FrenchPiezo: the French mainland groundwater level multivariate time series

<p><strong>THIS REPOSITORY IS INCOMPLETE, THE CORRECT DATASET IS AT:&nbsp;<a href="https://zenodo.org/record/7193812#.Y3-ThhTMLic">FrenchPiezo| 7193812#.Y3-ThhTMLic</a>&nbsp;</strong></p> <p>This dataset is a multivariate time series of groundwater level (a.k.a piezometric level) measured by sensors in many cities in the French mainland from January 2015 to January 2021 (2,221 days). The dataset contains 1026 multivariate time series composed of three dimensions sampled daily:</p> <ul> <li><strong>p: </strong>groundwater level</li> <li><strong>tp:&nbsp;</strong>precipitation</li> <li><strong>e:&nbsp;</strong>evapotranspiration</li> </ul> <p>Each time series is identified by a&nbsp;<strong>bss code&nbsp;</strong>&nbsp;which is the identifier of the piezometer using to collect the associated groundwater level.</p> <p>The groundwater level is collected from <a href="https://hubeau.eaufrance.fr/">Hub&#39;Eau</a>, the french service for accessing water data. The precipitation and evapotranspiration are collected from the Copernicus ERA5 climate database.&nbsp;</p> <p>The file <em>dataset_2015_2021.csv</em>&nbsp;contains the raw dataset with missing values</p> <p>The file <em>dataset_nomissing_linear.csv</em>&nbsp;is similar to the previous one, but the missing data&nbsp;have been imputed using linear interpolation.</p> <p>&nbsp;</p> <p>More details about this dataset with source code for collecting it can be found in our paper:&nbsp;</p> <p>```</p> <p>Mbouopda, Michael Franklin, et al. &quot;Experimental study of time series forecasting methods for groundwater level prediction.&quot;&nbsp;<em>ECML/PKDD Workshop on Advanced Analytics and Learning on Temporal Data</em>. 2022.</p> <p>```</p>