The notion of convergent and transdisciplinary integration, which is about braiding together different knowledge systems, is becoming the mantra of numerous initiatives aimed at tackling pressing water challenges. Yet, the transition from rhetoric to actual implementation is impeded by incongruence in semantics, methodologies, and discourse among disciplinary scientists and societal actors. Here, we embrace “integrated modeling”—both quantitatively and qualitatively—as a vital exploratory instrument to advance such integration, providing a means to navigate complexity and manage the uncertainty associated with understanding, diagnosing, predicting, and governing human‐water systems. From this standpoint, we confront disciplinary barriers by offering seven focused reviews and syntheses of existing and missing links across the frontiers distinguishing surface and groundwater hydrology, engineering, social sciences, economics, Indigenous and place‐based knowledge, and studies of other interconnected natural systems such as the atmosphere, cryosphere, and ecosphere. While there are, arguably, no bounds to the pursuit of inclusivity in representing the spectrum of natural and human processes around water resources, we advocate that integrated modeling can provide a focused approach to delineating the scope of integration, through the lens of three fundamental questions: (a) What is the modeling “purpose”? (b) What constitutes a sound “boundary judgment”? and (c) What are the “critical uncertainties” and their compounding effects? More broadly, we call for investigating what constitutes warranted “systems complexity,” as opposed to unjustified “computational complexity” when representing complex natural and human‐natural systems, with careful attention to interdependencies and feedbacks, scaling issues, nonlinear dynamics and thresholds, hysteresis, time lags, and legacy effects.