In developing countries like Bangladesh, river discharge monitoring networks are designed unseemly, operated poorly, and often fail to reach their purposes resulting in the unavailability of sufficient data to describe the behavior of such systems. In these cases, water-related decisions may create problems for the environment, the regional economy, and society. This paper has investigated the application of Shannon’s Information Theory to design and evaluate an efficient discharge monitoring network for the Surma River. A 1-D model has been formulated to extract all discharge data at different points of Surma River using MIKE 11. The appropriate monitoring station locations were determined by optimizing two conflicting objective functions (joint entropy and total correlation) using the Non-dominated Sorting Genetic Algorithm-II and Greedy algorithm. The study demonstrates that an informative yet less redundant monitoring network configuration can be found through the greedy algorithm.