08 Groundwater Modeling
08-11 Data-Driven & Machine Learning Approaches
Machine Learning-based prediction, data assimilation, hybrid models.
Contents
| Index | Description |
|---|---|
| 08-11-001 | REST request to Retrieve real-time Hydrogeological Data, an example |
08-11-001REST request to Retrieve real-time Hydrogeological Data, an example
| Type: Jupyter Notebook | Time: 15–30 minutes |
Figure 1: Data retrieved from the Sentilo sensor via API for a selected aquifer in Catalonia. (Screenshot)
This Jupyter Notebook serves as an example of how to retrieve hydrogeological data in real-time using REST requests. It is a useful tool for accessing open data from the aquifer of interest, such as piezometric levels, temperature, and electrical conductivity.
For this purpose, we illustrate how to retrieve hydrogeological data for the aquifers of Catalonia, sourced from the data generated by the Catalan Water Agency and stored in the open sensor platform Sentilo.
| Detail | Value |
|---|---|
| URL | github.com · open repository |
| Author(s) | Oriol Bertran (UPC) |
| Keywords | API, request, hydrogeological data |
| Fit For | self learning, online teaching, classroom teaching |
| Prerequisites | None specified. |
| References | https://aca.gencat.cat/ca/laigua/consulta-de-dades/dades-obertes/dades-obertes-temps-real/index.html#googtrans(ca%7Cen https://aca.gencat.cat/web/.content/20_Aigua/08_consulta_de_dades/01_dades_obertes/02_dades_obertes_temps_real/us_serveis_dades_API_REST.pdf https://www.sentilo.io/ https://aca.gencat.cat/ca/inici/index.html#googtrans(ca%7Cen |