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Machine learning theory Water/energy interactions Probabilistic streamflow forecasting Hydrologic similarity s u m m a r y Streamflow forecasting plays a critical role in nearly all aspects of water resources planning and management. In this work, Gaussian Process Regression (GPR), an effective kernel-based machine learning algorithm , is applied to(More)
a r t i c l e i n f o Keywords: DayCent model ParameterESTimation (PEST) GHG scenario analysis altered precipitation climate warming Greenhouse gas (GHG) emissions play an important role in regulating the Earth surface temperature. GHG emissions from soils are sensitive to climate change and land management practices. According to general circulation model(More)
To test whether there are general patterns in biomass partitioning in relation to environmental variation when stand biomass is considered, we investigated biomass allocation in leaves, stems, and roots in China's forests using both the national forest inventory data (2004-2008) and our field measurements (2011-2012). Distribution patterns of leaf, stem,(More)
The lack of high spatial resolution precipitation data, which are crucial for the modeling and managing of hydrological systems, has triggered many attempts at spatial downscaling. The essence of downscaling lies in extracting extra information from a dataset through some scale-invariant characteristics related to the process of interest. While most studies(More)
Dissolved organic carbon (DOC) concentrations have increased in many sites in Europe and North America in recent decades. High DOC concentrations can damage the structure and functions of aquatic ecosystems by influencing water chemistry. This study investigated the spatial and seasonal variation of DOC concentrations in Irish streams across 55 sites at(More)
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