Ten years of stochastic water supply modeling of Lower Colorado River Authority of Texas

Ronald E. Anderson and David Walker, Lower Colorado River Authority, Austin, TX, USA


Following the drought of 2006 and 2007, the Lower Colorado River Authority developed a medium-range forecast model to incorporate stochastically-generated hydrology. The model generates inflows and evaporation forecasts by Monte Carlo sampling 75 years of monthly historical records and applying Markov Chain methods conforming to historical cumulative inflow frequencies. LCRA has used the model continuously since its development, including during the severe multi-year drought from 2008 to 2016 when it was used to forecast system storage and lake level outcomes. During this period, LCRA revised the model to reflect three different reservoir operating plans, changing environmental flow requirements, and to incorporate newly available ENSO forecasts and newer hydrologic records. LCRA used the water supply forecasts for contingency planning during the drought. Water treatment operations; lake recreational interests, such as boat ramp and marina operations; water conservation managers; power plant operations; and downstream agricultural operations continue to use lake level and storage forecasts. Each user has unique needs for drought response lead times and differing levels of risk aversion. In addition to forecasting and contingency planning, the stochastic model was used to re-evaluate lake operating guidelines and management strategies originally developed using deterministic methods. Finally, using stochastic modelling introduced new planning and policy challenges, including identifying risk tolerances and determining significance of drought events. Future model improvements may include adjustments for deep persistence low rainfall runoff and migration to a more detailed river system modelling platform.

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