无水文资料地区，水文模型的参数难以确定。基于此，提出一套无资料地区水文模拟的方法体系，首先利用开源再分析数据驱动水文模型，然后基于流域相似性理论进行模型参数移植，完成无资料地区水文模拟。以元江-红河多国跨界流域为例，将流域划分成123个子流域，基于根据高程、坡度、形状系数、森林覆盖率、降水与蒸散发等指标，利用主成分分析和流域相似度计算对123个子流域进行相似性分析；再基于水文资料和相似性结果，将7个有流量资料的子流域划分出4组相似流域；对有资料流域进行参数率定和验证，模拟结果良好，经过参数移植后，无资料流域的模拟结果均得到了提高。基于流域相似性的参数区域化和开源再分析数据的无资料地区水文模拟方法，可以为无资料地区的水文模拟与水资源管理带来更多可能。

In recent years, extreme weather such as drought and floods have occurred more frequently, and the study of watershed water cycle under changing environments is of great research significance. However, the construction of hydrological and meteorological stations in some regions of the world is not perfect enough, and the consistency of hydrological data in some regions is also disrupted due to changes in underlying surface and climate. These have led to lack of data in many study areas, posing a great obstacle to watershed hydrological simulation. As a multinational basin, the research data in the study area is difficult to fully obtain, which leads to similar difficulties in hydrological simulation of cross-border watersheds as in hydrological simulation of areas lacking data. A set of hydrological research methods suitable for regions lacking data in cross-border watersheds are aimed to be explored.The research method was mainly based on hydrological model and watershed similarity theory. Meteorological data, as an important input data for hydrological simulation, is often difficult to fully obtain in areas without data. Reanalysis data CMADS as a supplement to meteorological data in the hydrological simulation of the Red River basin was selected and its applicability in the Red River basin was studied. Based on the SWAT model and watershed elevation data, the Red River basin was divided into 123 sub watersheds. Then, a series of indicators such as elevation, slope, shape coefficient, forest coverage, precipitation and evapotranspiration were introduced to analyze the similarity of 123 sub watersheds by using of principal component analysis. According to existing little hydrological data and similarity results, four groups of similar watersheds were divided. Model parameters were well calibrated and validated in the basins with enough data, and then the validated parameters were used to drive the hydrological model in the data-shortage basins. The research results were as follows: In the Red River basin, the SWAT model was driven by both traditional meteorological station data and CMADS. Results showed that the CMADS-driven model performed well in the Son Tay station in both the calibration and validation periods, with the ERSR≤0.50 and ENS>0.75. Compared with the results of the CMADS-driven model, the model driven by traditional meteorological station data still satisfied simulation accuracy requirements, but the PBIAS was 12.1% in the calibration period and as high as 21% in the validation period, indicating a large simulation error. This indicated that CMADS could greatly enrich meteorological data in the Red River basin. Based on the results of basin similarity analysis and parameters transplantation, hydrological modeling in data-scarce sub-basins were carried out, which improved the simulation accuracy in most data-scarce sub-basins. Among them,ENS increased from 0.69 to 0.75 for sub-basin 77 after parameter transplantation from sub-basin 123,ENS increased from 0.75 to 0.85 for sub-basin 95 after parameter transplantation from sub-basin 123,ENS increased from 0.64 to 0.78 for sub-basin 96 after parameter transplantation from sub-basin 108, and ENS increased from 0.62 to 0.67 for sub-basin 102 after parameter transplantation from sub-basin 115. This indicated that parameter transplantation based on basin similarity could provide suitable parameters for hydrological models in data-scarce basins and provide more possibilities for hydrological simulation in data-scarce areas. The main conclusions were summarized as follows: Firstly, under the condition of lack of meteorological data, CMADS could be the alternative data for the SWAT model simulation. Compared with simulation results obtained by traditional meteorological station data, the results obtained by the CMADS-driven model could reach a very good standard in both the calibration and validation periods. Secondly, parameter transplantation based on basin similarity can provide suitable parameters for hydrological models in data-scarce areas, and basin similarity method improved the simulation results of most data-scarce sub-basins after parameter transplantation between similar basins. Finally, one research method was put forward successfully, which provide more possibilities for hydrological simulation in more data-scarce areas.