Data underlying the research on Advancing the Understanding of Eco-Hydrological Processes with the STEMMUS-MLR Model

The increasing availability of solar-induced chlorophyll fluorescence (SIF) observations has significantly enhanced our understanding of eco-hydrological processes. To leverage this potential, the STEMMUS-MLR model was developed to directly estimate eco-hydrological fluxes and states using SIF data. This dataset includes the source code of the STEMMUS-MLR model, along with in-situ measurements used for model forcing and validation.日光诱导叶绿素荧光（solar-induced chlorophyll fluorescence, SIF）观测资料的可获取性日益提升，显著深化了学界对生态水文过程的认知。为充分挖掘该类数据的应用潜力，研究者开发了STEMMUS-MLR模型，可直接通过SIF数据估算生态水文通量与状态变量。本数据集涵盖STEMMUS-MLR模型的源代码，以及用于模型驱动与验证的原位实测数据。

搜集汇总

背景与挑战

背景概述

该数据集包含用于生态水文过程研究的STEMMUS-MLR模型源代码及相关现场测量数据，支持通过太阳诱导叶绿素荧光（SIF）数据直接估算生态水文通量和状态。数据集目前处于禁运状态（截至2027年6月1日），格式包括Excel和MATLAB文件，适用于生态水文建模和验证研究。