Seasonal Forecast of the California Water Price Index

Abstract

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 with R2=0.81 using four PCs that contain 85% of the total variance in the features. Predictions generally fall within $100/AF of the observed value, with larger errors associated with hydrologic forecast uncertainty during the winter. A threshold-based hedging strategy is developed to analyze the potential cost savings of buying during the winter (November–March) when the forecasted six-month average price is greater than the current index. This strategy shows an average cost reduction of 17% compared with the six-month average price, with reductions above 35% at the onset of dry water years. This study contributes a statistical modeling approach to support the development of more advanced hedging strategies in water portfolios.