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Full-Text Articles in Engineering
Learning From Machines: Insights In Forest Transpiration Using Machine Learning Methods, Morgan Tholl
Learning From Machines: Insights In Forest Transpiration Using Machine Learning Methods, Morgan Tholl
Dissertations and Theses
Machine learning has been used as a tool to model transpiration for individual sites, but few models are capable of generalizing to new locations without calibration to site data. Using the global SAPFLUXNET database, 95 tree sap flow data sites were grouped using three clustering strategies: by biome, by tree functional type, and through use of a k-means unsupervised clustering algorithm. Two supervised machine learning algorithms, a random forest algorithm and a neural network algorithm, were used to build machine learning models that predicted transpiration for each cluster. The performance and feature importance in each model were analyzed and compared …
Remote Sensing Of Water Use Efficiency And Terrestrial Drought Recovery Across The Contiguous United States, Behzad Ahmadi, Ali Ahmadalipour, Glenn Tootle
Remote Sensing Of Water Use Efficiency And Terrestrial Drought Recovery Across The Contiguous United States, Behzad Ahmadi, Ali Ahmadalipour, Glenn Tootle
Civil and Environmental Engineering Faculty Publications and Presentations
Ecosystem water-use efficiency (WUE) is defined as the ratio of carbon gain (i.e., gross primary productivity; GPP) to water consumption (i.e., evapotranspiration; ET). WUE is markedly influential on carbon and water cycles, both of which are fundamental for ecosystem state, climate and the environment. Drought can affect WUE, subsequently disturbing the composition and functionality of terrestrial ecosystems. In this study, the impacts of drought on WUE and its components (i.e., GPP and ET) are assessed across the Contiguous US (CONUS) at fine spatial and temporal resolutions. Soil moisture simulations from land surface modeling are utilized to detect and characterize agricultural …