STATISTICAL ANALYSIS OF DRIVERS OF CHANGE IN GROUNDWATER ELEVATION TRAJECTORY IN THE HIGH PLAINS AQUIFER

This study uses segmented regression, a broken-line regression technique, to locate changes in the trajectory of water table elevations for wells in the High Plains Aquifer, and assess the drivers of these changes. The High Plains Aquifer, which stretches across much of the Great Plains from South Dakota to Texas, is among the most heavily stressed aquifers in the world. The vast majority of water drawn from the aquifer is used for irrigation. Despite calls for on-farm management of irrigation water, results indicate that wells tend to experience changes in trajectory at the same time as other wells in the same area, suggesting the primacy of large-scale prevailing conditions. Statistical models demonstrate that variations in weather and crop prices account for at least 25% of changes in water table trends. Dry conditions exert greater control in the Southern High Plains (New Mexico and Texas), while commodity prices are a stronger driver in the Northern High Plains (Nebraska). This study raises important issues for farmers and water regulators. The results of this study have strong implications for any researchers who are interested in predicting aquifer lifespan over the long term using statistical methods, namely that the trajectory of the water table over time is neither linear nor logarithmic, but that even very heavily stressed parts of the aquifer have gone through multiple cycles of rapid decline and recovery.