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|Created:||Feb 16, 2022 at 2:54 a.m.|
|Last updated:|| Oct 28, 2022 at 2:58 a.m.
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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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|RF_GWL_projections_climate||Resource||Soheil Nozari||Public & Shareable||Open Access|
|RF_GWL_projections_management||Resource||Soheil Nozari||Public & Shareable||Open Access|
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
This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/
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