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Forecasting Irrigation Water Demand: A Case Study on the Flint River Basin in Georgia AgEcon
Banerjee, Swagata (Ban); Tareen, Irfan Y.; Gunter, Lewell F.; Bramblett, Jimmy; Wetzstein, Michael E..
Southeast drought conditions have accentuated the demand for irrigation in the face of restricted water supply. For allocating this supply, Georgia held an auction for withdrawing irrigated acreage. This auction withdrew 33,000 acres from irrigation, resulting in a physical estimate of a 399 acre-feet daily increase in water flow. The actual reduction is driven by crop distributional changes on the basis of economic substitution and expansion effects. In contrast to the physical estimates, an econometric model that considers these effects is developed. The differences between the physical and econometric models result in an increase in the estimate of water savings of around 19% to 24%.
Tipo: Journal Article Palavras-chave: Acreage response; Crop distribution; Irrigated acreage; Irrigation; Slippage; Water demand; Water saving; Q12; Q24.
Ano: 2007 URL: http://purl.umn.edu/37053
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ASSESSING THE SPATIAL DISTRIBUTION OF CROP PRODUCTION USING A GENERALIZED CROSS-ENTROPY APPROACH AgEcon
You, Liangzhi; Wood, Stanley.
While agricultural production statistics are reported on a geopolitical – often national - basis we often need to know the status of production or productivity within specific sub-regions, watersheds, or agro-ecological zones. Such re-aggregations are typically made using expert judgments or simple area-weighting rules. We describe a new, entropy-based approach to making spatially disaggregated assessments of the distribution of crop production. Using this approach tabular crop production statistics are blended judiciously with an array of other secondary data to assess the production of specific crops within individual ‘pixels’ – typically 25 to 100 square kilometers in size. The information utilized includes crop production statistics, farming system...
Tipo: Working or Discussion Paper Palavras-chave: Entropy; Cross entropy; Remote sensing; Spatial allocation; Production; Crop distribution; Crop Production/Industries.
Ano: 2004 URL: http://purl.umn.edu/60324
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