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    Short To Medium Range Hydrometeorological Forecasting In The Rio Grijalva Basin, Mexico

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    Author
    Uribe, Edgar M
    Issue Date
    2007
    Keywords
    Hydrology Prediction Meteorology Grijalva Basin Reanalysis
    Advisor
    Shuttleworth, William J
    Committee Chair
    Shuttleworth, William J
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    The Rio Grijalva basin is the most important basin in Mexico in terms of hydropower production and damages related to extreme rainfall events. This study investigates establishing a short- to medium-range hydrometeorological forecasting system for this basin which comprises a hydrological model and a regional Numerical Weather Prediction Model (NWPM). A physical, distributed, hydrological model (MMS-PRMS) is implemented through the following steps: (1) basin parameterization; (2) interfacing to observed meteorological fields, and (3) parameter optimization. The datasets normally used to parameterize the MMS-PRMS are only available in the US so an alternative methodology for deriving parameters from globally available public datasets was devised. Modeled streamflow calculated by model with the initial parameters was in good agreement with observed streamflow, and optimization yielded even better agreement. The predictive capabilities of the hydrological model was then tested by implementing modeled rainfall and temperature from the North American Regional Reanalysis (NARR), these data being used as a surrogate for those that would be available from a regional NWPM. A significant bias in NARR-rainfall was identified and a novel probabilistic correction procedure devised. This procedure was then extended to provide estimates of uncertainty in the modeled streamflow. Within the calculated uncertainty, the modeled streamflow calculated with these corrected NARR data is in good agreement with modeled streamflow calculated using local meteorological data.
    Type
    text
    Electronic Dissertation
    Degree Name
    PhD
    Degree Level
    doctoral
    Degree Program
    Hydrology
    Graduate College
    Degree Grantor
    University of Arizona
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