Bureau of Economic Analysis

Abstract Matrix-related pore networks in mudrocks are composed of nanometer- to micrometer-size pores. In shale-gas systems, these pores, along with natural fractures, form the flow-path (permeability) network that allows flow of gas from the mudrock to induced fractures during production. A pore classification consisting of three major matrix-related pore types is presented that can be used to quantify matrix-related pores and relate them to pore networks. Two pore types are associated with the mineral matrix; the third pore type is associated with organic matter (OM). Fracture pores are not controlled by individual matrix particles and are not part of this classification. Pores associated with mineral particles can be subdivided into interparticle (interP) pores that are found between particles and crystals and intraparticle (intraP) pores that are located within particles. Organic-matter pores are intraP pores located within OM. Interparticle mineral pores have a higher probability of being part of an effective pore network than intraP mineral pores because they are more likely to be interconnected. Although they are intraP, OM pores are also likely to be part of an interconnected network because of the interconnectivity of OM particles. In unlithifed near-surface muds, pores consist of interP and intraP pores, and as the muds are buried, they compact and lithify. During the compaction process, a large number of interP and intraP pores are destroyed, especially in ductile grain-rich muds. Compaction can decrease the pore volume up to 88% by several kilometers of burial. At the onset of hydrocarbon thermal maturation, OM pores are created in kerogen. At depth, dissolution of chemically unstable particles can create additional moldic intraP pores.

Aquifer overexploitation could significantly impact crop production in the United States because 60% of irrigation relies on groundwater. Groundwater depletion in the irrigated High Plains and California Central Valley accounts for ~50% of groundwater depletion in the United States since 1900. A newly developed High Plains recharge map shows that high recharge in the northern High Plains results in sustainable pumpage, whereas lower recharge in the central and southern High Plains has resulted in focused depletion of 330 km(3) of fossil groundwater, mostly recharged during the past 13,000 y. Depletion is highly localized with about a third of depletion occurring in 4% of the High Plains land area. Extrapolation of the current depletion rate suggests that 35% of the southern High Plains will be unable to support irrigation within the next 30 y. Reducing irrigation withdrawals could extend the lifespan of the aquifer but would not result in sustainable management of this fossil groundwater. The Central Valley is a more dynamic, engineered system, with north/south diversions of surface water since the 1950s contributing to ~7× higher recharge. However, these diversions are regulated because of impacts on endangered species. A newly developed Central Valley Hydrologic Model shows that groundwater depletion since the 1960s, totaling 80 km(3), occurs mostly in the south (Tulare Basin) and primarily during droughts. Increasing water storage through artificial recharge of excess surface water in aquifers by up to 3 km(3) shows promise for coping with droughts and improving sustainability of groundwater resources in the Central Valley.

Importance: US health care spending has continued to increase and now accounts for 18% of the US economy, although little is known about how spending on each health condition varies by payer, and how these amounts have changed over time. Objective: To estimate US spending on health care according to 3 types of payers (public insurance [including Medicare, Medicaid, and other government programs], private insurance, or out-of-pocket payments) and by health condition, age group, sex, and type of care for 1996 through 2016. Design and Setting: Government budgets, insurance claims, facility records, household surveys, and official US records from 1996 through 2016 were collected to estimate spending for 154 health conditions. Spending growth rates (standardized by population size and age group) were calculated for each type of payer and health condition. Exposures: Ambulatory care, inpatient care, nursing care facility stay, emergency department care, dental care, and purchase of prescribed pharmaceuticals in a retail setting. Main Outcomes and Measures: National spending estimates stratified by health condition, age group, sex, type of care, and type of payer and modeled for each year from 1996 through 2016. Results: Total health care spending increased from an estimated $1.4 trillion in 1996 (13.3% of gross domestic product [GDP]; $5259 per person) to an estimated $3.1 trillion in 2016 (17.9% of GDP; $9655 per person); 85.2% of that spending was included in this study. In 2016, an estimated 48.0% (95% CI, 48.0%-48.0%) of health care spending was paid by private insurance, 42.6% (95% CI, 42.5%-42.6%) by public insurance, and 9.4% (95% CI, 9.4%-9.4%) by out-of-pocket payments. In 2016, among the 154 conditions, low back and neck pain had the highest amount of health care spending with an estimated $134.5 billion (95% CI, $122.4-$146.9 billion) in spending, of which 57.2% (95% CI, 52.2%-61.2%) was paid by private insurance, 33.7% (95% CI, 30.0%-38.4%) by public insurance, and 9.2% (95% CI, 8.3%-10.4%) by out-of-pocket payments. Other musculoskeletal disorders accounted for the second highest amount of health care spending (estimated at $129.8 billion [95% CI, $116.3-$149.7 billion]) and most had private insurance (56.4% [95% CI, 52.6%-59.3%]). Diabetes accounted for the third highest amount of the health care spending (estimated at $111.2 billion [95% CI, $105.7-$115.9 billion]) and most had public insurance (49.8% [95% CI, 44.4%-56.0%]). Other conditions estimated to have substantial health care spending in 2016 were ischemic heart disease ($89.3 billion [95% CI, $81.1-$95.5 billion]), falls ($87.4 billion [95% CI, $75.0-$100.1 billion]), urinary diseases ($86.0 billion [95% CI, $76.3-$95.9 billion]), skin and subcutaneous diseases ($85.0 billion [95% CI, $80.5-$90.2 billion]), osteoarthritis ($80.0 billion [95% CI, $72.2-$86.1 billion]), dementias ($79.2 billion [95% CI, $67.6-$90.8 billion]), and hypertension ($79.0 billion [95% CI, $72.6-$86.8 billion]). The conditions with the highest spending varied by type of payer, age, sex, type of care, and year. After adjusting for changes in inflation, population size, and age groups, public insurance spending was estimated to have increased at an annualized rate of 2.9% (95% CI, 2.9%-2.9%); private insurance, 2.6% (95% CI, 2.6%-2.6%); and out-of-pocket payments, 1.1% (95% CI, 1.0%-1.1%). Conclusions and Relevance: Estimates of US spending on health care showed substantial increases from 1996 through 2016, with the highest increases in population-adjusted spending by public insurance. Although spending on low back and neck pain, other musculoskeletal disorders, and diabetes accounted for the highest amounts of spending, the payers and the rates of change in annual spending growth rates varied considerably.

Abstract Global synthesis of the findings from ∼140 recharge study areas in semiarid and arid regions provides important information on recharge rates, controls, and processes, which are critical for sustainable water development. Water resource evaluation, dryland salinity assessment (Australia), and radioactive waste disposal (US) are among the primary goals of many of these recharge studies. The chloride mass balance (CMB) technique is widely used to estimate recharge. Average recharge rates estimated over large areas (40–374 000 km 2 ) range from 0·2 to 35 mm year −1 , representing 0·1–5% of long‐term average annual precipitation. Extreme local variability in recharge, with rates up to ∼720 m year −1 , results from focussed recharge beneath ephemeral streams and lakes and preferential flow mostly in fractured systems. System response to climate variability and land use/land cover (LU/LC) changes is archived in unsaturated zone tracer profiles and in groundwater level fluctuations. Inter‐annual climate variability related to El Niño Southern Oscillation (ENSO) results in up to three times higher recharge in regions within the SW US during periods of frequent El Niños (1977–1998) relative to periods dominated by La Niñas (1941–1957). Enhanced recharge related to ENSO is also documented in Argentina. Climate variability at decadal to century scales recorded in chloride profiles in Africa results in recharge rates of 30 mm year −1 during the Sahel drought (1970–1986) to 150 mm year −1 during non‐drought periods. Variations in climate at millennial scales in the SW US changed systems from recharge during the Pleistocene glacial period (≥10 000 years ago) to discharge during the Holocene semiarid period. LU/LC changes such as deforestation in Australia increased recharge up to about 2 orders of magnitude. Changes from natural grassland and shrublands to dryland (rain‐fed) agriculture altered systems from discharge (evapotranspiration, ET) to recharge in the SW US. The impact of LU change was much greater than climate variability in Niger (Africa), where replacement of savanna by crops increased recharge by about an order of magnitude even during severe droughts. Sensitivity of recharge to LU/LC changes suggests that recharge may be controlled through management of LU. In irrigated areas, recharge varies from 10 to 485 mm year −1 , representing 1–25% of irrigation plus precipitation. However, irrigation pumpage in groundwater‐fed irrigated areas greatly exceeds recharge rates, resulting in groundwater mining. Increased recharge related to cultivation has mobilized salts that accumulated in the unsaturated zone over millennia, resulting in widespread groundwater and surface water contamination, particularly in Australia. The synthesis of recharge rates provided in this study contains valuable information for developing sustainable groundwater resource programmes within the context of climate variability and LU/LC change. Copyright © 2006 John Wiley & Sons, Ltd.

Income convergence across countries turns on whether technological knowledge spillovers are global or local. I estimate the amount of spillovers from R&D expenditures on a geographic basis, using a new data set which encompasses most of the world's innovative activity between 1970 and 1995. I find that technology is to a substantial degree local, not global, as the benefits from spillovers are declining with distance. The distance at which the amount of spillovers is halved is about 1,200 kilometers. I also find that over time, technological knowledge has become considerably more global. Moreover, language skills are important for spillover diffusion.

Abstract The Marcellus Formation of Pennsylvania represents an outstanding example of an organic matter (OM)–hosted pore system; most pores detectable by field-emission scanning electron microscopy (FE-SEM) are associated with OM instead of mineral matrix. In the two wells studied here, total organic carbon (TOC) content is a stronger control on OM-hosted porosity than is thermal maturity. The two study wells span a maturity from late wet gas (vitrinite reflectance [Ro], ∼1.0%) to dry gas (Ro, ∼2.1%). Samples with a TOC less than 5.5 wt. % display a positive correlation between TOC and porosity, but samples with a TOC greater than 5.5 wt. % display little or no increase in porosity with a further increasing TOC. In a subset of samples (14) across a range of TOC (2.3–13.6 wt. %), the pore volume detectable by FE-SEM is a small fraction of total porosity, ranging from 2 to 32% of the helium porosity. Importantly, the FE-SEM–visible porosity in OM decreases significantly with increasing TOC, diminishing from 30% of OM volume to less than 1% of OM volume across the range of TOC. The morphology and size of OM-hosted pores also vary systematically with TOC. The interpretation of this anticorrelation between OM content and SEM-visible pores remains uncertain. Samples with the lowest OM porosity (higher TOC) may represent gas expulsion (pore collapse) that was more complete as a consequence of greater OM connectivity and framework compaction, whereas samples with higher OM porosity (lower TOC) correspond to rigid mineral frameworks that inhibited compactional expulsion of methane-filled bubbles. Alternatively, higher TOC samples may contain OM (low initial hydrogen index, relatively unreactive) that is less prone to development of FE-SEM–detectable pores. In this interpretation, OM type, controlled by sequence-stratigraphic position, is a factor in determining pore-size distribution.

Importance: US health care spending has continued to increase, and now accounts for more than 17% of the US economy. Despite the size and growth of this spending, little is known about how spending on each condition varies by age and across time. Objective: To systematically and comprehensively estimate US spending on personal health care and public health, according to condition, age and sex group, and type of care. Design and Setting: Government budgets, insurance claims, facility surveys, household surveys, and official US records from 1996 through 2013 were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions (including cancer, which was disaggregated into 29 conditions). For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Spending was adjusted to reflect the health condition treated, rather than the primary diagnosis. Exposures: Encounter with US health care system. Main Outcomes and Measures: National spending estimates stratified by condition, age and sex group, and type of care. Results: From 1996 through 2013, $30.1 trillion of personal health care spending was disaggregated by 155 conditions, age and sex group, and type of care. Among these 155 conditions, diabetes had the highest health care spending in 2013, with an estimated $101.4 billion (uncertainty interval [UI], $96.7 billion-$106.5 billion) in spending, including 57.6% (UI, 53.8%-62.1%) spent on pharmaceuticals and 23.5% (UI, 21.7%-25.7%) spent on ambulatory care. Ischemic heart disease accounted for the second-highest amount of health care spending in 2013, with estimated spending of $88.1 billion (UI, $82.7 billion-$92.9 billion), and low back and neck pain accounted for the third-highest amount, with estimated health care spending of $87.6 billion (UI, $67.5 billion-$94.1 billion). The conditions with the highest spending levels varied by age, sex, type of care, and year. Personal health care spending increased for 143 of the 155 conditions from 1996 through 2013. Spending on low back and neck pain and on diabetes increased the most over the 18 years, by an estimated $57.2 billion (UI, $47.4 billion-$64.4 billion) and $64.4 billion (UI, $57.8 billion-$70.7 billion), respectively. From 1996 through 2013, spending on emergency care and retail pharmaceuticals increased at the fastest rates (6.4% [UI, 6.4%-6.4%] and 5.6% [UI, 5.6%-5.6%] annual growth rate, respectively), which were higher than annual rates for spending on inpatient care (2.8% [UI, 2.8%-2.8%] and nursing facility care (2.5% [UI, 2.5%-2.5%]). Conclusions and Relevance: Modeled estimates of US spending on personal health care and public health showed substantial increases from 1996 through 2013; with spending on diabetes, ischemic heart disease, and low back and neck pain accounting for the highest amounts of spending by disease category. The rate of change in annual spending varied considerably among different conditions and types of care. This information may have implications for efforts to control US health care spending.

Abstract Gas production from the Barnett Shale relies on hydraulic fracture stimulation. Natural opening-mode fractures reactivate during stimulation and enhance efficiency by widening the treatment zone. Knowledge of both the present-day maximum horizontal stress, which controls the direction of hydraulic fracture propagation, and the geometry of the natural fracture system, which we discuss here, is therefore necessary for effective hydraulic fracture treatment design. We characterized natural fractures in four Barnett Shale cores in terms of orientation, size, and sealing properties. We measured a mechanical rock property, the subcritical crack index, which governs fracture pattern development. Natural fractures are common, narrow (<0.05 mm; <0.002 in.), sealed with calcite, and present in en echelon arrays. Individual fractures have high length/width aspect ratios (>1000:1). They are steep (>75°), and the dominant trend is west-northwest. Other sets trend north-south. The narrow fractures are sealed and cannot contribute to reservoir storage or enhance permeability, but the population may follow a power-law size distribution where the largest fractures are open. The subcritical crack index for the Barnett Shale is high, indicating fracture clustering, and we suggest that large open fractures exist in clusters spaced several hundred feet apart. These fracture clusters may enhance permeability locally, but they may be problematic for hydraulic fracture treatments. The smaller sealed fractures act as planes of weakness and reactivate during hydraulic fracture treatments. Because the maximum horizontal stress trends northeast-southwest and is nearly normal to the dominant natural fractures, reactivation widens the treatment zone along multiple strands.

In this paper we utilize White's Reality Check bootstrap methodology (White (1999)) to evaluate simple technical trading rules while quantifying the data‐snooping bias and fully adjusting for its effect in the context of the full universe from which the trading rules were drawn. Hence, for the first time, the paper presents a comprehensive test of performance across all technical trading rules examined. We consider the study of Brock, Lakonishok, and LeBaron (1992), expand their universe of 26 trading rules, apply the rules to 100 years of daily data on the Dow Jones Industrial Average, and determine the effects of data‐snooping.

Abstract The Mississippian Barnett Formation of the Fort Worth Basin is a classic shale-gas system in which the rock is the source, reservoir, and seal. Barnett strata were deposited in a deeper water foreland basin that had poor circulation with the open ocean. For most of the basin's history, bottom waters were euxinic, preserving organic matter and, thus, creating a rich source rock, along with abundant framboidal pyrite. The Barnett interval comprises a variety of facies but is dominated by fine-grained (clay- to silt-size) particles. Three general lithofacies are recognized on the basis of mineralogy, fabric, biota, and texture: (1) laminated siliceous mudstone; (2) laminated argillaceous lime mudstone (marl); and (3) skeletal, argillaceous lime packstone. Each facies contains abundant pyrite and phosphate (apatite), which are especially common at hardgrounds. Carbonate concretions, a product of early diagenesis, are also common. The entire Barnett biota is composed of debris transported to the basin from the shelf or upper oxygenated slope by hemipelagic mud plumes, dilute turbidites, and debris flows. Biogenic sediment was also sourced from the shallower, better oxygenated water column. Barnett deposition is estimated to have occurred over a 25-m.y. period, and despite the variations in sublithofacies, sedimentation style remained remarkably similar throughout this span of time.

de niveau recherche, publis ou non, manant des tablissements d'enseignement et de recherche franais ou trangers, des laboratoires publics ou privs.

ABSTRACT Delineating faults from seismic images is a key step for seismic structural interpretation, reservoir characterization, and well placement. In conventional methods, faults are considered as seismic reflection discontinuities and are detected by calculating attributes that estimate reflection continuities or discontinuities. We consider fault detection as a binary image segmentation problem of labeling a 3D seismic image with ones on faults and zeros elsewhere. We have performed an efficient image-to-image fault segmentation using a supervised fully convolutional neural network. To train the network, we automatically create 200 3D synthetic seismic images and corresponding binary fault labeling images, which are shown to be sufficient to train a good fault segmentation network. Because a binary fault image is highly imbalanced between zeros (nonfault) and ones (fault), we use a class-balanced binary cross-entropy loss function to adjust the imbalance so that the network is not trained or converged to predict only zeros. After training with only the synthetic data sets, the network automatically learns to calculate rich and proper features that are important for fault detection. Multiple field examples indicate that the neural network (trained by only synthetic data sets) can predict faults from 3D seismic images much more accurately and efficiently than conventional methods. With a TITAN Xp GPU, the training processing takes approximately 2 h and predicting faults in a 128×128×128 seismic volume takes only milliseconds.

Past land use changes have greatly impacted global water resources, with often opposing effects on water quantity and quality. Increases in rain‐fed cropland (460%) and pastureland (560%) during the past 300 years from forest and grasslands decreased evapotranspiration and increased recharge (two orders of magnitude) and streamflow (one order of magnitude). However, increased water quantity degraded water quality by mobilization of salts, salinization caused by shallow water tables, and fertilizer leaching into underlying aquifers that discharge to streams. Since the 1950s, irrigated agriculture has expanded globally by 174%, accounting for ∼90% of global freshwater consumption. Irrigation based on surface water reduced streamflow and raised water tables resulting in waterlogging in many areas (China, India, and United States). Marked increases in groundwater‐fed irrigation in the last few decades in these areas has lowered water tables (≤1 m/yr) and reduced streamflow. Degradation of water quality in irrigated areas has resulted from processes similar to those in rain‐fed agriculture: salt mobilization, salinization in waterlogged areas, and fertilizer leaching. Strategies for remediating water resource problems related to agriculture often have opposing effects on water quantity and quality. Long time lags (decades to centuries) between land use changes and system response (e.g., recharge, streamflow, and water quality), particularly in semiarid regions, mean that the full impact of land use changes has not been realized in many areas and remediation to reverse impacts will also take a long time. Future land use changes should consider potential impacts on water resources, particularly trade‐offs between water, salt, and nutrient balances, to develop sustainable water resources to meet human and ecosystem needs.

Core Ideas A community effort is needed to move soil modeling forward. Establishing an international soil modeling consortium is key in this respect. There is a need to better integrate existing knowledge in soil models. Integration of data and models is a key challenge in soil modeling. The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate‐change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.

As HCI researchers have explored the possibilities of human computation, they have paid less attention to ethics and values of crowdwork. This paper offers an analysis of Amazon Mechanical Turk, a popular human computation system, as a site of technically mediated worker-employer relations. We argue that human computation currently relies on worker invisibility. We then present Turkopticon, an activist system that allows workers to publicize and evaluate their relationships with employers. As a common infrastructure, Turkopticon also enables workers to engage one another in mutual aid. We conclude by discussing the potentials and challenges of sustaining activist technologies that intervene in large, existing socio-technical systems. Copyright © 2013 ACM.

Significance We increasingly rely on global models to project impacts of humans and climate on water resources. How reliable are these models? While past model intercomparison projects focused on water fluxes, we provide here the first comprehensive comparison of land total water storage trends from seven global models to trends from Gravity Recovery and Climate Experiment (GRACE) satellites, which have been likened to giant weighing scales in the sky. The models underestimate the large decadal (2002–2014) trends in water storage relative to GRACE satellites, both decreasing trends related to human intervention and climate and increasing trends related primarily to climate variations. The poor agreement between models and GRACE underscores the challenges remaining for global models to capture human or climate impacts on global water storage trends.

Abstract Humans have exerted large‐scale changes on the terrestrial biosphere, primarily through agriculture; however, the impacts of such changes on the hydrologic cycle are poorly understood. The purpose of this study was to test the hypothesis that the conversion of natural rangeland ecosystems to agricultural ecosystems impacts the subsurface portion of the hydrologic cycle by changing groundwater recharge and flushing salts to underlying aquifers. The hypothesis was examined through point and areal studies investigating the effects of land use/land cover (LU/LC) changes on groundwater recharge and solute transport in the Amargosa Desert (AD) in Nevada and in the High Plains (HP) in Texas, US. Studies use the fact that matric (pore‐water‐pressure) potential and environmental‐tracer profiles in thick unsaturated zones archive past changes in recharging fluxes. Results show that recharge is related to LU/LC as follows: discharge through evapotranspiration (i.e., no recharge; upward fluxes <0.1 mm yr −1 ) in natural rangeland ecosystems (low matric potentials; high chloride and nitrate concentrations); moderate‐to‐high recharge in irrigated agricultural ecosystems (high matric potentials; low‐to‐moderate chloride and nitrate concentrations) (AD recharge: ∼130–640 mm yr −1 ); and moderate recharge in nonirrigated (dryland) agricultural ecosystems (high matric potentials; low chloride and nitrate concentrations, and increasing groundwater levels) (HP recharge: ∼9–32 mm yr −1 ). Replacement of rangeland with agriculture changed flow directions from upward (discharge) to downward (recharge). Recent replacement of rangeland with irrigated ecosystems was documented through downward displacement of chloride and nitrate fronts. Thick unsaturated zones contain a reservoir of salts that are readily mobilized under increased recharge related to LU/LC changes, potentially degrading groundwater quality. Sustainable land use requires quantitative knowledge of the linkages between ecosystem change, recharge, and groundwater quality.

ABSTRACT Basic meteorological data are essential for evaluating impacts of spatiotemporal variability in climate forcing on hydrology and agroecosystems. The objective of this work was to develop high‐resolution grids (0.25 ∘ × 0.25 ∘ ) of daily precipitation, evapotranspiration, and the five climate variables generally required to estimate evapostranspiration for Brazil. These five variables are maximum and minimum temperature, solar radiation, relative humidity, and wind speed. We tested six different interpolation schemes to create the grids for these variables. The data were obtained from 3625 rain gauge and 735 weather stations for period of 1980–2013. We used a cross‐validation approach that compares point observed data to point interpolated estimates to select the best interpolation scheme for each climate variable. We also present the performance of the best interpolation for each climate variable at daily timescales and for river basins. The inverse distance weighting and angular distance weighting methods produced the best results. Performance of all methods was poorer prior to 1995 because of fewer stations and available data. The performance of the interpolation varies for different seasons for almost all variables. Forecasting capability was tested for precipitation only and performed adequately for the system state (wet or dry). Variations in the interpolation schemes across river basins are primarily attributed to differences in gauge or station network density. This freely available gridded meteorological data set significantly advances the availability of climate data in Brazil.

Proliferation of evapotranspiration (ET) products warrants comparison of these products. The study objective was to assess uncertainty in ET output from four land surface models (LSMs), Noah, Mosaic, VIC, and SAC in NLDAS-2, two remote sensing-based products, MODIS and AVHRR, and GRACE-inferred ET from a water budget with precipitation from PRISM, monitored runoff, and total water storage change (TWSC) from GRACE satellites. The three cornered hat method, which does not require a priori knowledge of the true ET value, was used to estimate ET uncertainties. In addition, TWSC or total water storage anomaly (TWSA) from GRACE was compared with water budget estimates of TWSC from a flux-based approach or TWSA from a storage-based approach. The analyses were conducted using data from three regions (humid-arid) in the South Central United States as case studies. Uncertainties in ET are lowest in LSM ET (∼5 mm/mo), moderate in MODIS or AVHRR-based ET (10–15 mm/mo), and highest in GRACE-inferred ET (20–30 mm/month). There is a trade-off between spatial resolution and uncertainty, with lower uncertainty in the coarser-resolution LSM ET (∼14 km) relative to higher uncertainty in the finer-resolution (∼1–8 km) RS ET. Root-mean-square (RMS) of uncertainties in water budget estimates of TWSC is about half of RMS of uncertainties in GRACE-derived TWSC for each of the regions. Future ET estimation should consider a hybrid approach that integrates strengths of LSMs and satellite-based products to constrain uncertainties.

Abstract Recent developments in mascon (mass concentration) solutions for GRACE (Gravity Recovery and Climate Experiment) satellite data have significantly increased the spatial localization and amplitude of recovered terrestrial Total Water Storage anomalies (TWSA); however, land hydrology applications have been limited. Here we compare TWSA from April 2002 through March 2015 from (1) newly released GRACE mascons from the Center for Space Research (CSR‐M) with (2) NASA JPL mascons (JPL‐M), and with (3) CSR Tellus gridded spherical harmonics rescaled (sf) (CSRT‐GSH.sf) in 176 river basins, ∼60% of the global land area. Time series in TWSA mascons (CSR‐M and JPL‐M) and spherical harmonics are highly correlated (rank correlation coefficients mostly >0.9). The signal from long‐term trends (up to ±20 mm/yr) is much less than that from seasonal amplitudes (up to 250 mm). Net long‐term trends, summed over all 176 basins, are similar for CSR and JPL mascons (66–69 km 3 /yr) but are lower for spherical harmonics (∼14 km 3 /yr). Long‐term TWSA declines are found mostly in irrigated basins (−41 to −69 km 3 /yr). Seasonal amplitudes agree among GRACE solutions, increasing confidence in GRACE‐based seasonal fluctuations. Rescaling spherical harmonics significantly increases agreement with mascons for seasonal fluctuations, but less for long‐term trends. Mascons provide advantages relative to spherical harmonics, including (1) reduced leakage from land to ocean increasing signal amplitude, and (2) application of geophysical data constraints during processing with little empirical postprocessing requirements, making it easier for nongeodetic users. Results of this product intercomparison should allow hydrologists to better select suitable GRACE solutions for hydrologic applications.