Model Code Name:
Seasonality Trend Decomposition of Groundwater hydrographs by STL and time series analysis
Description:
The STL (Seasonal Trend by LOESS) method is used to decompose groundwater level time series. The different components are then analysed using time series clustering and correlation analysis
Purpose:
Statistical analysis of groundwater levels
Type:
Time series analysis
Mathematical Type:
Not Entered
URL:
Minimum Time Step:
1 minute
Maximum Time Step:
yearly
Version:
Publication date:
10-Jun-2015
Publications:
| Title | Published? | Publication URL | Digital Object Identifier | Authors | Year Published | Other Details |
|---|---|---|---|---|---|---|
| Use of seasonal trend decomposition to understand groundwater behaviour in the Permo-Triassic Sandstone aquifer, Eden Valley, UK | N | Lafare A.E.A., Peach D.W., Hughes A.G. | 0 | Hydrogeology Journal (in press) |
Computing Parameters:
| Parameter Name | Input/Output |
|---|---|
| Rainfall time series (P) | I |
| Groundwater level - time series | I |
| River flow time series | I |
| Remainder component | O |
| Long term trend of groundwater level | O |
| Seasonal fluctuation of groundwater level | O |
Keywords:
Computing requirements:
| Operating System | Code language | CPU | System Memory | Comments |
|---|---|---|---|---|
| Win7 | R Language | |||
| LINUX | R Language |
Responsible Parties:
| Name | Organisation | Country | |
|---|---|---|---|
| Antoine Lafare | British Geological Survey | UK | antoinel@bgs.ac.uk |