Underwater compressed air energy storage (UW-CAES), which utilizes flexible underwater air bags to enable constant-pressure  charge  and  discharge,  has  emerged  as  a  compelling  solution  for  renewable  energy  accommodation. However, there remains a distinct lack of research focused on parameter optimization to simultaneously reduce the capital costs of UW-CAES and enhance the operational economics of the plant. To address this critical gap, this paper proposes an optimal  configuration  method  for  UW-CAES  based  on  distributionally  robust  chance  constraints  (DRCC).  First,  a comprehensive UW-CAES system model is established, explicitly accounting for the impact of pipeline pressure losses on system dynamics. Subsequently, an optimal configuration framework incorporating these pressure losses is formulated to optimize  key  system  parameters,  with  the  dual  objectives  of  minimizing  investment  costs  and  maximizing  operational revenues.  Furthermore,  the  DRCC  approach  is  employed  to  reformulate  the  stochastic  chance  constraints  into  tractable linear constraints. This mathematical transformation not only ensures computational efficiency but also facilitates a flexible trade-off between economic optimality and robustness. Case studies demonstrate the efficacy of the proposed methodology: the  optimized  system  maintains  a  rated  discharge  power  of  60  MW  while  reducing  the  required  rated  charge  power  to 53.2  MW−an  8.75%  decrease  compared  to  the  original  baseline−thereby  significantly  improving  overall  system efficiency.  Finally,  sensitivity  analyses  reveal  that  systematically  calibrating  the  confidence  level  and  Wasserstein  radius within  the  DRCC  framework  effectively  navigates  the  equilibrium  between  economic  performance  and  system conservatism