Toward Understanding the Value of Climate Information for Multiobjective Reservoir Management under Present and Future Climate and Demand Scenarios

Nicholas E. Graham Hydrologic Research Center, San Diego, and Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

Search for other papers by Nicholas E. Graham in
Current site
Google Scholar
PubMed
Close
and
Konstantine P. Georgakakos Hydrologic Research Center, San Diego, and Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

Search for other papers by Konstantine P. Georgakakos in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Numerical simulation techniques and idealized reservoir management models are used to assess the utility of climate information for the effective management of a single multiobjective reservoir. Reservoir management considers meeting release and reservoir volume targets and minimizing wasteful spillage. The influence of reservoir size and inflow variability parameters on the management benefits is examined. The effects of climate and demand (release target) change on the management policies and performance are also quantified for various change scenarios. Inflow forecasts emulate ensembles of dynamical forecasts for a hypothetical climate system with somewhat predictable low-frequency variability. The analysis considers the impacts of forecast skill. The mathematical problem is cast in a dimensionless time and volume framework to allow generalization. The present work complements existing research results for specific applications and expands earlier analytical results for simpler management situations in an effort to draw general conclusions for the present-day reservoir management problem under uncertainty. The findings support the following conclusions: (i) reliable inflow forecasts are beneficial for reservoir management under most situations if adaptive management is employed; (ii) tolerance to forecasts of lower reliability tends to be higher for larger reservoirs; (iii) reliable inflow forecasts are most useful for a midrange of reservoir capacities; (iv) demand changes are more detrimental to reservoir management performance than inflow change effects of similar magnitude; (v) adaptive management is effective for mitigating climatic change effects and may even help to mitigate demand change effects.

Corresponding author address: Konstantine P. Georgakakos, Hydrologic Research Center, 12780 High Bluff Dr., Suite 250, San Diego, CA 92130. Email: kgeorgakakos@hrc-lab.org

Abstract

Numerical simulation techniques and idealized reservoir management models are used to assess the utility of climate information for the effective management of a single multiobjective reservoir. Reservoir management considers meeting release and reservoir volume targets and minimizing wasteful spillage. The influence of reservoir size and inflow variability parameters on the management benefits is examined. The effects of climate and demand (release target) change on the management policies and performance are also quantified for various change scenarios. Inflow forecasts emulate ensembles of dynamical forecasts for a hypothetical climate system with somewhat predictable low-frequency variability. The analysis considers the impacts of forecast skill. The mathematical problem is cast in a dimensionless time and volume framework to allow generalization. The present work complements existing research results for specific applications and expands earlier analytical results for simpler management situations in an effort to draw general conclusions for the present-day reservoir management problem under uncertainty. The findings support the following conclusions: (i) reliable inflow forecasts are beneficial for reservoir management under most situations if adaptive management is employed; (ii) tolerance to forecasts of lower reliability tends to be higher for larger reservoirs; (iii) reliable inflow forecasts are most useful for a midrange of reservoir capacities; (iv) demand changes are more detrimental to reservoir management performance than inflow change effects of similar magnitude; (v) adaptive management is effective for mitigating climatic change effects and may even help to mitigate demand change effects.

Corresponding author address: Konstantine P. Georgakakos, Hydrologic Research Center, 12780 High Bluff Dr., Suite 250, San Diego, CA 92130. Email: kgeorgakakos@hrc-lab.org

Save
  • Carpenter, T. M., and K. P. Georgakakos, 2001: Assessment of Folsom Lake response to historical and potential future climate scenarios: 1. Forecasting. J. Hydrol., 249 , 148175.

    • Search Google Scholar
    • Export Citation
  • Datta, B., and S. J. Burges, 1984: Short-term, single, multiple-purpose reservoir operation: Importance of loss functions and forecast errors. Water Resour. Res., 20 , 11671176.

    • Search Google Scholar
    • Export Citation
  • Draper, A. J., and J. R. Lund, 2004: Optimal hedging and carryover storage value. J. Water Resour. Plan. Manage., 130 (1) 8387.

  • Faber, B. A., and J. R. Stedinger, 2001: Reservoir optimization using sampling SDP with ensemble streamflow prediction (ESP) forecasts. J. Hydrol., 249 , 113133.

    • Search Google Scholar
    • Export Citation
  • Frederiksen, C. S., H. Zhang, R. C. Balgovind, N. Nicholls, W. Drosdowsky, and L. Chambers, 2001: Dynamical seasonal forecasts during the 1997/98 ENSO using persisted SST anomalies. J. Climate, 14 , 26752695.

    • Search Google Scholar
    • Export Citation
  • Georgakakos, A. P., H. Yao, M. G. Mullusky, and K. P. Georgakakos, 1998: Impacts of climate variability on the operational forecast and management of the upper Des Moines River basin. Water Resour. Res., 34 , 799821.

    • Search Google Scholar
    • Export Citation
  • Georgakakos, K. P., and N. E. Graham, 2008: Potential benefits of seasonal inflow prediction uncertainty for reservoir release decisions. J. Appl. Meteor. Climatol., 47 , 12971321.

    • Search Google Scholar
    • Export Citation
  • Georgakakos, K. P., A. P. Georgakakos, and N. E. Graham, 1998: Assessment of benefits of climate forecasts for reservoir management in the GCIP region. GEWEX News, No. 8, International GEWEX Project Office, Silver Spring, MD, 5–7.

    • Search Google Scholar
    • Export Citation
  • Georgakakos, K. P., N. E. Graham, and A. P. Georgakakos, 2000: Can forecasts accrue benefits for reservoir management? The Climate Report, 1 (4) 710.

    • Search Google Scholar
    • Export Citation
  • Georgakakos, K. P., N. E. Graham, T. M. Carpenter, A. P. Georgakakos, and H. Yao, 2005: Integrating climate-hydrology forecasts and multi-objective reservoir management for Northern California. Eos, Trans. Amer. Geophys. Union, 86 .doi:10.1029/2005EO120002.

    • Search Google Scholar
    • Export Citation
  • Goddard, L., and S. J. Mason, 2002: Sensitivity of seasonal climate forecasts to persisted SST anomalies. Climate Dyn., 19 , 619632.

  • Goddard, L., S. J. Mason, S. E. Zebiak, C. F. Ropelewski, R. Basher, and M. A. Cane, 2001: Current approaches to seasonal-to-interannual climate predictions. Int. J. Climatol., 21 , 11111152.

    • Search Google Scholar
    • Export Citation
  • Graham, N. E., K. P. Georgakakos, C. Vargas, and M. Echevers, 2006: Simulating the value of El Niño forecasts for the Panama Canal. Adv. Water Resour., 29 , 16651677.

    • Search Google Scholar
    • Export Citation
  • HRC–GWRI, 2006: Integrated Forecast and Reservoir Management (INFORM) for northern California: System development and initial demonstration. California Energy Commission, PIER Energy-Related Environmental Research Rep. CEC-500-2006-109, Sacramento, CA, 263 pp.

    • Search Google Scholar
    • Export Citation
  • Kelman, J., J. R. Stedinger, L. A. Cooper, E. Hsu, and S-Q. Yuan, 1990: Sampling stochastic dynamic programming applied to reservoir operation. Water Resour. Res., 26 , 447454.

    • Search Google Scholar
    • Export Citation
  • Klemeš, V., 1977: Value of information in reservoir optimization. Water Resour. Res., 13 , 837850.

  • Krzysztofowicz, R., 1979: Comment on ‘Value of information in reservoir optimization’ by V. Klemeš. Water Resour. Res., 15 , 973975.

    • Search Google Scholar
    • Export Citation
  • Mason, S. J., L. Goddard, N. E. Graham, E. Yulaeva, L. Sun, and P. A. Arkin, 1999: The IRI seasonal climate prediction system and the 1997/98 El Niño. Bull. Amer. Meteor. Soc., 80 , 18531873.

    • Search Google Scholar
    • Export Citation
  • McMahon, T. A., A. J. Adeloye, and S-L. Zhou, 2006: Understanding performance measures of reservoirs. J. Hydrol., 324 , 359382. doi:10.1016/j.jhydrol.2005.09.030.

    • Search Google Scholar
    • Export Citation
  • Mood, A. M., F. A. Graybill, and D. C. Boes, 1974: Introduction to the Theory of Statistics. 3rd ed. McGraw-Hill, 564 pp.

  • Naselli-Flores, L., and R. Barone, 2005: Water-level fluctuations in Mediterranean reservoirs: Setting a dewatering threshold as a management tool to improve water quality. Hydrobiologia, 548 , 8599.

    • Search Google Scholar
    • Export Citation
  • NRC, 2006: Completing the Forecast: Characterizing and Communicating Uncertainty for Better Decisions Using Weather and Climate Forecasts. National Academy Press, 178 pp.

    • Search Google Scholar
    • Export Citation
  • Stedinger, J. R., 1978: Comment on ‘Value of information in reservoir optimization’ by V. Klemeš. Water Resour. Res., 14 , 984986.

    • Search Google Scholar
    • Export Citation
  • Talwani, P., L. Chen, and K. Gahalaut, 2007: Seismogenic permeability, ks. J. Geophys. Res., 112 , B07309. doi:10.1029/2006JB004665.

  • Tanaka, S. K., and Coauthors, 2006: Climate warming and water management adaptation for California. Climatic Change, 76 , 361387.

  • Tejada-Guibert, J. A., S. A. Johnson, and J. R. Stedinger, 1995: The value of hydrologic information in stochastic dynamic programming models of a multireservoir system. Water Resour. Res., 31 , 25712579.

    • Search Google Scholar
    • Export Citation
  • VanRheenen, N. T., A. W. Wood, R. N. Palmer, and D. P. Lettenmaier, 2004: Potential implications of PCM climate change scenarios for Sacramento-San Joaquin River Basin hydrology and water resources. Climatic Change, 62 , 257281.

    • Search Google Scholar
    • Export Citation
  • Vogel, R. M., and J. R. Stedinger, 1988: The value of stochastic streamflow models in overyear reservoir design applications. Water Resour. Res., 24 , 14831490.

    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences. 2nd ed. Elsevier Academic Press, 592 pp.

  • Yao, H., and A. P. Georgakakos, 2001: Assessment of Folsom Lake response to historical and potential future climate scenarios: 2. Reservoir management. J. Hydrol., 249 , 176196.

    • Search Google Scholar
    • Export Citation
  • Yeh, W. W-G., 1985: Reservoir management and operations models: A state-of-the-art review. Water Resour. Res., 21 , 17971818.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 256 117 5
PDF Downloads 153 42 3