The present paper utilizes the Google Earth Engine (GEE) cloud computing platform and hydro-morphological dataset to understand the complex process-form relationships of the highly braided Brahmaputra River, India. To identify dynamic gradients between low and high risk of geomorphic adjustment/change, an analytical approach is developed to track and quantify the spatial patterns of geomorphic adjustment. In order to address the dominant geomorphological adjustments, two processed-based novel indicators are developed- the Normalised Threshold Exceedance (NTE) considering the excess energy theory, and the Normalised Process Gradient (NPG) utilizing the gradient between hierarchical thresholds. The results show that in a highly braided river system, the sand bar adjustments prevail over other forms of morphological changes and is closely dependent on the process gradient between the hierarchical thresholds. Further, the scale of planform evolution is computed from the Location Probability Index (LPI), and the geomorphic stationarity concept is introduced for a large braided river. Finally, a multi-faceted resilience-based freedom space management approach is designed based on system state trajectory, LPI variability, proximity to thresholds, and in-channel landform configuration.