Alluvial sand and gravel (ASG) aquifers are highly heterogeneous and exhibit strong, spatially variable anisotropy, often interspersed by buried paleo‐channels of increased hydraulic conductivity. Groundwater flow and solute transport is often characterized by preferential flow caused by anisotropic properties in ASG aquifers. Connected ASG subsurface structures such as buried paleo‐channels, however, are difficult to reproduce with commonly used techniques, and anisotropy is rarely considered in applied groundwater models. To ease the notoriously difficult problem of how to consider anisotropy, we propose a novel modeling framework based on calibration of an integrated surface‐subsurface hydrological model via spatially varying, preferred anisotropy pilot point inversion. The inversion leverages hydraulic and tracer‐based observations representing multiple spatial and temporal scales. We demonstrate the applicability of the framework on a real‐world ASG site used for drinking water production, and we quantify the information content of observations to identify connected paleo‐channels and provide guidance for optimal field‐data acquisition. Plain Language Summary Mountainous river corridors are used worldwide for drinking water production, as they represent a relatively safe and sustainable source of drinking water. The valley‐fill of mountainous river corridors is a result of millennia of fluvio‐glacial erosion and deposition via braided river systems and consists primarily of poorly sorted sand and gravel. Groundwater flow and solute transport through such alluvial sand and gravel (ASG) aquifers is characterized by preferential flow paths caused by formerly active, now buried meanders (i.e., paleo‐channels). The identification of paleo‐channels in ASG aquifers is crucial for safe drinking water production, but they are notoriously difficult to identify with the commonly used techniques. We propose a new modeling framework based on the calibration of an integrated surface‐subsurface hydrological model via spatially varying, preferred anisotropy pilot point inversion using both hydraulic and tracer observations. The new modeling framework is more efficient than other approaches to model flow through complex ASG aquifers and doesn't require precise prior knowledge of the location of paleo‐channels. The applicability and robustness of the framework is demonstrated on an ASG drinking water wellfield located in the Swiss Alps. Key Points Novel framework for identifying and quantifying groundwater flow through buried paleo‐channels Heterogeneous hydraulic conductivity fields were identified based on spatially varying, preferred anisotropy‐constrained inversion The fraction of infiltrating stream water in the aquifer and stream‐aquifer exchange fluxes best inform the paleo‐channel