Abstract: To address the strong weather dependence of the new energy industry and limitations of traditional insurance, it is imperative to accelerate the application of weather index insurance in new energy risk management. Based on a case study in the Beijiang river basin, this paper utilizes meteorological data from 1984 to 2023 and runoff data from 2003 to 2017 combined with hydrological and power generation potential models to analyze the spatiotemporal distribution characteristics of photovoltaic and hydrological climate resources on a monthly scale. Considering core processes such as trigger value setting, pure premium rate determination, compensation scheme formulation and verification, a basin-level photovoltaic and hydropower index insurance product is designed and applied. Furthermore, Kendall rank correlation analysis and standard deviation reduction percentage method are employed to systematically evaluate its hedging effects under different temporal-spatial conditions and different proportioning scenarios. The results show that the photovoltaic and hydropower index insurance, with monthly solar radiation and runoff as indices, can provide multi-level risk protection schemes by setting different monthly compensation trigger thresholds according to exceedance probabilities. Under different claim initiation standards, the annual average values of monthly pure premium rates for photovoltaic and hydropower index insurance are 7.1%—11.8% and 7.1%—39.9%, and the annual average values of monthly cumulative compensation ratios are 6.1%—13.3% and 6.9%—29.3% respectively. The spatial hedging performance of the photovoltaic and hydropower index insurance is superior to that of single-factor power generation index insurance. In the same spatial range, the complementarity of photovoltaic and hydropower generation potential is generally strong from June to October, showing a distribution pattern of "stronger in the southeast and weaker in the northwest". The risk diversification effect of photovoltaic and hydropower index insurance in different spatial areas is better than that in the same spatial area, and the diversification effect of "hydropower hedging solar power" is more optimal. In the scenario with the strongest hedging performance, when the proportion of photovoltaic and hydropower index insurance products is 7:3, the volatility of the insurance loss ratio reaches the smallest, which is respectively 19.2% and 51.9% lower than that of single photovoltaic and hydropower index insurance. Therefore, by optimizing the proportion of different insurance products, the volatility of the loss ratio of "hedging-type" insurance products can be effectively reduced, and their overall operational stability can be improved.