Skip to main content

Advertisement

Log in

From Changing Environment to Changing Extremes: Exploring the Future Streamflow and Associated Uncertainties Through Integrated Modelling System

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

Climate and land-use changes can alter the dynamics of hydro-climatic extremes by modifying the flow regimes. Here, we have attempted to disentangle the relationship between changing environmental conditions and hydro-climatic extremes considering associated uncertainties for the Subarnarekha, a flood prone-basin of India. A comprehensive, integrated modelling system was developed that incorporates a spatially explicit land-use model, a hydrological model, and an ensemble of regional climate models (RCMs). MIKE SHE/MIKE HYDRO RIVER was used to simulate the hydrological processes. The uncertainties associated with model parameters, model inputs, and model structures are analysed collectively using ‘quantile regression.’ A transferable framework was developed for the analysis of hydro-climatic extremes that deal with numerous aspects like sensitivity, occurrences, severity, and persistence for four-time horizons: baseline (1976–2005) and early (2020s), mid (2050s), end-centuries (2080s). ANOVA is used for partitioning uncertainty due to different sources. The results obtained from numerous analysis of the developed framework suggests that low, high, and medium flows will probably increase in the future (20%-85% increase), indicating a higher risk of floods, especially in the 2050s and 2080s. Partitioning of uncertainty suggests RCMs contribute 40%-62% to the uncertainty in streamflow projections. The developed modelling systems incorporates a flexible framework so update any other water sustainability issue in the future. These findings will help better meet the challenges associated with the possible risk of increasing high flows in the future by ceding references to the decision-makers for framing better prevention measures associated with land-use and climate changes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Availability of Data and Materials

Data and material would be made available on request.

References

  • Aduah MS, Jewitt GPW, Toucher MLW (2017) Scenario-based impacts of land use and climate changes on the hydrology of a lowland rainforest catchment in Ghana, West Africa. Hydrol Earth Syst Sci 1–27. https://doi.org/10.5194/hess-2017-591

  • Aich V, Liersch S, Vetter T (2014) Comparing impacts of climate change on streamflow in four large African river basins. Hydrol Earth Syst Sci 18:1305–1321

    Article  Google Scholar 

  • Anaraki MV, Farzin S, Mousavi SF, Karami H (2021) Uncertainty Analysis of Climate Change Impacts on Flood Frequency by Using Hybrid Machine Learning Methods. Water Resour Manag 35:199–223

    Article  Google Scholar 

  • Beven K, Feyen J (2002) The Future of Distributed Modelling. Hydrol Process 16:169–172

    Article  Google Scholar 

  • Bosshard T, Carambia M, Goergen K et al (2013) Quantifying uncertainty sources in an ensemble of hydrological climate-impact projections. Water Resour Res 49:1523–1536

    Article  Google Scholar 

  • Burn DH, Whitfield PH (2018) Changes in flood events inferred from centennial length streamflow data records. Adv Water Resour 121:333–349

    Article  Google Scholar 

  • Chawla I, Mujumdar PP (2018) Partitioning uncertainty in streamflow projections under nonstationary model conditions. Adv Water Resour 112:266–282

    Article  Google Scholar 

  • Dadson SJ, Lopez HP, Peng J, Vora S (2020) Hydroclimatic Extremes and Climate Change, In: Dadson SJ, Garrick DE, Penning-Rowsell EC, Hall JW, Hope R, Highes J. (Eds.), Water Science, Policy, and Management: a Global Challenge. John Wiley & Sons Ltd 11-28

  • Farjad B, Gupta A, Razavi S, Faramarzi M, Marceau DJ (2017) An integrated modelling system to predict hydrological processes under climate and land-use/cover change scenarios. Water 9:1–23

    Article  Google Scholar 

  • Gaur S, Bandyopadhyay A, Singh R (2020a) Modelling potential impact of climate change and uncertainty on streamflow projections: A case study. J Water Clim Change. https://doi.org/10.2166/wcc.2020.254

    Article  Google Scholar 

  • Gaur S, Mittal A, Bandyopadhyay A et al (2020b) Spatio-temporal analysis of land use and land cover change: a systematic model inter-comparison driven by integrated modelling techniques. Int J Remote Sens 41:9229–9255

    Article  Google Scholar 

  • Goyal MK, Surampalli RY (2018) Impact of climate change on water resources in India. J Environ Eng

  • Hamed KH, Ramachandra Rao A (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204:182–196

    Article  Google Scholar 

  • Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1: 96–99

  • IPCC (2013) Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535

  • Kendall MG (1975) Rank Correlation method, 4th edn. Charles Griffen, London

    Google Scholar 

  • Kim Y, Ohn I, Lee JK, Kim YO (2019) Generalizing uncertainty decomposition theory in climate change impact assessments. J Hydrol X 3:100024

    Article  Google Scholar 

  • Kim S, Alizamir M, Kim NW, Kisi O (2020) Bayesian model averaging: A unique model enhancing forecasting accuracy for daily streamflow based on different antecedent time series. Sustain 12:1–22

    Google Scholar 

  • Kling H, Stanzel P, Preishuber M (2014) Impact modelling of water resources development and climate scenarios on Zambezi River discharge. J Hydrol Reg Stud 1:17–43

    Article  Google Scholar 

  • Krysanova V, Vetter T, Eisner S et al (2017) Intercomparison of regional-scale hydrological models and climate change impacts projected for 12 large river basins worldwide - A synthesis. Environ Res Lett 12. https://doi.org/10.1088/1748-9326/aa8359

  • Kumar A, Singh R, Jena PP et al (2015) Identification of the best multi-model combination for simulating river discharge. J Hydrol 525:313–325

    Article  Google Scholar 

  • Kundzewicz ZW, Krysanova V, Benestad RE et al (2018) Uncertainty in climate change impacts on water resources. Environ Sci Policy 79:1–8

    Article  Google Scholar 

  • Laaha G, Blöschl G (2006) Seasonality indices for regionalising low flows. Hydrol Process 20:3851–3878

    Article  Google Scholar 

  • Lee JK, Kim YO, Kim Y (2017) A new uncertainty analysis in the climate change impact assessment. Int J Remote Sens 37(10):3837–3846

    Google Scholar 

  • Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259

    Article  Google Scholar 

  • Mohammadi B, Ahmadi F, Mehdizadeh S et al (2020a) Developing Novel Robust Models to Improve the Accuracy of Daily Streamflow Modeling. Water Resour Manag 34:3387–3409

    Article  Google Scholar 

  • Mohammadi B, Linh NTT, Pham QB et al (2020b) Adaptive neuro-fuzzy inference system coupled with shuffled frog leaping algorithm for predicting river streamflow time series. Hydrol Sci J 65:1738–1751

    Article  Google Scholar 

  • Moriasi DN, Arnold JG, Van Liew MW et al (2007) Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Trans ASABE 50:885–900

    Article  Google Scholar 

  • Norouzi Khatiri K, Niksokhan MH, Sarang A, Kamali A (2020) Coupled Simulation-Optimization Model for the Management of Groundwater Resources by Considering Uncertainty and Conflict Resolution. Water Resour Manag 34:3585–3608

    Article  Google Scholar 

  • Paul PK, Gaur S, Kumari B et al (2019) Diagnosing Credibility of a Large-Scale Conceptual Hydrological Model in Simulating Streamflow. J Hydrol Eng 24:04019004. https://doi.org/10.1061/(asce)he.1943-5584.0001766

    Article  Google Scholar 

  • Pechlivanidi IG, Arheimer B, Donnelly C (2017). Analysis of hydrological extremes at different hydro-climatic regimes under present and future conditions. Clim Change, 467–481. https://doi.org/10.1007/s10584-016-1723-0

  • Piani C, Haerter JO, Coppola E (2010) Statistical bias correction for daily precipitation in regional climate models over Europe. Theor Appl Climatol 187–192. https://doi.org/10.1007/s00704-009-0134-9

  • Sen PK (1968) Estimates of the Regression Coefficient Based on Kendall ’ s Tau. J Am Stat Asso 63 (324)

  • Serneels S, Said MY, Lambin EF (2001) Land cover changes around a major East African wildlife reserve: The Mara ecosystem (Kenya). Int J Remote Sens. 22(17):3397–3420

    Article  Google Scholar 

  • Singh AK, Giri S (2018) Subarnarekha River: The Golden Streak of India, In: Singh, D.S. (Ed.). The Indian Rivers. Springer, Singapore. https://doi.org/10.1007/978-981-10-2984-4

  • Singh R (2019) Stochastic modelling for the spatio-temporal analysis of rainfall patterns Dissertation. Indian Institute of Technology, Kharagpur

    Google Scholar 

  • Storch H. Von, Geesthacht H, Navarra A (1999) Analysis of climate variability. Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-662-03744-7

  • Tabari MMR (2015) Conjunctive Use Management under Uncertainty Conditions in Aquifer Parameters. Water Resour Manag 29:2967–2986

    Article  Google Scholar 

  • Warburton ML, Schulze RE, Jewitt GPW (2012) Hydrological impacts of land use change in three diverse South African catchments. J Hydrol 414–415:118–135

    Article  Google Scholar 

  • Weerts AH, Winsemius HC, VerkadeBox JS (2011) Estimation of predictive hydrological uncertainty using quantile regression : examples from the National Flood Forecasting System (England and Wales). Hydrol Earth Syst Sci. 15:255–265

    Article  Google Scholar 

  • Wijesekara G (2013) An integrated modeling system to simulate the impact of land-use changes on hydrological processes in the Elbow River watershed in Southern Alberta. Dissertation, University of Alberta

  • Wijesekara GN, Gupta A, Valeo C et al (2012) Assessing the impact of future land-use changes on hydrological processes in the Elbow River watershed in southern Alberta, Canada. J. Hydrol 412–413:220–232

  • Wijesekara GN, Farjad B, Gupta A et al (2014) A comprehensive land-use/hydrological modeling system for scenario simulations in the Elbow River watershed, Alberta, Canada. Environ Manage 53:357–381

    Article  Google Scholar 

  • Zhang Y, You Q, Chen C, Ge J (2016) Impacts of climate change on streamflows under RCP scenarios: A case study in Xin River Basin, China. Atmos Res 178–179:521–534

    Article  Google Scholar 

Download references

Acknowledgement

The World Climate Research Programme's Working Group on Regional Climate and the Working Group on Coupled Modelling, the former coordinating body of CORDEX and responsible panel for CMIP5, are gratefully acknowledged. The authors thank the Earth System Grid Federation (ESGF) infrastructure and the Climate Data Portal hosted at the Centre for Climate Change Research (CCCR), Indian Institute of Tropical Meteorology (IITM), for providing CORDEX South Asia data.

Author information

Authors and Affiliations

Authors

Contributions

Srishti Gaur: Conceptualisation, Data acquisition, Methodology, Writing- Original draft preparation. Arnab Bandyopadhyay: Supervision, Editing of the manuscript. Rajendra Singh: Conceptualisation, Supervision, Editing of the manuscript, Visualisation.

Corresponding author

Correspondence to Srishti Gaur.

Ethics declarations

Ethics Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Conflict of Interest

The author declares there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 659 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gaur, S., Bandyopadhyay, A. & Singh, R. From Changing Environment to Changing Extremes: Exploring the Future Streamflow and Associated Uncertainties Through Integrated Modelling System. Water Resour Manage 35, 1889–1911 (2021). https://doi.org/10.1007/s11269-021-02817-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-021-02817-3

Keywords

Navigation