Dataset from the Upper Mississippi River Restoration Program (1993-2019) to reconstruct missing data by comparing interpolation techniques
Dates
Publication Date
2023-05-09
Start Date
1993-01-01
End Date
2020-01-01
Citation
Larson, D.M., Bungula, W., Lee, A., Stockdill, A., McKean, C., Miller, F., Davis, K., Erickson, R., and Hlavacek, E., 2023, Dataset from the Upper Mississippi River Restoration Program (1993-2019) to reconstruct missing data by comparing interpolation techniques: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZR7BWL.
Summary
The dataset accompanies the scientific article, "Reconstructing missing data by comparing interpolation techniques: applications for long-term water quality data." Missingness is typical in large datasets, but intercomparisons of interpolation methods can alleviate data gaps and common problems associated with missing data. We compared seven popular interpolation methods for predicting missing values in a long-term water quality data set from the upper Mississippi River, USA.
Summary
The dataset accompanies the scientific article, "Reconstructing missing data by comparing interpolation techniques: applications for long-term water quality data." Missingness is typical in large datasets, but intercomparisons of interpolation methods can alleviate data gaps and common problems associated with missing data. We compared seven popular interpolation methods for predicting missing values in a long-term water quality data set from the upper Mississippi River, USA.
Click on title to download individual files attached to this item.
metadata_interpolate_missingness.xml Original FGDC Metadata
View
23.04 KB
application/fgdc+xml
water_data_qfneg.csv
8.14 MB
text/csv
Related External Resources
Type: Related Primary Publication
Larson, D.M., Bungula, W., Lee, A., Stockdill, A., McKean, C., Miller, F."., Davis, K., Erickson, R.A. and Hlavacek, E. (2023), Reconstructing missing data by comparing interpolation techniques: Applications for long-term water quality data. Limnol Oceanogr Methods. https://doi.org/10.1002/lom3.10556
The data were collected under the Upper Mississippi River Restoration Program, with the intend of characterizing the status and trends of the Upper Mississippi River, USA.
