Developing and Evaluating Drought Indicators for Decision-Making

Anne Steinemann Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

Search for other papers by Anne Steinemann in
Current site
Google Scholar
PubMed
Close
,
Sam F. Iacobellis Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

Search for other papers by Sam F. Iacobellis in
Current site
Google Scholar
PubMed
Close
, and
Daniel R. Cayan Scripps Institution of Oceanography, University of California, San Diego, and U.S. Geological Survey, La Jolla, California

Search for other papers by Daniel R. Cayan in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Drought indicators can help to detect, assess, and reduce impacts of drought. However, existing indicators often have deficiencies that limit their effectiveness, such as statistical inconsistency, noncomparability, arbitrary metrics, and lack of historic context. Further, indicators selected for drought plans may be only marginally useful, and relatively little prior work has investigated ways to design operationally practical indicators. This study devises a generalizable approach, based on feedback from users, to develop and evaluate indicators for decision-making. This approach employs a percentile-based framework that offers clarity, consistency, and comparability among different indicators, drought levels, time periods, and spatial scales. In addition, it characterizes the evolution of droughts and quantifies their severity, duration, and frequency. User preferences are incorporated into the framework’s parameters, which include percentile thresholds for drought onset and recovery, severity levels, anomalies, and consecutive time periods for triggering. To illustrate the approach and decision-making implications, the framework is applied to California Climate Division 2 and is used with decision-makers, water managers, and other participants in the National Integrated Drought Information System (NIDIS) California Pilot. Stakeholders report that the framework provides an easily understood and beneficial way to assess and communicate drought conditions, validly compare multiple indicators across different locations and time scales, quantify risks relative to historic droughts, and determine indicators that would be valuable for decision-making.

Current affiliation: Melbourne School of Engineering, The University of Melbourne, Melbourne, Victoria, Australia.

Corresponding author address: Anne Steinemann, School of Engineering, The University of Melbourne, Melbourne VIC 3010, Australia. E-mail: anne.steinemann@unimelb.edu.au

Abstract

Drought indicators can help to detect, assess, and reduce impacts of drought. However, existing indicators often have deficiencies that limit their effectiveness, such as statistical inconsistency, noncomparability, arbitrary metrics, and lack of historic context. Further, indicators selected for drought plans may be only marginally useful, and relatively little prior work has investigated ways to design operationally practical indicators. This study devises a generalizable approach, based on feedback from users, to develop and evaluate indicators for decision-making. This approach employs a percentile-based framework that offers clarity, consistency, and comparability among different indicators, drought levels, time periods, and spatial scales. In addition, it characterizes the evolution of droughts and quantifies their severity, duration, and frequency. User preferences are incorporated into the framework’s parameters, which include percentile thresholds for drought onset and recovery, severity levels, anomalies, and consecutive time periods for triggering. To illustrate the approach and decision-making implications, the framework is applied to California Climate Division 2 and is used with decision-makers, water managers, and other participants in the National Integrated Drought Information System (NIDIS) California Pilot. Stakeholders report that the framework provides an easily understood and beneficial way to assess and communicate drought conditions, validly compare multiple indicators across different locations and time scales, quantify risks relative to historic droughts, and determine indicators that would be valuable for decision-making.

Current affiliation: Melbourne School of Engineering, The University of Melbourne, Melbourne, Victoria, Australia.

Corresponding author address: Anne Steinemann, School of Engineering, The University of Melbourne, Melbourne VIC 3010, Australia. E-mail: anne.steinemann@unimelb.edu.au
Save
  • Anderson, M. C., Hain C. , Otkin J. , Zhan X. , Mo K. , Svoboda M. , Wardlow B. , and Pimstein A. , 2013: An intercomparison of drought indicators based on thermal remote sensing and NLDAS-2 simulations with U.S. Drought Monitor classifications. J. Hydrometeor., 14, 10351056, doi:10.1175/JHM-D-12-0140.1.

    • Search Google Scholar
    • Export Citation
  • California Department of Water Resources, 2000: Preparing for California’s next drought. DWR Rep., Natural Resources Agency, State of California, 66 pp. [Available online at www.water.ca.gov/waterconditions/docs/Drought_Report_87-92.pdf.]

  • California Department of Water Resources, 2012: Drought in California. DWR Rep. Natural Resources Agency, State of California, 11 pp. [Available online at www.water.ca.gov/waterconditions/docs/Drought2012.pdf.]

  • Carrão, H., Singleton A. , Naumann G. , Barbosa P. , and Vogt J. V. , 2014: An optimized system for the classification of meteorological drought intensity with applications in drought frequency analysis. J. Appl. Meteor. Climatol., 53, 19431960, doi:10.1175/JAMC-D-13-0167.1.

    • Search Google Scholar
    • Export Citation
  • Guttman, N. B., Wallis J. R. , and Hosking J. R. M. , 1992: Spatial comparability of the Palmer drought severity index. J. Amer. Water Resour. Assoc., 28, 11111119, doi:10.1111/j.1752-1688.1992.tb04022.x.

    • Search Google Scholar
    • Export Citation
  • Hao, Z., and AghaKouchak A. , 2014: A nonparametric multivariate multi-index drought monitoring framework. J. Hydrometeor., 15, 89101, doi:10.1175/JHM-D-12-0160.1.

    • Search Google Scholar
    • Export Citation
  • Keyantash, J., and Dracup J. A. , 2002: The quantification of drought: An evaluation of drought indices. Bull. Amer. Meteor. Soc., 83, 11671180, doi:10.1175/1520-0477(2002)083<1191:TQODAE>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • McKee, T. B., Doesken N. J. , and Kleist J. , 1993: The relationship of drought frequency and duration to time scale. Eighth Conf. on Applied Climatology, Anaheim, CA, Amer. Meteor. Soc., 179–184.

    • Search Google Scholar
    • Export Citation
  • Mizzell, H., Carbone G. , Dow K. , and Rhee J. , 2010: Addressing monitoring needs for drought management. Proc. South Carolina Water Resources Conf., Columbia, SC, Clemson University, 6 pp. [Available online at www.cisa.sc.edu/Pubs_Presentations_Posters/Conference%20Proceedings%20Papers/2010_Mizzell%20et%20al_Addressing%20monitoring%20needs%20for%20drought%20management.pdf.]

  • Mo, K. C., and Lettenmaier D. P. , 2014: Objective drought classification using multiple land surface models. J. Hydrometeor., 15, 9901010, doi:10.1175/JHM-D-13-071.1.

    • Search Google Scholar
    • Export Citation
  • NCDC, 2013: Billion-dollar weather/climate disasters. Accessed 29 October 2014. [Available online at www.ncdc.noaa.gov/billions.]

  • NIDIS, 2006: National Integrated Drought Information System Act of 2006. Pub. L. 109-430, 15 U.S.C. 311 and 313d. [Available online at www.gpo.gov/fdsys/pkg/PLAW-109publ430/pdf/PLAW-109publ430.pdf.]

  • NIDIS, 2014: California DEWS pilot. National Integrated Drought Information System, accessed 29 October 2014. [Available online at http://drought.gov/drought/content/california-california-dews-pilot.]

  • Paulo, A. A., and Pereira L. S. , 2008: Stochastic prediction of drought class transitions. Water Resour. Manage., 22, 12771296, doi:10.1007/s11269-007-9225-5.

    • Search Google Scholar
    • Export Citation
  • Quiring, S. M., 2009: Developing objective operational definitions for monitoring drought. J. Appl. Meteor. Climatol., 48, 12171229, doi:10.1175/2009JAMC2088.1.

    • Search Google Scholar
    • Export Citation
  • Redmond, K. T., 1991: Climate monitoring and indices. Drought Management and Planning: Proceedings of the Seminar and Workshop,Wilhite D. A. , Wood D. A. , and Kay P. A. , Eds, University of Nebraska–Lincoln, 2933.

  • Redmond, K. T., 2002: The depiction of drought: A commentary. Bull. Amer. Meteor. Soc., 83, 11431147, doi:10.1175/1520-0477(2002)083<1143:TDODAC>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Shukla, S., Steinemann A. , and Lettenmaier D. P. , 2011: Drought monitoring for Washington State: Indicators and applications. J. Hydrometeor., 12, 6683, doi:10.1175/2010JHM1307.1.

    • Search Google Scholar
    • Export Citation
  • Steinemann, A., 2003: Drought indicators and triggers: A stochastic approach to evaluation. J. Amer. Water Resour. Assoc., 39, 12171233, doi:10.1111/j.1752-1688.2003.tb03704.x.

    • Search Google Scholar
    • Export Citation
  • Steinemann, A., 2014: Drought information for improving preparedness in the western states. Bull. Amer. Meteor. Soc., 95, 843847, doi:10.1175/BAMS-D-13-00067.1.

    • Search Google Scholar
    • Export Citation
  • Steinemann, A., and Cavalcanti L. , 2006: Developing multiple indicators and triggers for drought plans. J. Water Resour. Plann. Manage., 132, 164174, doi:10.1061/(ASCE)0733-9496(2006)132:3(164).

    • Search Google Scholar
    • Export Citation
  • Steinemann, A., Hayes M. , and Cavalcanti L. , 2005: Drought indicators and triggers. Drought and Water Crises: Science, Technology, and Management Issues, D. Wilhite, Ed., CRC Press, 71–92.

  • Svoboda, M., and Coauthors, 2002: The Drought Monitor. Bull. Amer. Meteor. Soc., 83, 11811190, doi:10.1175/1520-0477(2002)083<1181:TDM>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Vose, R. S., Applequist S. , Durre I. , Menne M. J. , Williams C. N. , Fenimore C. , Gleason K. , and Arndt D. , 2014: Improved historical temperature and precipitation time series for U.S. climate divisions. J. Appl. Meteor. Climatol., 53, 12321251, doi:10.1175/JAMC-D-13-0248.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1993 1119 76
PDF Downloads 931 246 16