Exploiting Earth Observation Data to Impute Groundwater Level Measurements with an Extreme Learning Machine
Groundwater resources are expensive to develop and use; they are difficult to monitor and data collected from monitoring wells are often sporadic, often only available at irregular, infrequent, or brief intervals. Groundwater managers require an accurate understanding of historic groundwater storage...
Main Authors: | Steven Evans, Gustavious P. Williams, Norman L. Jones, Daniel P. Ames, E. James Nelson |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-06-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/12/12/2044 |
Similar Items
-
Groundwater Level Data Imputation Using Machine Learning and Remote Earth Observations Using Inductive Bias
by: Saul G. Ramirez, et al.
Published: (2022-11-01) -
Groundwater Storage Variations across Climate Zones from Southern Poland to Arctic Sweden: Comparing GRACE-GLDAS Models with Well Data
by: Zofia Rzepecka, et al.
Published: (2024-06-01) -
Exploiting Earth Observations to Enable Groundwater Modeling in the Data-Sparse Region of Goulbi Maradi, Niger
by: Sergio A. Barbosa, et al.
Published: (2023-11-01) -
Groundwater Depletion Signals in the Beqaa Plain, Lebanon: Evidence from GRACE and Sentinel-1 Data
by: Elias C. Massoud, et al.
Published: (2021-03-01) -
Assessing drought conditions in Northeast Brazil: A comparative analysis of soil moisture, groundwater, and total water storage
by: Mayara Silva de Oliveira, et al.
Published: (2024-12-01)