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）观测数据的可获取性持续提升，显著加深了学界对生态水文过程的认知。为充分挖掘该数据的应用潜力，研究人员开发了STEMMUS-MLR模型，可依托SIF数据直接估算生态水文通量与系统状态。本数据集包含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。