Datasets

type: dataset date: 2023

Total is 116 Results
Lunar Hydration at the South Pole observed by Deep Impact

10.4231/0643-AM58

Kris Laferriere, 0000-0002-9160-6184

08/11/2023

Files used for calibration and analysis of hydration feature as observed by Deep Impact during the 2009 lunar flyby of the south pole

EAPS hydration hydroxyl Moon Water

Dataset/Codes for the project: A Model for the Tropical Cyclone Wind Field Response to Idealized Landfall

10.4231/3AKW-VX52

Daniel Robert Chavas, 0000-0001-9172-8328, Jie Chen, 0000-0002-8742-1048

04/03/2023

This dataset provides the CM1 scripts to reproduce the idealized TC landfalls, and simulation outputs of the landfall experiments examined in the paper.

EAPS Hurricanes TC hazards TC landfalls TC structure theoretical TC wind field model tropical cyclones

Linking biogeochemical and hydrodynamic processes to model methane fluxes in shallow, tropical floodplain lakes.

10.4231/4WN4-S032

Mingyang Guo, 0000-0002-3087-453X, Qianlai Zhuang, 0000-0002-4536-9851

01/26/2023

This dataset contains the revised Arctic Lake Biogeochemistry Model (ALBM) code for the study of Linking biogeochemical and hydrodynamic processes to model methane fluxes in shallow, tropical floodplain lakes.

ALBM EAPS lake model Methane Emission

Data for Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins

10.4231/0PG5-KC30

Pin-ching Li, Sayan Dey, 0000-0002-5327-8431, Venkatesh Mohan Merwade, 0000-0001-5518-2890

01/23/2023

This resource contains the data used in the study "Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins" published in Water Resources Research (doi: 10.1029/2023WR034464)

Artificial Neural Network (ANN) covariate shift Hydrology Machine Learning prediction in ungauged basin Random Forest streamflow prediction

Codes for Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins

10.4231/B783-2C47

Pin-ching Li, Sayan Dey, 0000-0002-5327-8431, Venkatesh Mohan Merwade, 0000-0001-5518-2890

01/23/2023

This resource contains codes used in the study "Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins" published in Water Resources Research (doi: 10.1029/2023WR034464)

Artificial Neural Network (ANN) Machine Learning Random Forest streamflow prediction

A process-based biogeochemistry model and analysis for current and future global lake methane emissions

10.4231/67YG-V518

Mingyang Guo, 0000-0002-3087-453X, Qianlai Zhuang, 0000-0002-4536-9851

01/25/2023

This data contains the source code of a lake biogeochemistry model - Arctic Lake Biogeochemistry Model (ALBM).

ALBM Biogeochemical model EAPS lake model Methane Emission

Aerial imagery of the Purdue Agronomy Center for Research and Education (ACRE) – 1963

10.4231/ZBHC-3K73

Darrell G Schulze, 0000-0001-9278-2457, Shams Rahman R Rahmani, 0000-0001-6246-2786

01/26/2023

Aerial imagery from 1963 of the Purdue Agronomy Center for Research and Education (ACRE), West Lafayette, IN, USA.

ACRE aerial photography Agronomy Remote sensing imagery

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