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.
Kansas Hydrogeologic and Economic Data and Code used in "What Lies Beneath: Aquifer Heterogeneity and the Economics of Groundwater Management"
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 753.1 KB | |
Created: | Feb 03, 2019 at 12:46 p.m. | |
Last updated: | Feb 03, 2019 at 4:43 p.m. | |
Citation: | See how to cite this resource | |
Content types: | Single File Content |
Sharing Status: | Public |
---|---|
Views: | 2220 |
Downloads: | 46 |
+1 Votes: | Be the first one to this. |
Comments: | 1 comment |
Abstract
This resource contains data and code for the analysis and tables in: Edwards, E.C. What Lies Beneath? Aquifer Heterogeneity and the Economics of Groundwater Management. 2016. Journal of the Association of Environmental and Resource Economists, vol. 3 no. 2, pp. 453-91.
Subject Keywords
Coverage
Spatial
Temporal
Start Date: | |
---|---|
End Date: |
Content
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
Eric Edwards 5 years, 10 months ago
This data contains a stata .dta file and three state .do files. The .do files create the tables and figures from Edwards, E.C. What Lies Beneath? Aquifer Heterogeneity and the Economics of Groundwater Management. 2016. Journal of the Association of Environmental and Resource Economists, vol. 3 no. 2, pp. 453-91. The .dta file contains data linking economic data from the agricultural census to geophysical data
ReplyFarm Data
The US Agricultural Census provides the county-level economic data for the empirical work as digitized by Gutmann (2005) and Haines (2010). The agricultural census surveys farmers at approximately five year intervals. Farm value per acre is a measure of market value derived from asking farmers to report the estimated sale value of their farm and buildings. The measures of average farm size and percentage of total farm acres in corn come from the same agricultural census surveys. The dataset is constructed using observations for a 50-year window around the enactment of the GMD Act. County-level data is the smallest spatial aggregation that is currently available for the entirety of this time period. There were 11 agricultural census conducted from 1947-1997, and all variables are observed in each census except farm size, which is not available in 1954. The census is typically conducted every five years, with four years from the first observation, 1950, to 1954; 1974 to 1978; and 1978 to 1982.
Aquifer Data
Physical aquifer data comes from the Kansas Geological Survey (KGS) using data from the United States Geological Survey (USGS). KGS has developed the High Plains Atlas to visually represent this data and uses Public Land Survey System sections (one-square mile) to store the data. The variables of interest to this study are hydraulic conductivity (Cederstrand and Becker 1998); and recharge (Hansen 1991 modified by Kansas Department of Agriculture, Division of Water Resources). Hydrologic data is aggregated to county level by taking the average of each variable for all of the sections for which it is observed in a county.
Other Data
Additional data are compiled to control for land productivity. Soil capability is derived from the Gridded Soil Survey Geographic for Kansas (USDA/NRCS 2012). These data provide a score from 0 to 1 of agricultural suitability, with 1 being the best soil for agriculture. These data are provided as a 10m raster or map with cells of soil types and their suitability scores and averaged for each county by area. Table 2 provides a listing of the variables used in the regressions and the source of the data.
New Comment