ABSTRACT

The focus of this is to reveal the value of making national data archives available for scientific research by showing the specific example from the field of regional runoff reconstruction. Thus, for northwest Russia, we developed two gridded datasets of monthly runoff reconstruction: for the first dataset (BASE), we used only the freely available data from the Global Runoff Data Centre (GRDC), while, for the second dataset (SOTA), we complemented the GRDC data with digitized runoff records from Russian national observational runoff archives (R5). The accuracy of developed datasets in terms of monthly runoff prediction was assessed using the Nash-Sutcliffe efficiency (NSE) for a wide range of river basins. The results show that accounting for R5 data for runoff reconstruction underpins a substantial gain in NSE of SOTA over the BASE dataset. Moreover, both datasets, on average, outperform 10 state-of-the-art global hydrological models and one European-scale regional hydrological model.

摘要

其重点是通过展示区域径流重建领域的具体实例来揭示使国家数据档案可用于科学研究的价值。因此，对于俄罗斯西北部，我们开发了两个月径流重建的网格数据集：对于第一个数据集 (BASE)，我们仅使用来自全球径流数据中心 (GRDC) 的免费数据，而对于第二个数据集 (SOTA) , 我们用俄罗斯国家径流观测档案 (R5) 的数字化径流记录补充了 GRDC 数据。使用 Nash-Sutcliffe 效率 (NSE) 对大范围流域评估已开发数据集在每月径流预测方面的准确性。结果表明，考虑到用于径流重建的 R5 数据支持了 SOTA 的 NSE 相对于 BASE 数据集的实质性收益。