Balaji Rajagopalan

  • CIRES, University of Colorado Boulder

    Balaji Rajagopalan

    My main research program is a diverse and interdisciplinary effort to enable sustainable water quantity and quality for the growing populations under increasing climate variability and change. This entails three interconnected themes: (i) Understanding the large-scale climate drivers of year-to-year and multidecadal variability and predictability of regional hydroclimatology and their extremes, (ii) Developing ensemble hydroclimate projection tools with large-scale climate information and, (iii) Coupling the projections with resources management and decision support system. In addition, I have keen interests in paleo and contemporary variability of Indian monsoon, big-data analysis and modeling techniques, water and wastewater quality, construction safety and building energy efficiency.

Publications

  • Culler, Elsa S., Ben Livneh, Balaji Rajagopalan, and Kristy F. Tiampo. 2023. “A Data-Driven Evaluation of Post-Fire Landslide Susceptibility.” Natural Hazards and Earth System Sciences 23 (4): 1631–52.   https://doi.org/10.5194/nhess-23-1631-2023

  • Heldmyer, A.J., B. Livneh, B. Rajagopalan, and N. Molotch, 2021: Investigating the Relationship Between Peak Snow-Water Equivalent and Snow Timing Indices in the Western U.S. and Alaska, Water Resources Research, 57, e2020WR029395.   https://doi.org/10.1029/2020WR029395

  • Culler, Elsa S., Ben Livneh, Balaji Rajagopalan, and Kristy F. Tiampo (2021). A Data-Driven Evaluation of Post-Fire Landslide Susceptibility. Preprint. Landslides and Debris Flows Hazards.   https://doi.org/10.5194/nhess-2021-111

  • Smith, R.M., J.R. Kasprzyk, and R. Balaji (2019). Using multivariate regression trees and multiobjective tradeoff sets to reveal fundamental insights about water resources systems. Environmental Modelling and Software, Vol 120: 104498.   doi: 10.1016/j.envsoft.2019.104498

  • Stewart, J.S., B. Livneh, J.R. Kasprzyk, J.T. Minear, B. Rajagopalan, and W.J. Raseman (2017). A multi-algorithm approach to land surface modeling of suspended sediment in the Colorado Front Range. Journal of Advances in Models Earth Systems, 9(7), 2526-2544,   doi: 10.1002/2017MS001120

  • Gershunov, A., B. Rajagopalan, J. Overpeck, K. Guirguis, D. Cayan, M. Hughes, M. Dettinger, C. Castro, R. E. Schwartz, M. Anderson, A. J. Ray, J. Barsugli, T. Cavazos, and M. Alexander (2013). Future Climate: Projected Extremes. In Assessment of Climate Change in the Southwest United States: A Report Prepared for the National Climate Assessment, edited by G. Garfin, A. Jardine, R. Merideth, M. Black, and S. LeRoy, 126–147. A report by the Southwest Climate Alliance. Washington, DC: Island Press.   https://swcarr.arizona.edu/sites/default/files/ACCSWUS_Ch7.pdf
  • Cayan, D., M. Tyree, K. E. Kunkel, C. Castro, A. Gershunov, J. Barsugli, A. J. Ray, J. Overpeck, M. Anderson, J. Russell, B. Rajagopalan, I. Rangwala, and P. Duffy (2013). Future Climate: Projected Averages. In Assessment of Climate Change in the Southwest United States: A Report Prepared for the National Climate Assessment, edited by G. Garfin, A. Jardine, R. Merideth, M. Black, and S. LeRoy, 101–125. A report by the Southwest Climate Alliance. Washington, DC: Island Press.   https://swcarr.arizona.edu/sites/default/files/ACCSWUS_Ch6.pdf

  • Lukas, J., L. Wade, B. Rajagopalan (2012). Paleohydrology of the Lower Colorado River Basin and Implications for Water Supply Availability. Colorado Water Institute - Completion Report CR223, 37 pp.   
  • Lukas, J., L. Wade, B. Rajagopalan (2012). Paleohydrology of the Lower Colorado River Basin and Implications for Water Supply Availability. Colorado Water, Vol. 29, No. 6. November/December 2012 , 3 pp.   
  • Nowak, K., M. Hoerling, B. Rajagopalan, E. and Zagona (2012). Colorado River Basin Hydroclimatic Variability. Journal of Climate, 25(12): 4389.   https://doi.org/10.1175/JCLI-D-11-00406.1

  • Nowak, K., B. Rajagopalan, and E. Zagona (2011). Wavelet Auto-Regressive Method (WARM) for multi-site streamflow simulation of data with non-stationary spectra. Journal of Hydrology, 410 (1-2): 1-12.   https://doi.org/10.1016/j.jhydrol.2011.08.051

  • Bracken, C., B. Rajagopalan, and J. Prairie (2010). A Multi-Site Seasonal Ensemble Streamflow Forecasting Technique. Water Resources Research, 46: W03302.   
  • Nowak, K., J. Prairie, B. Rajagopalan, and U. Lall (2010). A nonparametric stochastic approach for multisite disaggregation of annual to daily streamflow. Water Resources Research, 46: W08529.   

  • Barsugli, J., K. Nowak, B. Rajagopalan, J. Prairie, and B. Harding (2009). Comment on “When Will Lake Mead go Dry?” by T. P. Barnett and D. W. Pierce. Water Resources Research, 45, W09601.   
  • Gangopadhyay, S., B. Harding, B. Rajagopalan, J. Lukas, and T. Fulp (2009). A Non-Parametric Approach for Paleohydrologic Reconstruction of Annual Streamflow Ensembles. Water Resources Research, 45, W06417.   

  • Rajagopalan, B., K. Nowak, J. Prairie, M. Hoerling, B. Harding, J. Barsugli, A. Ray, and B. Udall (2009). Water Supply Risk on the Colorado River: Can Management Mitigate? Water Resources Research, 45, W08201,   doi:10.1029/2008WR007652

  • Regonda, S., B. Rajagopalan, M. Clark, and E. Zagona (2006). A Multimodel Ensemble Forecast Framework: Application to Spring Seasonal Flows in the Gunnison River Basin. Water Resources Research, 42: W09404.   

  • Gangopadhyay, S., M. Clark, and B. Rajagopalan (2005). Statistical Downscaling Using K-Nearest Neighbors. Water Resources Research, 41(2): W02024.   
  • Rajagopalan, B., K. Grantz, S. Regonda, M. Clark, and E. Zagona (2005). Ensemble Streamflow Forecasting. In Methods and Applications: Advances in Water Science Methodologies. U. Aswathanarayana, ed. Netherlands, Taylor and Francis.   

  • Gangopadhyay, S., M. Clark, B. Rajagopalan, K. Werner, and D. Brandon (2004). Effects of Spatial and Temporal Aggregation on the Accuracy of Statistically Downscaled Precipitation Estimates in the Upper Colorado River Basin. Journal of Hydrometeorology, 5: 1192-1206.   
  • Clark, M., S. Gangopadhyay, D. Brandon, K. Werner, L. Hay, B. Rajagopalan, and D. Yates (2004). A Resampling Procedure for Generating Conditioned Daily Weather Sequences. Water Resources Research, 40(4): W04304.   
  • Clark, M., S. Gangopadhyay, L. Hay, B. Rajagopalan, and R. Wilby (2004). The Schaake Shuffle: A Method to Reconstruct the Space-time Variability of Forecasted Precipitation and Temperature Fields. Journal of Hydrometeorology, 5: 243-262.   

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