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Modelling Impacts of Climate Change on a River Basin: Analysis of Uncertainty Using REA & Possibilistic Approach

Author

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  • Jew Das

    (National Institute of Technology)

  • Alin Treesa

    (National Institute of Technology)

  • N. V. Umamahesh

    (National Institute of Technology)

Abstract

In the context of climate change, the uncertainty associated with Global Climate Models (GCM) and scenarios needs to be assessed for effective management practices and decision-making. The present study focuses on modelling the GCM and scenario uncertainty using Reliability Ensemble Averaging (REA) and possibility theory in projecting streamflows over Wainganga river basin. A macro scale, semi-distributed, grid-based hydrological model is used to project the streamflows from 2020 to 2094. The observed meteorological data are collected from the India Meteorological Department (IMD) and the streamflow data is obtained from Central Water Commission (CWC) Hyderabad. In REA, meteorological data are weighted based on the performance and convergence criteria (GCM uncertainty). Whereas in possibility theory, based on the projection of different GCMs and scenarios during recent past (2006–2015) possibility values are assigned. Based on the possibility values most probable experiment and weighted mean possible CDF for the future periods are obtained. The result shows that there is no significant difference in the outcomes is observed between REA and possibility theory. The uncertainty associated with GCM is more significant than the scenario uncertainty. An increasing trend in the low and medium flows is predicted in annual and monsoon period. However, flows during the non-monsoon season are projected to increase significantly. Moreover, it is observed that streamflow generation not only depends on the change in precipitation but also depends on the previous state of physical characteristics of the region.

Suggested Citation

  • Jew Das & Alin Treesa & N. V. Umamahesh, 2018. "Modelling Impacts of Climate Change on a River Basin: Analysis of Uncertainty Using REA & Possibilistic Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 4833-4852, December.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:15:d:10.1007_s11269-018-2046-x
    DOI: 10.1007/s11269-018-2046-x
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    References listed on IDEAS

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    1. Jew Das & Nanduri V. Umamahesh, 2016. "Downscaling Monsoon Rainfall over River Godavari Basin under Different Climate-Change Scenarios," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5575-5587, December.
    2. Jew Das & N. V. Umamahesh, 2018. "Assessment of uncertainty in estimating future flood return levels under climate change," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(1), pages 109-124, August.
    3. Subimal Ghosh & Sudhir Katkar, 2012. "Modeling Uncertainty Resulting from Multiple Downscaling Methods in Assessing Hydrological Impacts of Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(12), pages 3559-3579, September.
    4. Tobias Vetter & Julia Reinhardt & Martina Flörke & Ann Griensven & Fred Hattermann & Shaochun Huang & Hagen Koch & Ilias G. Pechlivanidis & Stefan Plötner & Ousmane Seidou & Buda Su & R. Willem Vervoo, 2017. "Evaluation of sources of uncertainty in projected hydrological changes under climate change in 12 large-scale river basins," Climatic Change, Springer, vol. 141(3), pages 419-433, April.
    5. Calum Brown & Evan Brown & Dave Murray-Rust & George Cojocaru & Cristina Savin & Mark Rounsevell, 2015. "Analysing uncertainties in climate change impact assessment across sectors and scenarios," Climatic Change, Springer, vol. 128(3), pages 293-306, February.
    6. Höllermann, Britta & Evers, Mariele, 2017. "Perception and handling of uncertainties in water management—A study of practitioners’ and scientists’ perspectives on uncertainty in their daily decision-making," Environmental Science & Policy, Elsevier, vol. 71(C), pages 9-18.
    7. Roja Najafi & Masoud Reza Hessami Kermani, 2017. "Uncertainty Modeling of Statistical Downscaling to Assess Climate Change Impacts on Temperature and Precipitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 1843-1858, April.
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    Cited by:

    1. Hadi Galavi & Majid Mirzaei, 2020. "Analyzing Uncertainty Drivers of Climate Change Impact Studies in Tropical and Arid Climates," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 2097-2109, April.
    2. Vassilios A. Tsihrintzis & Harris Vangelis, 2018. "Water Resources and Environment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 4813-4817, December.
    3. Jan Niel & E. Uytven & P. Willems, 2019. "Uncertainty Analysis of Climate Change Impact on River Flow Extremes Based on a Large Multi-Model Ensemble," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(12), pages 4319-4333, September.
    4. Yinmao Zhao & Zhansheng Li & Siyu Cai & Hao Wang, 2020. "Characteristics of extreme precipitation and runoff in the Xijiang River Basin at global warming of 1.5 °C and 2 °C," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 101(3), pages 669-688, April.
    5. Sri Lakshmi Sesha Vani Jayanthi & Venkata Reddy Keesara & Venkataramana Sridhar, 2022. "Prediction of Future Lake Water Availability Using SWAT and Support Vector Regression (SVR)," Sustainability, MDPI, vol. 14(12), pages 1-17, June.

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