A Framework for Evaluating Groundwater Management Strategies Under Climate Change for New Mexico

Tuesday, April 13, 2010
Brian Hurd, PhD , Agricultural Economics and Agricultural Business, New Mexico State University, Las Cruces, NM
Prasenjit Ghosh , Department of Economics, Colorado State University, Fort Collins, CO
Climate change is expected to alter surface hydrology throughout the arid Western United States, in most cases compressing the period of peak snowmelt and runoff, and in some cases, for example, the Rio Grande, limiting total runoff.  As such, climate change is widely expected to further stress arid watersheds, particularly in regions where trends in population growth, economic development and environmental regulation are current challenges.  Strategies to adapt to such changes are evolving at various institutional levels including conjunctive management of surface and ground waters.  In the Rio Grande, for example, both natural and active recharge aquifers are viewed as part of the adaptive regime.  Conjunctive management is, however, often hampered by the lack of accurate information concerning the geo-hydrology of regional aquifers, for example, volume and extent, quality, and subsurface flow.  The value of information about the dimensions of aquifers and the underlying value of the resource itself can be very important to further evolution of adaptation and overall resource management.

The key objective of this paper is to 1) develop a framework for estimating the value of groundwater resources and improved information, and 2) provide some preliminary estimates of this value and how it responds to plausible scenarios of climate change.

Central to this framework and analysis is a hydro-economic model of the Rio Grande watershed from Colorado to West Texas.  This model integrates plausible changes in climate, hydrologic responses, and water demands within a framework that optimizes water use allocations for the greatest economic benefit.  The study uses three climate change scenarios across two future time periods selected to represent the range of effects indicted by the outputs across 18 GCMs using the SRES A1B emissions scenario.