Skip to main content

Md Fahim Hasan

thumbnail
Datasets are inputs and outputs of Aquaculture and Irrigation Water Use Model (AIWUM) 2.0. AIWUM 2.0 employs remote sensing data sets and machine learning utilizing Distributed Random Forests, an ensemble machine learning algorithm to estimate annual and monthly groundwater use for irrigation and aquaculture (2014–20) throughout this region at 1 km resolution, using annual pumping data from flowmeters in Mississippi and real-time flowmeters in Arkansas, Louisiana, Mississippi, Missouri, and Tennessee. Aquaculture and irrigation estimates contained in this data release are representative of groundwater withdrawal for six different categories: aquaculture, cotton, corn, rice, soybeans, and other crops. Model results...
ScienceBase brings together the best information it can find about USGS researchers and offices to show connections to publications, projects, and data. We are still working to improve this process and information is by no means complete. If you don't see everything you know is associated with you, a colleague, or your office, please be patient while we work to connect the dots. Feel free to contact sciencebase@usgs.gov.