| Title: | A hybrid artificial neural network to estimate soil moisture using SWAT+ and SMAP data |
| Authors: | Breen, K.H., S.C. James, J.D. White, P.M. Allen and J.G. Arnold |
| Year: | 2020 |
| Journal: | Machine Learning and Knowledge Extraction |
| Volume (Issue): | 2 |
| Pages: | 283-306 |
| Article ID: | |
| DOI: | 10.3390/make2030016 |
| URL (non-DOI journals): | |
| Model: | SWAT+ |
| Broad Application Category: | hydrologic only |
| Primary Application Category: | model and/or data comparison |
| Secondary Application Category: | groundwater and/or soil water impacts |
| Watershed Description: | Middle-Tennessee Elk, Yazoo and Washita Rivers, and Escalante-Sevier Lake drainage area, all located in the U.S. |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Language: | English |
| Keywords: | Runoff, Modelling, Karst, SWAT, Watershed, GIS |