Optimal Irrigation Strategies and Adaptive Decision-Making Under
Groundwater Pumping Restrictions and Precipitation Uncertainties
Abstract
Innovative groundwater management strategies are essential to preserve
aquifers for crop irrigation. In western Kansas, USA, irrigators
self-organized to extend the aquifer’s lifespan by self-imposing
groundwater pumping limits enforced over a five-year period. While the
five-year groundwater allocation period granted irrigators additional
flexibility, it adds a new temporal dimension to their decision-making
beyond the typical annual/sub-annual cropping and irrigation decisions.
Pumping restrictions, along with uncertain precipitation, complicate
multi-year farm planning. We formulated a two-stage stochastic modeling
framework to design optimal annual cropping and irrigation allocations
under pumping restrictions and uncertain precipitation. Optimal cropping
and allocation strategies by the stochastic optimization model
significantly outperform observed farmer strategies during the first two
five-year LEMA periods (2013-2022) but only outperformed the optimal
strategy by the deterministic optimization model assuming long-term
average precipitation during drier conditions. We show that optimal
cropping decisions shift from predominately corn to sorghum if more
stringent pumping restrictions are imposed. Furthermore, irrigators are
better off to use less water in the earlier years and saving more water
for later years under more stringent five-year pumping restrictions,
while they should use more of their allocation earlier under less
stringent pumping limits. Extending the duration of the groundwater
allocation window allows additional operational flexibility and enhances
profits but the marginal gains for each additional year drop off after
around seven years. Our versatile modeling framework is applicable to
other regions considering groundwater pumping restrictions with the aim
of balancing water conservation with farmer profitability and
adaptability.