The estimation of mountain-front recharge to regional aquifers is approached from a hydroclimatic standpoint. Analytical models of the seasonal water yield and streamflow are developed in this dissertation. These models are specialized for hard-rock mountainous watersheds where deep percolation occurs through fractures exclusively. Input variables are considered to be stochastic, and a relationship between precipitation and surface runoff is derived by using a deterministic physical process. Streamflow models for the summer and winter rainy seasons are developed separately in terms of known parameters of the storm process and unknown parameters of the physical process. The winter model considers the generation of surface runoff from both rainfall and snowmelt. These models include the long-term effective subsurface outflow from the mountainous watershed, or mountain-front recharge, as one of the parameters to be identified. The parameter estimation problem is posed in the framework of maximum likelihood theory, where prior information about the model parameters and a suitable weighting scheme for the error terms in the estimation criterion are included. The issues of model and parameter identifiability, uniqueness and stability are addressed, and strategies to mitigate identifiability problems in our modeling are discussed. Finally, the seasonal streamflow models are applied to three mountainous watersheds in the Tucson basin, and maximum likelihood estimates of mountain-front recharge and other model and statistical parameters are obtained. The analysis of estimation errors is performed in both the eigenspace and the original space of the parameters.