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Effective groundwater management is critical to future environmental, ecological, and social sustainability and requires accurate estimates of groundwater withdrawals. Unfortunately, these estimates are not readily available in most areas due to physical, regulatory, and social challenges. Here, we compare four different approaches for estimating groundwater withdrawals for agricultural irrigation. We apply these methods in a groundwater‐irrigated region in the state of Kansas, USA, where high‐quality groundwater withdrawal data are available for evaluation. The four methods represent a broad spectrum of approaches: (1) the hydrologically‐based Water Table Fluctuation method (WTFM); (2) the demand‐based SALUS crop model; (3) estimates based on satellite‐derived evapotranspiration (ET) data from OpenET; and (4) a landscape hydrology model which integrates hydrologic‐ and demand‐based approaches. The applicability of each approach varies based on data availability, spatial and temporal resolution, and accuracy of predictions. In general, our results indicate that all approaches reasonably estimate groundwater withdrawals in our region, however, the type and amount of data required for accurate estimates and the computational requirements vary among approaches. For example, WTFM requires accurate groundwater levels, specific yield, and recharge data, whereas the SALUS crop model requires adequate information about crop type, land use, and weather. This variability highlights the difficulty in identifying what data, and how much, are necessary for a reasonable groundwater withdrawal estimate, and suggests that data availability should drive the choice of approach. Overall, our findings will help practitioners evaluate the strengths and weaknesses of different approaches and select the appropriate approach for their application. 

Efficient irrigation technologies, which seem to promise reduced production costs and water consumption in heavily irrigated areas, may instead be driving increased irrigation use in areas that were not traditionally irrigated. As a result, the total dependence on supplemental irrigation for crop production and revenue is steadily increasing across the contiguous United States. Quantifying this dependence has been hampered by a lack of comprehensive irrigated and dryland yield and harvested area data outside of major irrigated regions, despite the importance and long history of irrigation applications in agriculture. This study used a linear regression model to disaggregate lumped agricultural statistics and estimate average irrigated and dryland yields at the state level for five major row crops: corn, cotton, hay, soybeans, and wheat. For 1945–2015, we quantified crop production, irrigation enhancement revenue, and irrigated and dryland areas in both intensively irrigated and marginally-dependent states, where both irrigated and dryland farming practices are implemented. In 2015, we found that irrigating just the five commodity crops enhanced revenue by ~$7 billion across all states with irrigation. In states with both irrigated and dryland practices, 23% of total produced area relied on irrigation, resulting in 7% more production than from dryland practices. There was a clear response to increasing biofuel demand, with the addition of more than 3.6 million ha of irrigated corn and soybeans in the last decade in marginally-dependent states. Since 1945, we estimate that yield enhancement due to irrigation has resulted in over $465 billion in increased revenue across the contiguous United States (CONUS). Example applications of this dataset include estimating historical water use, evaluating the effects of environmental policies, developing new resource management strategies, economic risk analyses, and developing tools for farmer decision making. 

Many irrigated agricultural areas seek to prolong the lifetime of their groundwater resources by reducing pumping. However, it is unclear how lagged responses, such as reduced groundwater recharge caused by more efficient irrigation, may impact the long‐term effectiveness of conservation initiatives. Here, we use a variably saturated, simplified surrogate groundwater model to: (a) analyze aquifer responses to pumping reductions, (b) quantify time lags between reductions and groundwater level responses, and (c) identify the physical controls on lagged responses. We explore a range of plausible model parameters for an area of the High Plains aquifer (USA) where stakeholder‐driven conservation has slowed groundwater depletion. We identify two types of lagged responses that reduce the long‐term effectiveness of groundwater conservation, recharge‐dominated and lateral‐flow‐dominated, with vertical hydraulic conductivity (K_Z) the major controlling variable. When highK_Zallows percolation to reach the aquifer, more efficient irrigation reduces groundwater recharge. By contrast, when lowK_Zimpedes vertical flow, short term changes in recharge are negligible, but pumping reductions alter the lateral flow between the groundwater conservation area and the surrounding regions (lateral‐flow‐dominated response). For the modeled area, we found that a pumping reduction of 30% resulted in median usable lifetime extensions of 20 or 25 years, depending on the dominant lagged response mechanism (recharge‐ vs. lateral‐flow‐dominated). These estimates are far shorter than estimates that do not account for lagged responses. Results indicate that conservation‐based pumping reductions can extend aquifer lifetimes, but lagged responses can create a sizable difference between the initially perceived and actual long‐term effectiveness.

 

Biofuel crops, including annuals such as maize (Zea maysL.), soybean [Glycine max(L.) Merr.], and canola (Brassica napusL.), as well as high‐biomass perennial grasses such as miscanthus (Miscanthus×giganteusJ.M. Greef & Deuter ex Hodkinson & Renvoiz), are candidates for sustainable alternative energy sources. However, large‐scale conversion of croplands to perennial biofuel crops could have substantial impacts on regional water, nutrient, and C cycles due to the longer growing seasons and differences in rooting systems compared with most annual crops. However, due to the limited tools available to nondestructively study the spatiotemporal patterns of root water uptake in situ at field scales, these differences in crop water use are not well known. Geophysical imaging tools such as electrical resistivity (ER) reveal changes in water content in the soil profile. In this study, we demonstrate the use of a novel coupled hydrogeophysical approach with both time domain reflectometry soil water content and ER measurements to compare root water uptake and soil properties of an annual crop rotation with the perennial grass miscanthus, across three growing seasons (2009–2011) in southwest Michigan, USA. We estimated maximum root depths to be between 1.2 and 2.2 m, with the vertical distribution of roots being notably deeper in 2009 relative to 2010 and 2011, likely due to the drought conditions during that first year. Modeled cumulative ET of both crops was underestimated (2–34%) relative to estimates obtained from soil water drawdown in prior studies but was found to be greater in the perennial grass than the annual crops, despite shallower modeled rooting depths in 2010 and 2011.