Abstract  In order to understand the anticipated status of the industry for non-starch ethanol and renewable hydrocarbon biofuels as of the end of calendar year 2015, the National Renewable Energy Laboratory (NREL) updated its annual survey of U.S. non-starch ethanol and renewable hydrocarbon biofuels producers. This report presents the results of this survey update, describes the survey methodology, and documents important changes since the 2015 survey published at the end of 2015 (Schwab et al. 2015).

Abstract  While agricultural residue is considered as a near-term feedstock option for cellulosic biofuels, its sustainability must be evaluated by taking water into account. This study aims to analyze the county-level water footprint for four biofuel pathways in the United States, including bioethanol generated from corn grain, stover, wheat straw, and biodiesel from soybean. The county-level blue water footprint of ethanol from corn grain, stover, and wheat straw shows extremely wide variances with a national average of 31, 132, and 139 L of water per liter biofuel (L(w)/L(bf)), and standard deviation of 133, 323, and 297 L(w)/L(bf), respectively. Soybean biodiesel production results in a blue water footprint of 313 L(w)/L(bf) on the national average with standard deviation of 894 L(w)/L(bf). All biofuels show a greater green water footprint than the blue one. This work elucidates how diverse spatial resolutions affect biofuel water footprints, which can provide detailed insights into biofuels' implications on local water sustainability.

Abstract  Water consumption and water quality continue to be key factors affecting environmental sustainability in biofuel production. This review covers the findings from biofuel water analyses published over the past 2 years to underscore the progress made, and to highlight advancements in understanding the interactions among increased production and water demand, water resource availability, and potential changes in water quality. We focus on two key areas: water footprint assessment and watershed modeling. Results revealed that miscanthus-, switchgrass-, and forest wood-based biofuels all have promising blue and grey water footprints. Alternative water resources have been explored for algae production, and challenges remain. A most noticeable improvement in the analysis of life-cycle water consumption is the adoption of geospatial analysis and watershed modeling to generate a spatially explicit water footprint at a finer scale (e.g., multi-state region, state, and county scales) to address the impacts of land use change and climate on the water footprint in a landscape with a mixed biofuel feedstock.

Abstract  A large imbalance between recharge and water withdrawal has caused vital regions of the High Plains Aquifer (HPA) to experience significant declines in storage. A new predevelopment map coupled with a synthesis of annual water levels demonstrates that aquifer storage has declined by approximately 410km super(3) since the 1930s, a 15% larger decline than previous estimates. If current rates of decline continue, much of the Southern High Plains and parts of the Central High Plains will have insufficient water for irrigation within the next 20 to 30 years, whereas most of the Northern High Plains will experience little change in storage. In the western parts of the Central and northern part of the Southern High Plains, saturated thickness has locally declined by more than 50%, and is currently declining at rates of 10% to 20% of initial thickness per decade. The most agriculturally productive portions of the High Plains will not support irrigated production within a matter of decades without significant changes in management.

Abstract  Understanding how irrigated areas change over time is vital to effectively manage limited agricultural water resources, but long-term, high-resolution, and spatially explicit datasets are rare. The High Plains Aquifer (HPA) in the central United States is one of the largest and most stressed aquifer systems in the world. It supports a $20 billion economy, but groundwater use is unsustainable over much of the aquifer. Emerging cloud computing tools like Google Earth Engine (GEE) make it possible to use the full Landsat record to monitor regional systems like the HPA with high spatial and temporal resolution over multiple decades. However, challenges remain to develop irrigation classification methods that are robust to a wide range of climate conditions and crop types, evolving management, and missing data. Here, we addressed these challenges to produce an annual, moderately high resolution (30 m) irrigation map time series from 1984 to 2017 over the aquifer. Leveraging GEE's extensive data catalog, we combined Landsat imagery, environmental covariables, and a large heterogeneous ground truth dataset to create a single random forest classifier applied annually to the entire region. Following classification, we applied the Bayesian Updating of Land-Cover (BULC) algorithm to fill imagery gaps and reduce commission errors in the provisional irrigation time series. Novel neighborhood greenness indices contributed to an overall 91.4% map accuracy across years; county statistics (r2 = 0.86) were similarly well-matched. Trend analysis of irrigated area through time identified regions of stable, expanding, and declining irrigated area. Given declining aquifer storage, we estimate that up to 24% of currently irrigated area may be lost this century. To date, the map dataset is the longest, highest resolution large-scale record of where and when irrigation occurs. It is freely available for stakeholders, managers, and researchers to inform policies and management decisions, as well as for use in hydrology, agronomy, and climate models.

Abstract  Recent expansion of croplands in the United States has caused widespread conversion of grasslands and other ecosystems with largely unknown consequences for agricultural production and the environment. Here we assess annual land use change 2008-16 and its impacts on crop yields and wildlife habitat. We find that croplands have expanded at a rate of over one million acres per year, and that 69.5% of new cropland areas produced yields below the national average, with a mean yield deficit of 6.5%. Observed conversion infringed upon high-quality habitat that, relative to unconverted land, had provided over three times higher milkweed stem densities in the Monarch butterfly Midwest summer breeding range and 37% more nesting opportunities per acre for waterfowl in the Prairie Pothole Region of the Northern Great Plains. Our findings demonstrate a pervasive pattern of encroachment into areas that are increasingly marginal for production, but highly significant for wildlife, and suggest that such tradeoffs may be further amplified by future cropland expansion.

Abstract  This study aims to quantify water appropriation and the potential production of algal bio-oil using freshwater and municipal wastewater effluent (MWW) as an alternative water resource. The county-level analysis focuses on open-pond algae cultivation systems located in 17 states in the southern United States. Several scenarios were developed to examine the water availability for algae bio-oil production under various water resource mixing MWW and freshwater. The results of the analysis indicate that water availability can significantly affect the selection of an algal refinery site and therefore the potential production of algal bio-oil. The production of one liter of algal bio-oil requires 1036–1666 L of water at the state level, in which 3% to 91% can be displaced by MWW, depending on the biorefinery location. This water requirement corresponds to a total of 25 billion liters of bio-oil produced if the spatially and temporally available MWW effluent together with 10% of total available freshwater are used. The production of algal bio-oil is only 14% of estimated production under the assumption that all of the water demand can be fulfilled without any restriction. In addition, if only the spatially and temporally available effluent is used as the sole source of water, the total bio-oil production is estimated to be 9 billion liters. This study not only quantifies the water demands of the algal bio-oil, but it also elucidates the importance of taking water sustainability into account in the development of algal bio-oil.

Abstract  Concurrent measurements of reflected canopy radia-tion and the basal crop coefficient (K^b) for corn were conducted throughout a season in order to develop a reflectance-based crop coefficient model. Reflectance was measured in Landsat Thematic Mapper bands TM3 (0.63 - 0.69 um) and TM4 (0.76 - 0.90 um) and used in the calculation of a vegetation index called the normalized difference (ND). A linear transformation of the ND was used as the reflectance-based crop coefficient (Kcr). The transformation equates the ND for dry bare soil and the ND at effective cover, to the basal crop coefficient for dry soil evaporation and at effective cover, respectively. Basal crop coefficient values for com were obtained from daily evapotranspiration measurements of corn and alfalfa, using hydraulic weighing lysimeters. The Richards growth curve function was fitted to both sets of data. The K^b values were determined to be within -2.6% and 4.7% of the K^^ values. The date of effective cover obtained from the K^b data was within four days of the date on which the ND curve reached its maxima according to the Richards function. A comparison of the Kcr with basal crop curves from the literature for several years of data indicated good agreement. Reflectance-based crop coefficients are sensitive to periods of slow and fast growth induced by weather conditions, resulting in a real time coefficient, independent from the traditional time base parameters based on the day of planting and effective cover.

Abstract  Nonrenewable groundwater contributes ∼20% of global irrigation water. As a result, key agricultural regions around the world are on unsustainable trajectories due to aquifer depletion, threatening food production and local economies. With increasing resource scarcity in the central High Plains Aquifer in the United States, an innovative stakeholder-driven groundwater management framework emerged in Kansas referred to as the Local Enhanced Management Area (LEMA) program. This framework enables groups of irrigators to join together to implement measures to conserve groundwater. Here, we assessed the efficacy of the first LEMA to move the region toward sustainability with a process-based crop model driven by well records and satellite-derived annual land use. We found increased irrigation efficiency under the LEMA program reduced groundwater extraction by 25% (40 million m3). However, only 22% of pumping reductions benefitted the net water balance (9 million m3) due to decreased irrigation return flow resulting from increased irrigation efficiency. We then estimated economic impacts using simulated crop yields, commodity prices, and estimated energy saved from reduced groundwater pumping. Cost savings from reduced pumping were about 4.5 times greater than the income lost from minor yield penalties. This suggests that the program promotes both economic and water sustainability, but water targets may need to be more strict to stabilize groundwater levels. As aquifer depletion threatens crop production in many parts of the world, approaches that integrate dynamic process-based models with in situ and satellite data can inform economically and hydrologically sustainable management strategies. Our work highlights the need to consider both economic factors and root zone processes when evaluating irrigation conservation programs.

Abstract  The perpetuation of current trend of growing more corn for ethanol is projected to further exacerbate water quality problems in the Upper Mississippi River Basin (URMB). Switchgrass with cellulosic ethanol potential which requires no or little fertilizers can be effective in reducing nonpoint source pollutants such as nitrate and sediments. In this study, the Soil and Water Assessment Tool model was applied to the UMRB to simulate and evaluate the impacts of two bio-fuel crops (corn and switchgrass) on nonpoint source pollution. High impact areas to which a large amount of pollutants are attributed were identified by simulating and analyzing nitrate outputs from 131 subbasins. Simulation results showed that growing switchgrass instead of corn could reduce nitrate yield by up to 71% (14 kg/ha) and sediments by up to 99% (5 t/ha). It is demonstrated that water quality in the UMRB can be significantly improved and meanwhile economic benefits can still be derived. The results of this study can assist in cost-benefit analysis and decision-making in environmental management in large-scale agricultural areas.

Abstract  Crop coefficient (Kc)-based estimation of crop evapotranspiration is one of the most commonly used methods for irrigation water management. However, uncertainties of the generalized dual crop coefficient (Kc) method of the Food and Agricultural Organization of the United Nations Irrigation and Drainage Paper No. 56 can contribute to crop evapotranspiration estimates that are substantially different from actual crop evapotranspiration. Similarities between the crop coefficient curve and a satellite-derived vegetation index showed potential for modeling a crop coefficient as a function of the vegetation index. Therefore, the possibility of directly estimating the crop coefficient from satellite reflectance of a crop was investigated. The Kc data used in developing the relationship with NDVI were derived from back-calculations of the FAO-56 dual crop coefficients procedure using field data obtained during 2007 from representative US cropping systems in the High Plains from AmeriFlux sites. A simple linear regression model ( ) is developed to establish a general relationship between a normalized difference vegetation index (NDVI) from a moderate resolution satellite data (MODIS) and the crop coefficient (Kc) calculated from the flux data measured for different crops and cropping practices using AmeriFlux towers. There was a strong linear correlation between the NDVI-estimated Kc and the measured Kc with an r2 of 0.91 and 0.90, while the root-mean-square error (RMSE) for Kc in 2006 and 2007 were 0.16 and 0.19, respectively. The procedure for quantifying crop coefficients from NDVI data presented in this paper should be useful in other regions of the globe to understand regional irrigation water consumption.

Abstract  Irrigated agriculture is generally considered to be more productive than rainfed agriculture at any given location. This difference in crop yield between irrigated and rainfed production ('Irrigation-limited yield gap' or ILYG) is subject to spatio-temporal variability, due to differences in management, environmental conditions, soils, and policy. However, quantification of ILYG and its associated variability remains uninvestigated. In this study, we analyzed the spatio-temporal dynamics of county level-ILYG for nine major irrigated crops in the United States: maize, soybean, spring wheat, winter wheat, alfalfa, sorghum, cotton, barley and oats from around 1950 to 2015. ILYG was found to be highly specific to crop and location and has been increasing, in general, over time, albeit with regional differences. Maize had the greatest ILYG magnitude on a national basis, with cotton ILYG showing highest temporal rates of increase. Increased ILYG variability over the study period was found for all crops, except cotton, which also showed the highest magnitude of long-term mean variability. Maps and key information in this article are significant to irrigation research, policy and decision-making, plant breeding, groundwater withdrawal allocation strategies and producers to identify pertinent regions using historical ILYG for optimizing farm irrigation management strategies to enhance overall national agricultural productivity.

Abstract  Fresh ground-water withdrawals from 66 principal aquifers in the United States were estimated for irrigation, public-supply, and self-supplied industrial water uses for the year 2000. Total ground-water withdrawals were 76,500 million gallons per day, or 85,800 thousand acre-feet per year for these three uses. Irrigation used the largest amount of ground water, 56,900 million gallons per day, followed by public supply with 16,000 million gallons per day, and self-supplied industrial with 3,570 million gallons per day. These three water uses represented 92 percent of the fresh ground-water withdrawals for all uses in the United States, the remaining 8 percent included self-supplied domestic, aquaculture, livestock, mining, and thermoelectric power uses. Aquifer withdrawals were categorized by five lithologic groups: unconsolidated and semiconsolidated sand and gravel aquifers, carbonate-rock aquifers, igneous and metamorphic-rock aquifers, sandstone aquifers, and sandstone and carbonate-rock aquifers. Withdrawals from aquifers that were not included in one of the 66 principal aquifers were reported in an "Other" aquifers group. The largest withdrawals in the United States were from unconsolidated and semiconsolidated sand and gravel aquifers, which accounted for 80 percent of total withdrawals from all aquifers. Carbonate-rock aquifers provided 8 percent of the withdrawals, and igneous and metamorphic-rock aquifers, 6 percent. Withdrawals from sandstone aquifers, from sandstone and carbonate-rock aquifers, and from the "Other" aquifers category each constituted about 2 percent of the total withdrawals reported. Fifty-five percent of the total withdrawals for irrigation, public-supply, and self-supplied industrial water uses were provided by the High Plains aquifer, California Central Valley aquifer system, the Mississippi River Valley alluvial aquifer, and the Basin and Range basin-fill aquifers. These aquifers provided most of the withdrawals for irrigation. The High Plains aquifer was the most intensively used aquifer in the United States. This aquifer provided 23 percent of the total withdrawals from all aquifers for irrigation, public-supply, and self-supplied industrial water uses combined, and 30 percent of the total withdrawals from all aquifers for irrigation. The primary aquifers used for public supply were the glacial sand and gravel aquifers of the Northeastern and North-Central States, the California Coastal Basin aquifers, the Floridan aquifer system, the Basin and Range basin-fill aquifers, and the Coastal lowlands aquifer system along the Gulf Coast. These five aquifers provided 43 percent of the total withdrawals from all aquifers for public supply. The glacial sand and gravel aquifers, Coastal lowlands aquifer system, Floridan aquifer system, and Cambrian-Ordovician aquifer system were the primary sources of water for self-supplied industrial use; these aquifers provided 46 percent of the total ground-water withdrawals for that use.

Abstract  In modern agriculture, the interplay between complex physical, agricultural, and socioeconomic water use drivers must be fully understood to successfully manage water supplies on extended timescales. This is particularly evident across large portions of the High Plains Aquifer where groundwater levels have declined at unsustainable rates despite improvements in both the efficiency of water use and water productivity in agricultural practices. Improved technology and land use practices have not mitigated groundwater level declines, thus water management strategies must adapt accordingly or risk further resource loss. In this study, we analyze the water-energy-food nexus over the High Plains Aquifer as a framework to isolate the major drivers that have shaped the history, and will direct the future, of water use in modern agriculture. Based on this analysis, we conclude that future water management strategies can benefit from: (1) prioritizing farmer profit to encourage decision-making that aligns with strategic objectives, (2) management of water as both an input into the water-energy-food nexus and a key incentive for farmers, (3) adaptive frameworks that allow for short-term objectives within long-term goals, (4) innovative strategies that fit within restrictive political frameworks, (5) reduced production risks to aid farmer decision-making, and (6) increasing the political desire to conserve valuable water resources. This research sets the foundation to address water management as a function of complex decision-making trends linked to the water-energy-food nexus. Water management strategy recommendations are made based on the objective of balancing farmer profit and conserving water resources to ensure future agricultural production.