Abstract: Reversible pump turbines are extensively used in pumped storage plants to bear the base loads and rapidly respond to power grid demands by switching operating conditions, thus significantly contributing to the integration of new energy sources into the grid. To improve the energy efficiency, structural function and operational stability of pump turbine, this study designs a medium to high head pump turbine (H_T=315 m, H_P=310 m) from the two-way perspective: hydraulic performance and sediment abrasion performance. The design process involves controlling the load distribution on the blade crown and band streamlines using an inverse method, determining the meridional flow passage shape through curve interpolation, and formulating the initial pump-turbine design. The method of equal velocity moment is applied to define the change in cross-sectional areas of the volute, while equirectangular helix method is used to design the guide vane profiles. Optimization of the preliminary pump-turbine design is achieved using the Latin hypercube sampling algorithm combined with the NSGA-II non-dominated sorting genetic algorithm, generating a Pareto front of optimal solutions within the design space. The SST k-ω turbulence model and the Tabakoff abrasion model are adopted to investigate hydraulic and abrasion performance of various pump turbine designs by numerical simulation. The optimal design achieves hydraulic efficiencies of 91.8% and 93.19% in pumping and generating modes, respectively. In the interval of 0.8Q_BEP～1.2Q_BEP, the hydraulic efficiency exceeds 85% in both modes. For the optimized pump turbine model in pumping mode, the blade inlet edge near the upper crown and lower ring are offset towards the suction and pressure sides by θ₁=6.93°, respectively. Conversely, the blade outlet edge near the upper crown and lower ring are offset towards the pressure side and suction side by θ=8.62°. This inclination results in a reduction of the average blade abrasion rate by 9.26% and 9.71% in pumping and generating modes, respectively. Analysis under diverse operating conditions revealed correlations between flow capacity and sediment erosion: the average sediment volume fraction on blade surfaces, the mean sediment velocity near blade walls, and the average blade erosion rates exhibit polynomial relationships with flow rate, a fifth-degree function for volume fraction, a quadratic function for velocity, and a cubic function for erosion rate.