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Full-Text Articles in Oceanography and Atmospheric Sciences and Meteorology
Sediment Budgets For Small Salinized Agricultural Catchments In Southwest Australia And Implications For Phosphorus Transport, Robert J. Wasson, David Weaver
Sediment Budgets For Small Salinized Agricultural Catchments In Southwest Australia And Implications For Phosphorus Transport, Robert J. Wasson, David Weaver
Natural Resources Research Articles
Examples of sediment budgets are needed to document the range of budget types and their controls. Sediment budgets for three small agricultural catchments (7.6 to 15.6 km2) in southwestern Australia are dominated by channel and gully erosion, with sheet and rill erosion playing a subordinate role. Erosion was increased by clearing naturally swampy valley floors and hillslopes for agriculture and grazing, and episodic intense rainstorms. The proportion of sediment from channel and gully erosion in the sediment budget appears to be determined by the depth of alluvial fills. Dryland salinization caused by clearing native vegetation has connected hillslopes to channels …
A Continental-Scale Assessment Of Density, Size, Distribution And Historical Trends Of Farm Dams Using Deep Learning Convolutional Neural Networks, Martino E. Malerba, Nicholas J. Wright, Peter I. Macreadie
A Continental-Scale Assessment Of Density, Size, Distribution And Historical Trends Of Farm Dams Using Deep Learning Convolutional Neural Networks, Martino E. Malerba, Nicholas J. Wright, Peter I. Macreadie
Climate Science Research Articles
Farm dams are a ubiquitous limnological feature of agricultural landscapes worldwide. While their primary function is to capture and store water, they also have disproportionally large effects on biodiversity and biogeochemical cycling, with important relevance to several Sustainable Development Goals (SDGs). However, the abundance and distribution of farm dams is unknown in most parts of the world. Therefore, we used artificial intelligence and remote sensing data to address this critical global information gap. Specifically, we trained a deep learning convolutional neural network (CNN) on high-definition satellite images to detect farm dams and carry out the first continental-scale assessment on density, …