The MaRIUS‐G2G datasets were produced for the MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity) project, using the Grid‐to‐Grid (G2G) national‐scale hydrological model for Great Britain. There are six separate datasets, with each of three combinations of meteorological driving data (two observation‐based and one from climate model ensembles) used to produce two types of outputs (daily time‐series of natural river flow for 260 sites, and monthly 1 × 1 km grids of natural flow and soil moisture in the unsaturated zone). The driving data required by G2G are rainfall and potential evaporation (PE). Two of the datasets from observation‐based driving data use rainfall from CEH‐GEAR (CEH‐Gridded Estimates of Areal Rainfall) with PE from MORECS (Met Office Rainfall and Evaporation Calculation System), and cover the period 1960–2015, while the other two use CEH‐GEAR rainfall with PE derived from 5 km temperature data using the Oudin method, and cover 1891–2015. The two datasets based on driving data (rainfall and PE) from the climate model ensembles cover three periods: Historical Baseline (1900–2006), Near‐Future (2020–2049), and Far‐Future (2070–2099). Data for a 30‐year Baseline period (1975–2004), against which the Near‐Future and Far‐Future periods should be compared, are also available directly. There are 100 members in each ensemble, and the future periods use the RCP8.5 emissions scenario. This paper provides details of the G2G model and the different sets of meteorological driving data, as well as the availability and formatting of the output datasets. It also describes some recent and potential applications of the datasets, which have already been used to support historical and future analyses of low flow and drought characteristics across Britain, and provides some guidance on how the climate model‐driven datasets should (and should not) be used.

中文翻译：

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MaRIUS‐G2G数据集：使用观测和气候模型驱动数据对英国的水流和土壤湿度进行网格到网格模型估计

MaRIUS-G2G数据集是使用英国的网格到网格（G2G）国家级水文模型为MaRIUS（管理干旱和水资源短缺的风险，影响和不确定性）项目生成的。共有六个独立的数据集，其中三种气象驱动数据组合（两种基于观测数据，一种来自气候模型集合）用于产生两种类型的输出（260个站点的每日自然河流流量时间序列，每月1个） ×1 km的非饱和区自然流量和土壤湿度网格）。G2G所需的驱动数据是降雨和潜在蒸发量（PE）。来自基于观测的驾驶数据的两个数据集使用来自CEH-GEAR（CEH的地区降雨网格估计）的降雨和来自MORECS（气象局的降雨和蒸发计算系统）的PE，覆盖的时间范围是1960-2015年，而其他两个使用的是使用Oudin方法从5 km温度数据得出的PE的CEH-GEAR降雨，覆盖的时间范围是1891-2015。基于来自气候模型集合的驱动数据（降雨和PE）的两个数据集涵盖三个时期：历史基线（1900-2006年），近期（2020-2049年）和未来（2070-2099年）。也可以直接获得30年基线期（1975-2004）的数据，应将其与近未来和远未来时期进行比较。每个合集中有100个成员，将来的期间将使用RCP8.5排放方案。本文提供了G2G模型和不同的气象驱动数据集的详细信息，以及输出数据集的可用性和格式。它还描述了数据集的一些近期和潜在应用，