Scientific and operational value of alternative datasets in hydrological science

应用水文学在很大程度上依赖于水文气象信息，特别是对降水结束温度的测量。然而，相关水文气象变量的时间序列存在着时间视界短、数据缺失、误差大、偏差大等问题。这限制了充分反映流域尺度上水文过程的空间和时间变异性的能力，有时甚至是严重的。已经提出了新的数据集，以缓解缺乏直接观测和在时间和空间上覆盖不够理想的问题。现有的数据集包括传统的基于站点的数据和三个备选数据集：网格数据集、观测重新分析和动态生成的数据。参与该项目的科学家和工业伙伴提议：调查替代数据集在水文科学中的科学和业务价值。更确切地说，该项目旨在实现以下具体目标：

Applied hydrological science strongly relies on hydrometeorological information, and especially on measurements of precipitation end temperature. However, time series of relevant hydrometeorological variables are plagued with problems such as short temporal horizons, missing data, errors, and various biases. This limits, sometimes severely, the ability to adequately represent the spatial and temporal variability of the hydrological processes at the basin scale. New datasets have been proposed to palliate the lack of direct observations and the less than optimal coverage in time and space. Available datasets consists of the traditional station-based data and of three alternative datasets: gridded datasets, reanalyses of observations and dynamically generated data. The scientists and industrial partners involved in this project propose to: Investigate the scientific and operational value of alternative datasets in hydrological science. More precisely, this project intends to address the following specific objectives: