Determining forecast and decision horizons for reservoir operations under hedging policies

Abstract

Hedging policies for reservoir operations makes a small deficit in current supply to reduce the probability of a severe water shortage in the future. One of the critical questions for hedging research is how long the forecast period should be so that reliable inflow forecast in the period can be used for decision making under hedging. Decision makers always hope to look further into the future; however, the longer the forecast period, the more uncertain and less reliable the involved information, which will have a diminishing influence on decision making. For dynamic reservoir operation optimization models, the decision horizon (DH) may be defined as the initial periods in which decisions are not affected by forecast data beyond a certain period, defined as the forecast horizon (FH). This paper determines FH with given DH for dynamic reservoir operation problems through both theoretical and numerical analysis. We use order of magnitude analysis and numerical modeling to identify the impact of various factors such as water stress level (the deficit between water availability and demand), reservoir size, inflow uncertainty, evaporation rate, and discount rate. Three types of inflow time series are used: stationary, nonstationary with seasonality, and random walk. Results show that inflow characteristics and reservoir capacity have major impacts on FH when water stress is modest; larger reservoir capacity and the deterministic component of inflow such as seasonality require a longer FH. Economic factors have strong impacts when water stress levels are high. Copyright 2008 by the American Geophysical Union.