Simple forecast-operations model using hydrologic persistence in Central Texas

The Lower Colorado River Authority (LCRA) is a water conservation and reclamation district that operates a series of six lakes on the watershed of the Lower Colorado River in Central Texas to provide water supply and flood control to a 33-county area, including the City of Austin and several rice ir...

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Bibliographic Details
Published in:Operating Reservoirs in Changing Conditions
Main Authors: Watkins, David W., Wei, Wenge, Nykanen, Deborah K.
Format: Text
Language:unknown
Published: Digital Commons @ Michigan Tech 2006
Subjects:
Online Access:https://digitalcommons.mtu.edu/michigantech-p/8675
https://doi.org/10.1061/40875(212)32
Description
Summary:The Lower Colorado River Authority (LCRA) is a water conservation and reclamation district that operates a series of six lakes on the watershed of the Lower Colorado River in Central Texas to provide water supply and flood control to a 33-county area, including the City of Austin and several rice irrigation districts along the Texas Gulf Coast. In addition, the LCRA produces wholesale power for a 53-county service area and provides water resources for lake recreation activities and in-stream flow maintenance. Currently, the LCRA uses beginning-of-year storage levels to determine the amount of water available to meet demands in the coming year. Seasonal and long-term forecasts are not used by the LCRA for a number of reasons, including high seasonal and annual variability of stream flow, the absence of easily measured hydrologic indicators such as snowpack, and a lack of experience with probabilistic planning methods. In this paper, we illustrate and verify a simple approach for adjusting seasonal water availability forecasts based on hydrologic persistence. Predictor variables include historical monthly streamflow observations and simulated soil moisture content from the NCEP North American Regional Reanalysis. Extensions of the approach are discussed, including generation of probabilistic forecasts and consideration of climate indicators such as the El Nino/Southern Oscillation, Pacific Decadal Oscillation, and North Atlantic Oscillation. Copyright ASCE 2006.