World Library  

Add to Book Shelf
Flag as Inappropriate
Email this Book

A Trading-space-for-time Approach to Probabilistic Continuous Streamflow Predictions in a Changing Climate : Volume 8, Issue 4 (01/07/2011)

By Singh, R.

Click here to view

Book Id: WPLBN0004012968
Format Type: PDF Article :
File Size: Pages 33
Reproduction Date: 2015

Title: A Trading-space-for-time Approach to Probabilistic Continuous Streamflow Predictions in a Changing Climate : Volume 8, Issue 4 (01/07/2011)  
Author: Singh, R.
Volume: Vol. 8, Issue 4
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


APA MLA Chicago

Singh, R., Wagener, T., Werkhoven, K. V., Mann, M., & Crane, R. (2011). A Trading-space-for-time Approach to Probabilistic Continuous Streamflow Predictions in a Changing Climate : Volume 8, Issue 4 (01/07/2011). Retrieved from

Description: Department of Civil and Environmental Engineering, The Pennsylvania State University, Sackett Building, University Park, PA 16802, USA. Understanding the implications of potential future climatic conditions for hydrologic services and hazards is a crucial and current science question. The common approach to this problem is to force a hydrologic model, calibrated on historical data or using a priori parameter estimates, with future scenarios of precipitation and temperature. Recent studies suggest that the climatic regime of the calibration period is reflected in the resulting parameter estimates and that the model performance can be negatively impacted if the climate for which projections are made is significantly different from that during calibration. We address this issue by introducing a framework for probabilistic streamflow predictions in a changing climate wherein we quantify the impact of climate on model parameters. The strategy extends a regionalization approach (used for predictions in ungauged basins) by trading space-for-time to account for potential parameter variability in a future climate that is beyond the historically observed one. The developed methodology was tested in five US watersheds located in dry to wet climates using synthetic climate scenarios generated by increasing the historical mean temperature from 0 to 8 °C and by changing historical mean precipitation from −30 % to +40 % of the historical values. Validation on historical data shows that changed parameters perform better if future streamflow differs from historical by more than 25 %. We found that the thresholds of climate change after which the streamflow projections using adjusted parameters were significantly different from those using fixed parameters were 0 to 2 °C for temperature change and −10 % to 20 % for precipitation change depending upon the aridity of the watershed. Adjusted parameter sets simulate a more extreme watershed response for both high and low flows.

A trading-space-for-time approach to probabilistic continuous streamflow predictions in a changing climate

Arthington, A. H., Bunn, S. E., Poff, N. L., and Naiman, R. J.: The challenge of providing environmental environmental flow rules to sustain river ecosystems, Ecol. Appl., 16, 1311–1318, 2006.; Arnold, J. G., Allen, P. M., Muttiah, R., and Bernhardt, G.: Automated base flow separation and recession analysis techniques, Ground Water, 33(6), 1010–1018, doi:10.1111/j.1745-6584.1995.tb00046, 1995.; Bárdossy, A.: Calibration of hydrological model parameters for ungauged catchments, Hydrol. Earth Syst. Sci., 11, 703–710, doi:10.5194/hess-11-703-2007, 2007.; Bastola, S., Murphy, C., and Sweeney, J.: Evaluation of the transferability of hydrological model parameters for simulations under changed climatic conditions, Hydrol. Earth Syst. Sci. Discuss., 8, 5891–5915, doi:10.5194/hessd-8-5891-2011, 2011.; Beven, K., and Freer, J.: Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, J. Hydrol., 249(1–4), 11–29, doi:10.1016/S0022-1694(01)00421-8, 2001.; Boyle, D. P., Gupta, H. V., and Sorooshian, S.: Toward improved calibration of hydrologic models: Combining the strengths of manual and automatic methods, Water Resour. Res., $36$(12), 3663–3674, doi:10.1029/2000WR900207, 2000.; Budyko, M. I.: Climate and Life, Academic Press, New York, 1974.; Bulygina, N., McIntyre, N., and Wheater, H.: Conditioning rainfall-runoff model parameters for ungauged catchments and land management impacts analysis, Hydrol. Earth Syst. Sci., 13, 893–904, doi:10.5194/hess-13-893-2009, 2009.; Bulygina, N., McIntyre, N., and Wheater H.: Bayesian conditioning of a rainfall-runoff model for predicting flows in ungauged catchments and under land use changes, Water Resour. Res., 47, W02503, doi:10.1029/2010WR009240, 2011.; Buytaert, W., Célleri, R., and Timbe, L.: Predicting climate change impacts on water resources in the tropical Andes: Effects of GCM uncertainty, Geophys. Res. Lett., 36, L07406, doi:10.1029/2008GL037048, 2009.; Chapra, S. C.: Rivers and Streams, in: Surface Water-Quality Modeling, 243–244, Waveland Press, Inc., Long Grove, Illinois, 1997.; Christensen, J. H., Hewitson, B., Busuioc, A., Chen, A., Gao, X., Held, I., Jones, R., Kolli, R. K., Kwon, W.-T., Laprise, R., Magaña Rueda, V., Mearns, L., Menéndez, C. G., Räisänen, J., Rinke, A., Sarr, A., and Whetton, P.: Regional Climate Projections, Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2007.; Dewalle, D. R., and Rango, A.: Principles of Snow Hydrology, Cambridge University Press, Cambridge, UK, 2008.; Dooge, J.: Sensitivity of runoff to climate change: A Hortonian approach, Bull. Amer. Meteor. Soc., 73, 2013–2024, doi:10.1175/1520-0477(1992)073, 1992.; Duan, Q., Schaake, J., Andreassian, V., Franks, S., Gupta, H. V., Gusev, Y. M., Habets, F., Hall, A., Hay, L., Hogue, T. S., Huang, M., Leavesley, G., Liang, X., Nasonova, O. N., Noilhan, J., Oudin, L., Sorooshian, S., Wagener, T., and Wood, E. F.: The Model Parameter Estimation Experiment (MOPEX): An overview


Click To View

Additional Books

  • A Groundwater Recharge Perspective on Lo... (by )
  • Determining Spatial Variability of Dry S... (by )
  • Variability of Dissolved Co2 in the Pang... (by )
  • Explicit Simulations of Stream Networks ... (by )
  • The Influence of Heterogeneous Groundwat... (by )
  • Joint Impact of Rainfall and Tidal Level... (by )
  • Errors in Climate Model Daily Precipitat... (by )
  • Time-series of Tritium, Stable Isotopes ... (by )
  • Effects of Snow Ratio on Annual Runoff W... (by )
  • Application of Time-series Analyses to t... (by )
  • Increasing Silicon Concentrations in Boh... (by )
  • Palaeoclimatological Perspective on Rive... (by )
Scroll Left
Scroll Right


Copyright © World Library Foundation. All rights reserved. eBooks from Hawaii eBook Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.