Objective: Blue spaces have been gradually recognized due to their positive impact on human mental and physical well-being. However, existing works have greatly depended on subjective questionnaires and lack objective and quantitative evidence, especially regarding the effects of specific spatial scales of water environments on brain activity. Methods: To address this gap, this study uses virtual reality (VR) technology to construct immersive waterbody environments with systematically varied visual and auditory properties, which enables controlled experimental exposure to different water space scales. A total of 52 healthy participants aged 18-36 from Tsinghua University were involved in experiencing 35 water scenarios characterized by five levels of visible water area (0%, 30%, 50%, 80%, and 100%) and seven flow velocity levels (0-3.0 m/s). During the VR exposure, two neurophysiological indicators—electroencephalogram (EEG) alpha power and heart rate variability (HRV)—were concurrently recorded to reflect the cognitive and autonomic brain states of the participants. EEG alpha activity, which is associated with relaxation and creative ideation, and HRV, which is an index of emotional regulation and adaptive capacity, served as core outcome measures. After signal preprocessing and normalization, Gaussian process regression was adopted to model the nonlinear coupling between water environment features and physiological responses. Results: Results revealed significant interindividual variability in responses to water scale. For the majority of participants (Class I), moderate visible water areas (10%-30%) combined with low flow velocities (0.5-1.5 m/s) exhibited the most favorable neurophysiological responses, with EEG alpha power and HRV values increasing beyond resting baseline levels. However, these values decreased substantially in scenes with excessively large water areas (>50%) or higher flow velocities, which suggests that overstimulation from water features may suppress cognitive readiness and emotional stability. By contrast, a minority group (Class II) displayed the opposite pattern, which exhibited stronger EEG and HRV responses under conditions of larger water areas and either very low or high flow speeds. This divergence emphasizes the important role of individual backgrounds in shaping responses to blue space. Furthermore, a support vector machine classification model was developed based on the demographic and environmental background data of participants (including birthplace precipitation, humidity, and surface water ratio), which accurately predicted individual response categories with an accuracy of 95%. In addition, a single-factor analysis of water sound levels disclosed that moderate auditory stimuli (~30 dB) improved EEG alpha activity even in the absence of visual water elements, which reinforces the cognitive benefits of natural soundscapes and implies potential for non-visual design interventions. Conclusions: Overall, this study constructs a robust experimental and modeling framework to quantify the neurocognitive impact of waterbody scale, which offers new insights into the modulating mechanism of specific aquatic features on brain states in dynamic and individualized ways. The findings show that the restorative and creativity-enhancing effects of blue space are neither universal nor linear but rather depend on environmental parameters and individual characteristics. Thus, these outcomes challenge conventional assumptions and highlight the need for tailored blue space design. The proposed method provides valuable scientific evidence for optimizing urban water landscapes not only for aesthetic or ecological purposes but also as cognitive infrastructures that support mental health, emotional resilience, and innovation across diverse populations and geographic contexts.