Predictive_model_Assam


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Resource type: Composite Resource
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Created: Jan 29, 2022 at 1:57 a.m.
Last updated: Feb 24, 2022 at 4:31 p.m.
DOI: 10.4211/hs.d4f4b7601c694667bdf62a7826cad1a6
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Sharing Status: Published
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Abstract

The resources contain grid averaged arsenic concentration (mean concentrations) and predictor variables in Jorhat and Golaghat districts of Assam. GPS location has included error terms for privacy. Basic workflow random forest model in python environment is also provided. Final model was determined through random 10-fold cross-validation. Final model was used in the prediction of arsenic probability in unknown locations. We have also checked spatial cross-validation. The results were found to be consistent and confirmed the overall distribution of high/moderate/low-risk zones for arsenic in groundwater.

Some of the original point data can be downloaded from: https://www.hydroshare.org/resource/bbe23dfacab647568a18dc338114d6d7/
reference: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2017WR022485

Subject Keywords

Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
Jorhat
Longitude
94.0336°
Latitude
26.6267°

Content

How to Cite

Nath, B. (2022). Predictive_model_Assam, HydroShare, https://doi.org/10.4211/hs.d4f4b7601c694667bdf62a7826cad1a6

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
CC-BY

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