摘要: The recently launched California water price index (NASDAQ: NQH2O) and corresponding futures market provide an opportunity for water users to hedge against seasonal drought risk. While the volume of futures trading remains low, the index can be analyzed as a spatially aggregated price of physical water trades that responds to hydrology and management. This study investigates the extent to which the NQH2O index can be predicted from a combination of reservoir storage anomalies and inflow forecasts throughout the state. Over the available record (November 2013–June 2023), the daily hydrologic time-series are reduced to a set of principal components, which are shown to be nonlinearly correlated with the current and season-ahead price index. The PCs are then used as features in an exponential regression to predict the forward six-month average price. The most accurate model in cross-validation performs …