000205882 001__ 205882
000205882 005__ 20180123001039.0
000205882 037__ $$a330-2016-13969
000205882 041__ $$aen_US
000205882 245__ $$aAquifer Depletion in the face of Climate Change and Technical Progress.
000205882 260__ $$c2015-05-27
000205882 269__ $$a2015-05-27
000205882 270__ $$mnicolasq@ksu.edu$$pQuintana-Ashwell,   Nicolas E.
000205882 270__ $$mjpeters@ksu.edu$$pPeterson,   Jeffrey M.
000205882 300__ $$a32
000205882 336__ $$aConference Paper/ Presentation
000205882 490__ $$aPaper #7836
000205882 520__ $$aA dynamic optimization framework is applied to the problem where groundwater stock and the state of technology and the climate are the state variables and groundwater pumping is the control variable and the objective is to maximize the net present value of the stream of rents from irrigation over the life of the aquifer.  Dynamical systems govern the evolution of the aquifer, the climate, and the rate of technical progress. These dynamical systems may be dependent upon periodic groundwater allocations, as in the case of the aquifer, or independent of the periodic allocations as in the case of climate and technical change. Alternative plans are considered where the planner ignores one or more of the state variables when prescribing an extraction path. The ``information effect'' in these plans is assessed by comparing extraction, depletion, and rents from irrigation paths. A well accepted formulation of hydrologic dynamics for the aquifer is employed and simple dynamic trends for climate and technology are developed.   A simplified example of the model incorporating only deterministic aquifer and technical change dynamics is presented as a linear-quadratic optimal control problem. Numerical results from Sheridan County, KS, suggest that prescribing a pumping schedule ignoring the dynamics of climate change is most costly. Furthermore, once on the optimal path, relatively large savings in groundwater may be achieved with relatively small portions of profits foregone.
000205882 542__ $$fLicense granted by Nicolas Quintana Ashwell (nicolasq@k-state.edu) on 2015-05-28T04:35:42Z (GMT):

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000205882 650__ $$aEnvironmental Economics and Policy
000205882 650__ $$aProduction Economics
000205882 650__ $$aResource /Energy Economics and Policy
000205882 6531_ $$aAquifer
000205882 6531_ $$aOgallala
000205882 6531_ $$aOptimal Control
000205882 6531_ $$aDynamic Optimization
000205882 6531_ $$aIrrigation
000205882 700__ $$aQuintana-Ashwell, Nicolas E.
000205882 700__ $$aPeterson, Jeffrey M.
000205882 773__ $$d2015
000205882 8564_ $$s2286461$$uhttp://ageconsearch.umn.edu/record/205882/files/QuintanaPetersonAAEApaperTCandCConCRPsubmitted.pdf
000205882 887__ $$ahttp://purl.umn.edu/205882
000205882 909CO $$ooai:ageconsearch.umn.edu:205882$$pGLOBAL_SET
000205882 912__ $$nSubmitted by Nicolas Quintana Ashwell (nicolasq@k-state.edu) on 2015-05-28T04:41:38Z
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  Previous issue date: 2015-05-27
000205882 982__ $$gAgricultural and Applied Economics Association>2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California
000205882 980__ $$a330