RF_Model_Finney_County


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Created: Feb 16, 2022 at 2:54 a.m.
Last updated: Feb 16, 2022 at 4:34 a.m.
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Abstract

This repository includes all the Python programming language scripts developed for long-term groundwater level (GWL) projections in Finney County in southwest Kansas, using the combination of the random forests (RF) and ordinary kriging techniques. The repository also includes all required data for running the scripts. GWL projections are done under various climate and management scenarios. The Scikit-learn library is used to construct the RF model and the ArcPy package is utilized for all geospatial and geostatistical analyses. All the scripts and data for GWL projections in different climate scenarios and under status quo management conditions are stored as a resource named "RF_GWL_projections_climate" and all the scripts and data pertinent to GWL forecasts in different well retirement plans and under the wet and dry climate conditions are stored as a resource named "RF_GWL_projections_management" (see Collection Contents). In each resource, all the files are uploaded as a single 7z file.

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Collection Contents

Add Title Type Owners Sharing Status My Permission Remove
RF_GWL_projections_climate CompositeResource Soheil Nozari Public & Shareable Open Access
RF_GWL_projections_management CompositeResource Soheil Nozari Public & Shareable Open Access

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
National Institute of Food and Agriculture, U.S. Department of Agriculture Sustaining agriculture through adaptive management to preserve the Ogallala aquifer under a changing climate 2016-68007-25066

How to Cite

Nozari, S., R. Bailey (2022). RF_Model_Finney_County, HydroShare, http://www.hydroshare.org/resource/eefb75d6189940d0a683291600a81cfb

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

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

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