Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...
This resource contains some files/folders that have non-preferred characters in their name. Show non-conforming files/folders.
This resource contains content types with files that need to be updated to match with metadata changes. Show content type files that need updating.
| Authors: |
|
|
|---|---|---|
| Owners: |
|
This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource. |
| Type: | Resource | |
| Storage: | The size of this resource is 1.7 GB | |
| Created: | Jun 03, 2021 at 7:36 p.m. | |
| Last updated: | Mar 07, 2022 at 11:52 p.m. (Metadata update) | |
| Published date: | Mar 07, 2022 at 11:46 p.m. | |
| DOI: | 10.4211/hs.a6ea89ae20354e39b3c9f1228997e27a | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
|---|---|
| Views: | 1557 |
| Downloads: | 88 |
| +1 Votes: | Be the first one to this. |
| Comments: | No comments (yet) |
Abstract
This resource contains the supporting data and code files for the analyses presented in "Toward automating post processing of aquatic sensor data," an article published in the journal Environmental Modelling and Software. This paper describes pyhydroqc, a Python package developed to identify and correct anomalous values in time series data collected by in situ aquatic sensors. For more information on pyhydroqc, see the code repository (https://github.com/AmberSJones/pyhydroqc) and the documentation (https://ambersjones.github.io/pyhydroqc/) The package may be installed from the Python Package Index (more info: https://packaging.python.org/tutorials/installing-packages/)
Included in this resource are input data, Python scripts to run the package on the input data (anomaly detection and correction), results from running the algorithm, and Python scripts for generating the figures in the manuscript. The organization and structure of the files are described in detail in the readme file. The input data were collected as part of the Logan River Observatory (LRO). The data in this resource represent a subset of data available for the LRO and were compiled by querying the LRO’s operational database. All available data for the LRO can be sourced at http://lrodata.usu.edu/tsa/ or on HydroShare: https://www.hydroshare.org/search/?q=logan%20river%20observatory.
There are two sets of scripts in this resource: 1.) Scripts that reproduce plots for the paper using saved results, and 2.) Code used to generate the complete results for the series in the case study. While all figures can be reproduced, there are challenges to running the code for the complete results (it is computationally intensive, different results will be generated due to the stochastic nature of the models, and the code was developed with an early version of the package), which is why the saved results are included in this resource. For a simple example of running pyhydroqc functions for anomaly detection and correction on a subset of data, see this resource: https://www.hydroshare.org/resource/92f393cbd06b47c398bdd2bbb86887ac/.
Subject Keywords
Coverage
Spatial
Temporal
| Start Date: | |
|---|---|
| End Date: |
Content
Related Resources
| The content of this resource references | Jones, A. S. (2021). pyhydroqc Sensor Data QC: Single Site Example, HydroShare, https://doi.org/10.4211/hs.92f393cbd06b47c398bdd2bbb86887ac |
| This resource is described by | Jones, A.S., Jones, T.L., Horsburgh, J.S. (2022). Toward automated post processing of aquatic sensor data, Environmental Modelling and Software, https://doi.org/10.1016/j.envsoft.2022.105364 |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| National Science Foundation | Collaborative Research: Elements: Advancing Data Science and Analytics for Water (DSAW) | 1931297 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
There are currently no comments
New Comment