Skip to main content
Erschienen in: Water Resources Management 6/2021

15.04.2021

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

verfasst von: Srishti Gaur, Arnab Bandyopadhyay, Rajendra Singh

Erschienen in: Water Resources Management | Ausgabe 6/2021

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

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.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Anhänge
Nur mit Berechtigung zugänglich
Literatur
Zurück zum Zitat Aich V, Liersch S, Vetter T (2014) Comparing impacts of climate change on streamflow in four large African river basins. Hydrol Earth Syst Sci 18:1305–1321CrossRef Aich V, Liersch S, Vetter T (2014) Comparing impacts of climate change on streamflow in four large African river basins. Hydrol Earth Syst Sci 18:1305–1321CrossRef
Zurück zum Zitat 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 35:199–223CrossRef 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 35:199–223CrossRef
Zurück zum Zitat Beven K, Feyen J (2002) The Future of Distributed Modelling. Hydrol Process 16:169–172CrossRef Beven K, Feyen J (2002) The Future of Distributed Modelling. Hydrol Process 16:169–172CrossRef
Zurück zum Zitat Bosshard T, Carambia M, Goergen K et al (2013) Quantifying uncertainty sources in an ensemble of hydrological climate-impact projections. Water Resour Res 49:1523–1536CrossRef Bosshard T, Carambia M, Goergen K et al (2013) Quantifying uncertainty sources in an ensemble of hydrological climate-impact projections. Water Resour Res 49:1523–1536CrossRef
Zurück zum Zitat Burn DH, Whitfield PH (2018) Changes in flood events inferred from centennial length streamflow data records. Adv Water Resour 121:333–349CrossRef Burn DH, Whitfield PH (2018) Changes in flood events inferred from centennial length streamflow data records. Adv Water Resour 121:333–349CrossRef
Zurück zum Zitat Chawla I, Mujumdar PP (2018) Partitioning uncertainty in streamflow projections under nonstationary model conditions. Adv Water Resour 112:266–282CrossRef Chawla I, Mujumdar PP (2018) Partitioning uncertainty in streamflow projections under nonstationary model conditions. Adv Water Resour 112:266–282CrossRef
Zurück zum Zitat 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 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
Zurück zum Zitat 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 9:1–23CrossRef 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 9:1–23CrossRef
Zurück zum Zitat 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 41:9229–9255CrossRef 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 41:9229–9255CrossRef
Zurück zum Zitat Goyal MK, Surampalli RY (2018) Impact of climate change on water resources in India. J Environ Eng Goyal MK, Surampalli RY (2018) Impact of climate change on water resources in India. J Environ Eng
Zurück zum Zitat Hamed KH, Ramachandra Rao A (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204:182–196CrossRef Hamed KH, Ramachandra Rao A (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204:182–196CrossRef
Zurück zum Zitat Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1: 96–99 Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1: 96–99
Zurück zum Zitat 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 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
Zurück zum Zitat Kendall MG (1975) Rank Correlation method, 4th edn. Charles Griffen, London Kendall MG (1975) Rank Correlation method, 4th edn. Charles Griffen, London
Zurück zum Zitat Kim Y, Ohn I, Lee JK, Kim YO (2019) Generalizing uncertainty decomposition theory in climate change impact assessments. J Hydrol X 3:100024CrossRef Kim Y, Ohn I, Lee JK, Kim YO (2019) Generalizing uncertainty decomposition theory in climate change impact assessments. J Hydrol X 3:100024CrossRef
Zurück zum Zitat 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 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
Zurück zum Zitat Kling H, Stanzel P, Preishuber M (2014) Impact modelling of water resources development and climate scenarios on Zambezi River discharge. J Hydrol Reg Stud 1:17–43CrossRef Kling H, Stanzel P, Preishuber M (2014) Impact modelling of water resources development and climate scenarios on Zambezi River discharge. J Hydrol Reg Stud 1:17–43CrossRef
Zurück zum Zitat Kumar A, Singh R, Jena PP et al (2015) Identification of the best multi-model combination for simulating river discharge. J Hydrol 525:313–325CrossRef Kumar A, Singh R, Jena PP et al (2015) Identification of the best multi-model combination for simulating river discharge. J Hydrol 525:313–325CrossRef
Zurück zum Zitat Kundzewicz ZW, Krysanova V, Benestad RE et al (2018) Uncertainty in climate change impacts on water resources. Environ Sci Policy 79:1–8CrossRef Kundzewicz ZW, Krysanova V, Benestad RE et al (2018) Uncertainty in climate change impacts on water resources. Environ Sci Policy 79:1–8CrossRef
Zurück zum Zitat Laaha G, Blöschl G (2006) Seasonality indices for regionalising low flows. Hydrol Process 20:3851–3878CrossRef Laaha G, Blöschl G (2006) Seasonality indices for regionalising low flows. Hydrol Process 20:3851–3878CrossRef
Zurück zum Zitat 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 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
Zurück zum Zitat Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259CrossRef Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259CrossRef
Zurück zum Zitat Mohammadi B, Ahmadi F, Mehdizadeh S et al (2020a) Developing Novel Robust Models to Improve the Accuracy of Daily Streamflow Modeling. Water Resour Manag 34:3387–3409CrossRef Mohammadi B, Ahmadi F, Mehdizadeh S et al (2020a) Developing Novel Robust Models to Improve the Accuracy of Daily Streamflow Modeling. Water Resour Manag 34:3387–3409CrossRef
Zurück zum Zitat 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 65:1738–1751CrossRef 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 65:1738–1751CrossRef
Zurück zum Zitat Moriasi DN, Arnold JG, Van Liew MW et al (2007) Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Trans ASABE 50:885–900CrossRef Moriasi DN, Arnold JG, Van Liew MW et al (2007) Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Trans ASABE 50:885–900CrossRef
Zurück zum Zitat 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 34:3585–3608CrossRef 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 34:3585–3608CrossRef
Zurück zum Zitat Sen PK (1968) Estimates of the Regression Coefficient Based on Kendall ’ s Tau. J Am Stat Asso 63 (324) Sen PK (1968) Estimates of the Regression Coefficient Based on Kendall ’ s Tau. J Am Stat Asso 63 (324)
Zurück zum Zitat 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):3397–3420CrossRef 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):3397–3420CrossRef
Zurück zum Zitat Singh R (2019) Stochastic modelling for the spatio-temporal analysis of rainfall patterns Dissertation. Indian Institute of Technology, Kharagpur Singh R (2019) Stochastic modelling for the spatio-temporal analysis of rainfall patterns Dissertation. Indian Institute of Technology, Kharagpur
Zurück zum Zitat Tabari MMR (2015) Conjunctive Use Management under Uncertainty Conditions in Aquifer Parameters. Water Resour Manag 29:2967–2986CrossRef Tabari MMR (2015) Conjunctive Use Management under Uncertainty Conditions in Aquifer Parameters. Water Resour Manag 29:2967–2986CrossRef
Zurück zum Zitat Warburton ML, Schulze RE, Jewitt GPW (2012) Hydrological impacts of land use change in three diverse South African catchments. J Hydrol 414–415:118–135CrossRef Warburton ML, Schulze RE, Jewitt GPW (2012) Hydrological impacts of land use change in three diverse South African catchments. J Hydrol 414–415:118–135CrossRef
Zurück zum Zitat 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. 15:255–265CrossRef 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. 15:255–265CrossRef
Zurück zum Zitat 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 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
Zurück zum Zitat 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, 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
Zurück zum Zitat 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 53:357–381CrossRef 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 53:357–381CrossRef
Zurück zum Zitat 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 178–179:521–534CrossRef 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 178–179:521–534CrossRef
Metadaten
Titel
From Changing Environment to Changing Extremes: Exploring the Future Streamflow and Associated Uncertainties Through Integrated Modelling System
verfasst von
Srishti Gaur
Arnab Bandyopadhyay
Rajendra Singh
Publikationsdatum
15.04.2021
Verlag
Springer Netherlands
Erschienen in
Water Resources Management / Ausgabe 6/2021
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI
https://doi.org/10.1007/s11269-021-02817-3

Weitere Artikel der Ausgabe 6/2021

Water Resources Management 6/2021 Zur Ausgabe