UC Davis

We introduce a new approach for improving estimates of water balance components, applicable to a multi-period water balance series for a lake, watershed, or other area of any size. It consists of making use of statistical relationships between a component series estimate and the residual errors of the water mass balance series. Through this approach, two novel specific techniques are developed. The first, ‘precipitation-decorrelation’, entails implementing a criterion of decorrelation of residual errors from precipitation estimates. The second, ‘residual-redistribution’, consists of redistributing each residual error over initial water balance component estimates, in accord with an error minimization criterion for each component series. Efficacy is tested using series of annual water balances for the Tahoe Basin. Upon implementation of precipitation-decorrelation, a tightly bounded statistical estimate of mean annual Lake Tahoe evaporation is obtained, which closely matches independent measurement-based estimates. Residual-redistribution yields revised estimates of annual series of Tahoe areal precipitation and watershed runoff, which are each shown to have substantially reduced random error variance. Highly precise revised estimates of inter-annual variations in Tahoe precipitation have enabled resolution of the watershed multi-year ‘memory’ of precipitation, and more reliable separation of inter-annual changes in watershed storage from inter-annual variations in atmospheric loss.