Underwater Wireless Sensor Networks (UWSNs) consists of various components like vehicles (both underwater and surface), acoustic sensors etc., which can be classified as static, semi-static and dynamic nodes. These are spread across the water bodies to collect the data and to monitor the movement of vehicles, torpedoes etc. All these nodes form as networks and establishes communication with ground stations. Currently, UWSNs face problems and challenges pertain to limited bandwidth, media access control, high propagation delay, 3D topology, spectrum sensing, resource utilization, routing, and power constraints. This proposal deals with the intelligent spectrum sensing in Underwater Cognitive Sonar Communication Networks (CSCN). Here, the improved performance of spectrum sensing in underwater communication is attained by optimizing the cooperative spectrum sensing and data transmission. The parameters of system like sub-channel allocation, and transmission power are optimized by a new hybrid meta-heuristic algorithm by integrating the concepts of Whale Optimization Algorithm (WOA), and Grey Wolf Optimization (GWO) termed as WGWOA. The main intention of optimizing these parameters is to maximize the Spectrum Efficiency (SE) and Energy Efficiency (EE) of the underwater channel communication system. The analysis is done with respect to convergence rate, minimum detection probability, and local sensing time.