ESTIMATION OF MOUNTAIN FRONT RECHARGE TO REGIONAL AQUIFERS .2. A MAXIMUM-LIKELIHOOD APPROACH INCORPORATING PRIOR INFORMATION

In this two-part series a stochastic estimation procedure applicable t o the analytic streamflow model derived in the companion is introduced . The parameter estimation problem is posed in the framework of maximu m likelihood theory, where prior information about the model parameter s and a suitable weighting scheme for the error terms in the estimatio n criterion are included. Various optimization methods are combined fo r parameter estimation. The issues of model and parameter identifiabil ity, uniqueness, and stability are addressed, and strategies to mitiga te identifiability problems in our modeling are discussed. The seasona l streamflow model is applied to a mountainous watershed in southern A rizona, and maximum likelihood estimates of mountain front recharge an d other model and statistical parameters are obtained. The analysis of estimation errors is performed in both the eigenspace and the origina l space of the parameters.