Evaluation of Data Needs for Assessments of Aquifers Supporting Irrigated Agriculture

One of the primary means of addressing the depletion of aquifers supporting irrigated agriculture is to reduce pumping. In this work, we address the key question of how much data is needed to reliably predict the impact of pumping reductions. Previous studies have demonstrated the effectiveness of a simple water balance‐based approach for predicting the near‐term impact of changes in total pumping on changes in average water levels for areas ranging in size from 256 to 21,600 km2 in the High Plains aquifer (HPA) in the state of Kansas in the central U.S. This method shows considerable promise as a management tool in the Kansas HPA and potentially other highly stressed aquifers. However, one characteristic that sets the Kansas HPA apart from many other aquifers is an abundance of data on both water levels, from a decades‐old annual water level measurement program, and annual pumping volumes, due to reporting requirements and regulatory oversight. Most regions will have considerably less information. This study investigates the impact of more limited data availability through random subsampling of the water level and water use data sets from Groundwater Management District 4 (GMD4) in northwest Kansas and GMD5 in south‐central Kansas. The results indicate that accurate estimates of net inflow and specific yield, the key parameters needed to predict near‐term aquifer responses to proposed pumping reductions, can be obtained with much sparser water level and water use data than are available in the Kansas HPA, as long as the data are not systematically biased. Plain Language Summary Throughout the world, groundwater levels are declining rapidly in many aquifers supporting irrigated agriculture. In many of these areas, reduction of pumping is the only viable means to reduce decline rates in the near term. Previous studies have demonstrated the effectiveness of a simple approach for predicting the impact of proposed pumping reductions on water level decline rates based on historical water use and water level data. However, these studies have been applied in a region with abundant water use and water level data, namely the High Plains aquifer (HPA) region in the U.S. state of Kansas. This study examines the applicability of the method to areas with sparser data by sampling from the available data in two portions of the Kansas HPA, demonstrating that the method provides reasonably accurate results even with significantly less monitoring of water levels or water us