/10.1002/hyp.14544
- 34. Sushanth K, Bhardwaj A (2019) Assessment of landuse change impact on runoff and sediment yield of Patiala-Ki-Rao watershed in Shivalik foot-hills of northwest India. Environ Monitor Assess 191:1–14. https://doi.org/10.1007/s10661-019-7932-z
- 35. Thomas T, Ghosh NC, Sudheer KP (2021) Optimal reservoir operation–a climate change adaptation strategy for Narmada basin in central India. J Hydrol 598:126238. https://doi.org/10.1016/j.jhydrol.2021.126238
- 36. Tinoco V, Willems P, Wyseure G, Cisneros F (2016) Evaluation of reservoir operation strategies for irrigation in the Macul Basin, Ecuador. J Hydrol: Reg Stud 5:213–225. https://doi.org/10.1016/j.ejrh.2015.12.063
- 37. van Beek LPH, Wada Y, Bierkens MF (2011) Global monthly water stress: 1. Water balance and water availability. Water Resour Res 47:107517. https://doi.org/10.1029/2010WR009791
- 38. Vanderkelen I et al (2022) Evaluating a reservoir parametrization in the vector-based global routing model mizuRoute (v.2 0.1) for Earth system model coupling. Geosci Model Dev 15(10):4163–4192. https://doi.org/10.5194/gmd-15-4163-2022
- 39. Vicente-Serrano SM et al (2017) Extreme hydrological events and the influence of reservoirs in a highly regulated river basin of northeastern Spain. J Hydrol Reg Stud 12:13–32. https://doi.org/10.1016/j.ejrh.2017.01.004
- 40. Voisin N, Li H, Ward D, Huang M, Wigmosta M, Leung LR (2013) On an improved sub-regional water resources management representation for integration into earth system models. Hydrol Earth Syst Sci 17:3605–3622. https://doi.org/10.5194/hess-17-3605-2013
- 41. Wada Y, de Graaf IE, van Beek LPH (2016) High-resolution modelling of human and climate impacts on global water resources. J Adv Model Earth Syst 8:735–763. https://doi.org/10.1002/2015MS000618
- 42. Wang G, Xia J (2010) Improvement of SWAT2000 modelling to assess the impact of dams and sluices on streamflow in the Huai River basin of China. Hydrol Proc 24:1455–1471. https://doi.org/10.1002/hyp.76
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- 44. Wu Y, Chen J (2012) An operation-based scheme for a multiyear and multipurpose reservoir to enhance macroscale hydrologic models. J Hydromet 13:270–283. https://doi.org/10.1175/JHM-D-10-05028.1
- 45. Yang S, Yang D, Chen J, Zhao B (2019) Real-time reservoir operation using recurrent neural networks and inflow forecast from a distributed hydrological model. J Hydrol 579:124229. https://doi.org/10.1016/j.jhydrol.2019.124229
- 46. Yang T, Zhang L, Kim T, Hong Y, Zhang D, Peng Q (2021) A large-scale comparison of Artificial Intelligence and Data Mining (AI&DM) techniques in simulating reservoir releases over the Upper Colorado Region. J Hydrol 602:126723. https://doi.org/10.1016/j.jhydrol.2021.126723
- 47. Yassin F, Razavi S, Elshamy M, Davison B, Sapriza-Azuri G, Wheater H (2019) Representation and improved parameterisation of reservoir operation in hydrological and land-surface models. Hydrol Earth Syst Sci 23:3735–3764. https://doi.org/10.5194/hess-23-3735-2019
- 48. Zajac Z, Revilla-Romero B, Salamon P, Burek P, Hirpa FA, Beck H (2017) The impact of lake and reservoir parameterisation on global streamflow simulation. J Hydrol 548:552–568. https://doi.org/10.1016/j.jhydrol.2017.03.022
- 49. Zaji AH, Bonakdari H, Gharabaghi B (2018) Reservoir water level forecasting using group method of data handling. Acta Geophys 66(4):717–730. https://doi.org/10.1007/s11600-018-0168-4
- 50. Zhao G, Gao H, Naz BS, Kao SC, Voisin N (2016) Integrating a reservoir regulation scheme into a spatially distributed hydrological model. Adv Water Resour 98:16–31. https://doi.org/10.1016/j.advwatres.2016.10.014
- 51. Zhao Q, Li D, Cai X (2021) Online generic diagnostic reservoir operation tools. Environ Model Softw 135:104918. https://doi.org/10.1016/j.envsoft.2020.104918
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c1ac409b-cba8-4e4d-a10b-f86f72d678ad