{"title":"Simple Approaches to Examine Economic Impacts of Water Reallocations from Agriculture","authors":"Ashley K. Bickel, Dari Duval, George B. Frisvold","doi":"10.1111/j.1936-704X.2019.03319.x","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Facing an anticipated shortage declaration on the Colorado River and reductions in surface water for agricultural use, rural stakeholder groups are concerned about how water cutbacks will affect their local economies. Local farm groups and county governments often lack the analytical tools to measure such impacts. While one can learn much from large-scale hydro-economic models, data, cost, and time limitations have been barriers to such model development. This article introduces three basic modeling approaches, using relatively low-cost and accessible data, to examine local economic impacts of water reallocations from agriculture. An empirical application estimates the effect of agricultural water reductions to Pinal County, Arizona, the county that would be most affected by a Colorado River Shortage Declaration. Water cutbacks to agriculture are modeled using two variants of a “rationing” model, which assumes that farmers will fallow their acres that generate the lowest gross returns (Rationing Model I) or the lowest net returns (Rationing Model II) per acre-foot of water. Rationing models have modest data requirements given that crop and region specific data are available. Building off these simpler rationing models, an input-output (I-O) model provides more detailed information about the impacts on different rural stakeholder groups as well as the impacts to non-agricultural sectors and the local tax base. Given imminent water cutbacks, access to low-cost data and information that are easy to interpret is essential for effective community dialogue.</p>\n </div>","PeriodicalId":45920,"journal":{"name":"Journal of Contemporary Water Research & Education","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2020-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/j.1936-704X.2019.03319.x","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Contemporary Water Research & Education","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/j.1936-704X.2019.03319.x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 1
Abstract
Facing an anticipated shortage declaration on the Colorado River and reductions in surface water for agricultural use, rural stakeholder groups are concerned about how water cutbacks will affect their local economies. Local farm groups and county governments often lack the analytical tools to measure such impacts. While one can learn much from large-scale hydro-economic models, data, cost, and time limitations have been barriers to such model development. This article introduces three basic modeling approaches, using relatively low-cost and accessible data, to examine local economic impacts of water reallocations from agriculture. An empirical application estimates the effect of agricultural water reductions to Pinal County, Arizona, the county that would be most affected by a Colorado River Shortage Declaration. Water cutbacks to agriculture are modeled using two variants of a “rationing” model, which assumes that farmers will fallow their acres that generate the lowest gross returns (Rationing Model I) or the lowest net returns (Rationing Model II) per acre-foot of water. Rationing models have modest data requirements given that crop and region specific data are available. Building off these simpler rationing models, an input-output (I-O) model provides more detailed information about the impacts on different rural stakeholder groups as well as the impacts to non-agricultural sectors and the local tax base. Given imminent water cutbacks, access to low-cost data and information that are easy to interpret is essential for effective community dialogue.