Editorial Type:
Article
Article Type:
Research Article

A Stochastic Conceptual Modeling Approach for Examining the Effects of Climate Change on Streamflows in Mountain Basins

Peter R. Furey Natural Resources Ecology Laboratory, Colorado State University, Fort Collins, Colorado

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Stephanie K. Kampf Natural Resources Ecology Laboratory, Colorado State University, Fort Collins, Colorado

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Jordan S. Lanini Natural Resources Consulting Engineers, Inc., Fort Collins, Colorado

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Andre Q. Dozier Natural Resources Consulting Engineers, Inc., Fort Collins, Colorado

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Print Publication:
01 Jun 2012
DOI:
https://doi.org/10.1175/JHM-D-11-037.1
Page(s):
837–855
Restricted access

Abstract

This study presents a modeling approach for examining how changes in climate affect streamflow in mesoscale mountain basins dominated by snowmelt runoff. A conceptual snowmelt-runoff model was developed that is forced by daily time series of temperature and precipitation. The model can be run using either observed climate data or artificial climate data generated from a GCM or a stochastic model. The model was applied to a case-study basin, the north fork of the Clearwater River in Idaho, using stochastically generated climate scenarios. Climate scenarios were generated using a contemporaneous auto-regressive integrated moving average (CARIMA) model for temperature and a precipitation model based on a two-state first-order Markov process. A baseline climate scenario was developed that represents recently observed temperature and precipitation conditions and then 15 additional climate scenarios that represent shifts in recent conditions. For each scenario, model application produced an ensemble of 50 streamflow traces each spanning 30 yr. Results show that an increase in temperature among scenarios leads to a decrease in streamflow and vice versa. Decreases in temperature shift the basin runoff to fully snowmelt dominated, whereas increases in temperature increase the frequency of midwinter runoff events. Increasing precipitation leads to increased runoff in cases where the temperature remains the same as the observed record, but not in cases where the temperature increases. The modeling approach presented here can be used by water managers to examine which types of climate change could require modifications in water planning and operations.

Corresponding author address: Peter Furey, NorthWest Research Associates, 3380 Mitchell Lane, Boulder, CO 80301. E-mail: furey@cora.nwra.com

Abstract

This study presents a modeling approach for examining how changes in climate affect streamflow in mesoscale mountain basins dominated by snowmelt runoff. A conceptual snowmelt-runoff model was developed that is forced by daily time series of temperature and precipitation. The model can be run using either observed climate data or artificial climate data generated from a GCM or a stochastic model. The model was applied to a case-study basin, the north fork of the Clearwater River in Idaho, using stochastically generated climate scenarios. Climate scenarios were generated using a contemporaneous auto-regressive integrated moving average (CARIMA) model for temperature and a precipitation model based on a two-state first-order Markov process. A baseline climate scenario was developed that represents recently observed temperature and precipitation conditions and then 15 additional climate scenarios that represent shifts in recent conditions. For each scenario, model application produced an ensemble of 50 streamflow traces each spanning 30 yr. Results show that an increase in temperature among scenarios leads to a decrease in streamflow and vice versa. Decreases in temperature shift the basin runoff to fully snowmelt dominated, whereas increases in temperature increase the frequency of midwinter runoff events. Increasing precipitation leads to increased runoff in cases where the temperature remains the same as the observed record, but not in cases where the temperature increases. The modeling approach presented here can be used by water managers to examine which types of climate change could require modifications in water planning and operations.

Corresponding author address: Peter Furey, NorthWest Research Associates, 3380 Mitchell Lane, Boulder, CO 80301. E-mail: furey@cora.nwra.com
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Journal of Hydrometeorology

  • Bloomfield, P., 1992: Trends in global temperature. Climatic Change, 21, 1–16.

  • Blöschl, G., and Montanari A. , 2010: Climate change impacts—Throwing the dice? Hydrol. Processes, 24, 374–381.

  • Brandon, D. G., 2005: Using NWSRFS ESP for making early outlooks of seasonal runoff volumes into Lake Powell. Extended Abstracts, AMS Forum: Living with a Limited Water Supply, San Diego, CA, Amer. Meteor. Soc., 1.5. [Available online at http://ams.confex.com/ams/Annual2005/techprogram/paper_84342.htm.]

  • Caballero, R., Jewson S. , and Brix A. , 2002: Long memory in surface air temperature: Detection, modeling, and application to weather derivative valuation. Climate Res., 21, 127–140.

    • Search Google Scholar
    • Export Citation

  • Cary, L. E., 1984: Application of the U.S. Geological Survey’s Precipitation-Runoff Modeling System to the Prairie Dog Creek basin, Southeastern Montana. U.S. Geological Survey Water-Resources Investigations Rep. 84-4178, 98 pp.

  • Christensen, N., Wood A. , Voisin N. , Lettenmaier D. , and Palmer R. , 2004: Effects of climate change on the hydrology and water resources of the Colorado River basin. Climatic Change, 62, 337–363.

    • Search Google Scholar
    • Export Citation

  • Dettinger, M. D., Cayan D. R. , Meyer M. K. , and Jeton A. E. , 2004: Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900-2099. Climatic Change, 62, 283–317.

    • Search Google Scholar
    • Export Citation

  • Ecovista, Nez Perce Tribe Wildlife Division, and Washington State University Center for Environmental Education, 2003: Draft—Clearwater subbasin assessment. Northwest Power and Conservation Council Rep., 479 pp. [Available online at http://www.nwcouncil.org/fw/subbasinplanning/clearwater/plan/assessment.pdf.]

  • Gentleman, R., Ihaka R. , and R Project Contributors, cited 2009: The R Foundation for Statistical Computing. [Available online at http://www.r-project.org.]

  • Gómez-Landesa, E., and Rango A. , 2002: Operational snowmelt runoff forecasting in the Spanish Pyrenees using the snowmelt runoff model. Hydrol. Processes, 16, 1583–1591.

    • Search Google Scholar
    • Export Citation

  • Guan, H., Wilson J. L. , and Xie H. , 2009: A cluster-optimizing regression-based approach for precipitation spatial downscaling in mountainous terrain. J. Hydrol., 375, 578–588.

    • Search Google Scholar
    • Export Citation

  • Hamlet, A. F., and Lettenmaier D. , 1999a: Columbia River streamflow forecasting based on ENSO and PDO climate signals. J. Water Resour. Plann. Manage., 125, 333–341.

    • Search Google Scholar
    • Export Citation

  • Hamlet, A. F., and Lettenmaier D. , 1999b: Effects of climate change on hydrology and water resources in the Columbia River basin. Amer. Water Res. Assoc., 35, 1597–1623.

    • Search Google Scholar
    • Export Citation

  • Hay, L. E., and Clark M. P. , 2003: Use of statistically and dynamically downscaled atmospheric model output for hydrologic simulations in three mountainous basins in the western United States. J. Hydrol., 282, 56–75.

    • Search Google Scholar
    • Export Citation

  • Hundecha, Y., Pahlow M. , and Schumann A. , 2009: Modeling of daily precipitation at multiple locations using a mixture of distributions to characterize the extremes. Water Resour. Res., 45, W12412, doi:10.1029/2008WR007453.

    • Search Google Scholar
    • Export Citation

  • Jasper, K., Calanca P. , Gyalistras D. , and Fuhrer J. , 2004: Differential impacts of climate change on the hydrology of two alpine river basins. Climate Res., 26, 113–129.

    • Search Google Scholar
    • Export Citation

  • Lawrance, A. J., and Kottegoda N. T. , 1977: Stochastic modelling of river flow time series. J. Roy. Stat. Soc., 140A, 1–47.

  • Leavesley, G. H., Lichty R. W. , Troutman B. M. , and Saindon L. G. , 1983: Precipitation-runoff modeling system—User’s manual. U.S. Geological Survey Water-Resources Investigations Rep. 83-4238, 207 pp.

  • Leavesley, G. H., Markstrom S. L. , Viger R. J. , and Hay L. E. , 2005: USGS Modular Modeling System (MMS)—Precipitation-Runoff Modeling System (PRMS) MMS-PRMS. Watershed Models, V. Singh and D. Frevert, Eds., CRC Press, 159–177.

  • Liang, X., Lettenmaier D. P. , Wood E. F. , and Burges S. J. , 1994: A simple hydrologically based model of land surface water and energy fluxes for GSMs. J. Geophys. Res., 99 (D7), 14 415–14 428.

    • Search Google Scholar
    • Export Citation

  • Markoff, M. S., and Cullen A. , 2008: Impact of climate change on Pacific Northwest hydropower. Climatic Change, 87, 451–269.

  • Martinec, J., and Rango A. , 1986: Parameter values for snowmelt runoff modelling. J. Hydrol., 84, 197–219.

  • Martinec, J., Rango A. , and Roberts R. , 2008: Snowmelt Runoff Model (SRM) user’s manual. New Mexico State University, Agricultural Experiment Station Special Rep. 100, 177 pp.

  • Mehrotra, R., and Sharma A. , 2006: A nonparametric stochastic downscaling framework for daily rainfall at multiple locations. J. Geophys. Res., 111, D15101, doi:10.1029/2005JD006637.

    • Search Google Scholar
    • Export Citation

  • Molini, A., Katul G. G. , and Porporato A. , 2011: Maximum discharge from snowmelt in a changing climate. Geophys. Res. Lett., 38, L05402, doi:10.1029/2010GL046477.

    • Search Google Scholar
    • Export Citation

  • Mote, P. W., and Coauthors, 2003: Preparing for climatic change: The water, salmon, and forests of the Pacific Northwest. Climatic Change, 61, 45–88.

    • Search Google Scholar
    • Export Citation

  • Ng, W. W., and Panu U. S. , 2010: Comparisons of traditional and novel stochastic models for the generation of daily precipitation occurrences. J. Hydrol., 380, 222–236.

    • Search Google Scholar
    • Export Citation

  • Raisanen, J., 2007: How reliable are climate models? Tellus, 59, 2–29.

  • Rajagopalon, B., and Lall U. , 1999: A k-nearest neighbor simulator for daily precipitation and other weather variables. Water Resour. Res., 35, 3089–3101.

    • Search Google Scholar
    • Export Citation

  • Rango, A., and van Katwijk V. , 1990: Development and testing of a snowmelt-runoff forecasting technique. Water Resour. Bull., 26, 135–144.

    • Search Google Scholar
    • Export Citation

  • Rango, A., and Martinec J. , 1994: Areal extent of seasonal snow cover in a changed climate. Nord. Hydrol., 25, 233–246.

  • Salas, J. D., 1993: Analysis and modeling of hydrologic time series. Handbook of Hydrology, D. R. Maidment, Ed., McGraw-Hill, Inc., 19.1–19.72.

  • Salathé, E. P., Mote P. W. , and Wiley M. W. , 2007: Review of scenario selection and downscaling methods for the assessment of climate change impacts on hydrology in the United States Pacific Northwest. Int. J. Climatol., 27, 1611–1621.

    • Search Google Scholar
    • Export Citation

  • Schär, C., and Frei C. , 2005: Orographic precipitation and climate change. Global Change and Mountain Regions, U. M. Huber, H. K. M. Bugmann, and M. A. Reasoner, Eds., Springer, 255–266.

  • Soncini-Sessa, R., and Volta M. , 2005: One-year-long runoff forecast by a single snowpack evaluation. Hydrol. Processes, 19, 1419–1430.

    • Search Google Scholar
    • Export Citation

  • The MathWorks, Inc., cited 2009: MATLAB—R2009b. [Available online at http://www.mathworks.com.]

  • Wagener, T., Gupta H. V. , and Sorooshian S. , 2004: Stochastic formulation of a conceptual hydrological model. B. Webb, Ed., Vol. 1, Hydrology: Science and Practice for the 21st Century, British Hydrological Society, 398–405.

  • Wood, A. W., Leung L. R. , Sridhar V. , and Lettenmaier D. P. , 2004: Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Climatic Change, 62, 189–216.

    • Search Google Scholar
    • Export Citation

  • Xu, C., 1999: From GCMs to river flow: A review of downscaling methods and hydrologic modelling approaches. Prog. Phys. Geogr., 23, 229–249.

    • Search Google Scholar
    • Export Citation

  • Young, G. K., and Pisano W. C. , 1968: Operational hydrology using residuals. J. Hydraul. Div., 94, 909–923.

  • Yue, S., Pilon P. , and Cavadias G. , 2002: Power of the Mann–Kendall and Spearman’s rho tests for detecting monotonic trends in hydrological series. J. Hydrol., 259, 254–271.

    • Search Google Scholar
    • Export Citation
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