This study aimed to quantify the ability of distributed and lumped hydrological models to use high-resolution precipitation and temperature data to improve streamflow simulation at watershed outlets. To that end, a 40-year, high-resolution, spatially distributed, meteorological dataset was extracted from a 15-km resolution regional climate model simulation (from the Canadian Regional Climate Model – CRCM v.4.2.4 driven by ERA40 reanalysis). This dataset was used to feed one distributed and four lumped hydrological models. The five models were calibrated on 192 watersheds located in the province of Quebec (Canada) using five different meteorological network densities of pseudo-stations. These densities ranged from one single station (located at the centre of gravity of the watershed) up to the maximum grid density of 1 station per 225 km² (15 km × 15 km which corresponds to the CRCM spatial resolution). No significant decrease in validation performance for both types of hydrological models was observed when using any of the tested station densities. Similar results were also obtained when investigating the subsets of 54 smaller (≤2,500 km²) and 84 medium-sized (2,500 < area <10,000 km²) watersheds. However, for the 54 larger watersheds (≥10,000 km²), the decrease in performance was statistically significant for the distributed model when using one single station. While all lumped models showed a noticeable drop in performance only when using a single station, the distributed model was the only model to show a gradual decrease in performance as the network density decreased. These results indicate that when dealing with large watersheds, distributed models could benefit up to some extent from a larger meteorological network density. These conclusions are likely to be relevant to Canadian watersheds with similar physiographic characteristics and hydroclimatic conditions as the ones included in the Quebec database that was studied.

这项研究旨在量化分布式和集总水文模型使用高分辨率降水和温度数据来改善流域出口处的水流模拟的能力。为此，从15公里分辨率的区域气候模型模拟中提取了40年的高分辨率，空间分布的气象数据集（来自ERA40再分析驱动的加拿大区域气候模型– CRCM v.4.2.4）。该数据集用于提供一个分布式和四个集总水文模型。使用五个不同的伪站点气象网络密度，在位于魁北克省（加拿大）的192个分水岭上对这五个模型进行了校准。这些密度的范围从一个单站（位于流域的重心）到每225公里最大1个站的网格密度²（15 km×15 km，对应于CRCM空间分辨率）。使用任何测试的站台密度时，两种水文模型的验证性能均未见明显下降。当调查54个较小的（≤2,500km ²）和84个中型（2,500 <面积<10,000 km ²）流域的子集时，也获得了相似的结果。但是，对于54个较大的流域（≥10,000km ²），使用单个工作站时，分布式模型的性能下降在统计上是显着的。虽然所有集总模型仅在使用单个站时才会显示出明显的性能下降，但分布式模型是唯一显示出随着网络密度降低而性能逐渐下降的模型。这些结果表明，在处理大流域时，分布式模型可以在更大程度上受益于更大的气象网络密度。这些结论可能与生理学特征和水文气候条件与研究的魁北克数据库中相似的加拿大流域有关。