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USGS2014

Groundwater-flow and land-subsidence model of Antelope Valley, California

Antelope Valley, California, is a topographically closed basin in the western part of the Mojave Desert, about 50 miles northeast of Los Angeles. The Antelope Valley groundwater basin is about 940 square miles and is separated from the northern part of Antelope Valley by faults and low-lying hills. Prior to 1972, groundwater provided more than 90 percent of the total water supply in the valley; since 1972, it has provided between 50 and 90 percent. Most groundwater pumping in the valley occurs in the Antelope Valley groundwater basin, which includes the rapidly growing cities of Lancaster and Palmdale. Groundwater-level declines of more than 270 feet in some parts of the groundwater basin have resulted in an increase in pumping lifts, reduced well efficiency, and land subsidence of more than 6 feet in some areas. Future urban growth and limits on the supply of imported water may increase reliance on groundwater. In 2011, the Los Angeles County Superior Court of California ruled that the Antelope Valley groundwater basin is in overdraft—groundwater extractions are in excess of the Court-defined safe yield of the groundwater basin. The Court determined that the safe yield of the adjudicated area of the basin was 110,000 acre-feet per year (acre-ft/yr). Natural recharge is an important component of total groundwater recharge in Antelope Valley; however, the exact quantity and distribution of natural recharge, primarily in the form of mountain-front recharge, is uncertain, with total estimates ranging from 30,000 to 160,000 acre-ft/yr. Technical experts, retained by parties to the adjudication, used 60,000 acre-ft/yr to estimate the sustainable yield of the basin, and this value was used in this study. In order to better understand the uncertainty associated with natural recharge and to provide a tool to aid in groundwater management, a numerical model of groundwater flow and land subsidence in the Antelope Valley groundwater basin was developed using old and new geohydrologic information. The groundwater-flow system consists of three aquifers: the upper, middle, and lower aquifers. The three aquifers, which were identified on the basis of the hydrologic properties, age, and depth of the unconsolidated deposits, consist of gravel, sand, silt, and clay alluvial deposits and clay and silty clay lacustrine deposits. Prior to groundwater development in the valley, recharge was primarily the infiltration of runoff from the surrounding mountains. Groundwater flowed from the recharge areas to discharge areas around the playas where it discharged from the aquifer system as either evapotranspiration or from springs. Partial barriers to horizontal groundwater flow, such as faults, have been identified in the groundwater basin. Water-level declines owing to groundwater development have eliminated the natural sources of discharge, and pumping for agricultural and urban uses have become the primary source of discharge from the groundwater system. Infiltration of return flow from agricultural irrigation has become an important source of recharge to the aquifer system. The groundwater-flow model of the basin was discretized horizontally into a grid of 130 rows and 118 columns of square cells 1 kilometer (0.621 mile) on a side, and vertically into four layers representing the upper (two layers), middle (one layer), and lower (one layer) aquifers. Faults that were thought to act as horizontal-flow barriers were simulated in the model. The model was calibrated to simulate steady-state conditions, represented by 1915 water levels and transient-state conditions during 1915–95, by using water-level and subsidence data. Initial estimates of the aquifer-system properties and stresses were obtained from a previously published numerical model of the Antelope Valley groundwater basin; estimates also were obtained from recently collected hydrologic data and from results of simulations of groundwater-flow and land-subsidence models of the Edwards Air Force Base area. Some of these initial estimates were modified during model calibration. Groundwater pumpage for agriculture was estimated on the basis of irrigated crop acreage and crop consumptive-use data. Pumpage for public supply, which is metered, was compiled and entered into a database used for this study. Estimated annual agricultural pumpage peaked at 395,000 acre-feet (acre-ft) in 1951 and then declined because of declining agricultural production. Recharge from irrigation return flows was assumed to be 30 percent of agricultural pumpage; delays associated with return flow moving through the unsaturated zone were also simulated. The annual quantity of mountain-front recharge initially was based on estimates from previous studies. The model was calibrated using the PEST software suite; prior information from the area was incorporated through the use of Tikhonov regularization. During model calibration, the estimated mountain-front recharge was reduced from the previous estimate of 30,300 acre-ft/yr to 29,150 acre-ft/yr. Results of the simulations using the calibrated model indicate that simulated groundwater pumpage exceeded recharge in most years, resulting in an estimated cumulative depletion in groundwater storage of 8,700,000 acre-ft during the transient-simulation period (1915–2005). About 15,000,000 acre-ft of cumulative groundwater pumpage was simulated during the transient-simulation period (1915–2005), reaching a maximum rate of about 400,000 acre-ft/yr in 1951. Groundwater pumpage resulted in simulated hydraulic heads declining by more than 150 feet (ft) compared to 1915 conditions in agricultural areas. The decline in hydraulic head in the groundwater basin is the result of this depletion of groundwater storage. In turn, the simulated decline in hydraulic head in the groundwater basin has resulted in the decrease in natural discharge from the basin and has caused compaction of aquitards, resulting in land subsidence. The areal distribution of total simulated land subsidence for 2005, after about 90 years of groundwater development, indicates that land subsidence occurred throughout almost the entire Lancaster subbasin, with a maximum of about 9.4 ft in the central and eastern parts of the subbasin. An important objective of this study was to systematically address the uncertainty in estimates of natural recharge and related aquifer parameters by using the groundwater-flow and land-subsidence model with observational data and expert knowledge. After the model was calibrated to the observations and a reasonable parameter set obtained, the parameter null space—parameter values that do not appreciably affect the model calibration but may have importance for prediction—was identified. The effect of parameter uncertainty on the estimation of mountain-front recharge was addressed using the Null-Space Monte Carlo method. The Pareto trade-off method of visualizing uncertainty was also used to portray the reasonableness of larger natural-recharge rates. Results indicate that the total mountain-front recharge likely ranges between 28,000 and 44,000 acre-ft/yr, which is appreciably less than published estimates of 60,000 acre-ft/yr. Additionally, expected errors associated with agricultural pumpage estimates used in this study were found to have relatively little effect on the estimates of mountain-front recharge, reflecting the difficulty in increasing recharge through manipulation of other components of the water budget. The calibrated model was used to simulate the response of the aquifer to potential future pumping scenarios: (1) no change in the distribution of pumpage, or status quo; (2) redistribution of pumpage; and (3) artificial recharge. All three of these scenarios specify a total pumpage throughout the Antelope Valley of 110,000 acre-ft/yr according to the safe yield value ruled by the Los Angeles County Superior Court of California. This reduction in groundwater pumpage is assumed uniform throughout the basin, based on a 10-percent reduction of the total pumpage in 2005 to achieve the 110,000 acre-ft/yr level. The calibrated Antelope Valley groundwater-flow and land-subsidence model was used to simulate the hydrologic effects of the three groundwater-management scenarios during a 50-year period by using the reduced, temporally constant, pumpage distribution. Results from the first scenario indicated that the total drawdown observed since predevelopment would continue, with values exceeding 325 ft near Palmdale; consequently, land subsidence would also continue, with additional subsidence (since 2005) exceeding 3 ft in the central part of the Lancaster subbasin. The second scenario evaluated redistributing pumpage from areas in the Lancaster subbasin where simulated hydraulic-head declines were the greatest to areas where declines were smallest. Neither a formal optimization algorithm nor water-rights allocations were considered when redistributing the pumpage. Results indicated that hydraulic heads near Palmdale, where the pumpage was reduced, would recover by about 200 ft compared to 2005 conditions, with only 30 ft of additional drawdown in the northwestern part of the Lancaster subbasin, where the pumpage was increased. The magnitude of the simulated additional land subsidence decreased slightly compared to the first, status quo, scenario but land subsidence continued to be simulated throughout most of the northern part of the Lancaster subbasin. The third scenario consisted of two artificial-recharge simulations along the Upper Amargosa Creek channel and at a site located north of Antelope Buttes. Results indicate that applying artificial recharge at these sites would yield continued drawdowns and associated land subsidence. However, the magnitudes of drawdown and subsidence would be smaller than those simulated in the status quo scenario, indicating that artificial-recharge operations in the Antelope Valley could be expected to reduce the magnitude and extent of continued water-level declines and associated land subsidence.

California↗

USGS2018

Land subsidence along the California Aqueduct in west-central San Joaquin Valley, California, 2003–10

Extensive groundwater withdrawal from the unconsolidated deposits in the San Joaquin Valley caused widespread aquifer-system compaction and resultant land subsidence from 1926 to 1970—locally exceeding 8.5 meters. The importation of surface water beginning in the early 1950s through the Delta-Mendota Canal and in the early 1970s through the California Aqueduct resulted in decreased groundwater pumping, recovery of water levels, and a reduced rate of compaction in some areas of the San Joaquin Valley. However, drought conditions during 1976–77, 1987–92, and drought conditions and operational reductions in surface-water deliveries during 2007–10 decreased surface-water availability, causing pumping to increase, water levels to decline, and renewed compaction. Land subsidence from this compaction has reduced freeboard and flow capacity of the California Aqueduct, Delta-Mendota Canal, and other canals that deliver irrigation water and transport floodwater. The U.S. Geological Survey, in cooperation with the California Department of Water Resources, assessed more recent land subsidence near a 145-kilometer reach of the California Aqueduct in the west-central part of the San Joaquin Valley as part of an effort to minimize future subsidence-related damages to the California Aqueduct. The location, magnitude, and stress regime of land-surface deformation during 2003–10 were determined by using data and analyses associated with extensometers, Global Positioning System surveys, Interferometric Synthetic Aperture Radar, spirit-leveling surveys, and groundwater wells. Comparison of continuous Global Positioning System, shallow-extensometer, and groundwater-level data indicated that most of the compaction in this area took place beneath the Corcoran Clay, the primary regional confining unit. The integration of measurements strengthens confidence in individual measurement methods and provides the information at spatial and temporal scales that water managers need to design and implement groundwater sustainability plans in compliance with California’s Sustainable Groundwater Management Act. Measurements of land-surface deformation during 2003–10 indicated that the parts of the California Aqueduct closest to the Coast Ranges in the west-central part of the San Joaquin Valley were fairly stable or minimally subsiding on an annual basis; some areas show seasonal periods of subsidence and uplift that resulted in little or no longer-term elevation loss. Many groundwater levels in these areas did not reach historical lows during 2003–10, indicating that deformation nearest the Coast Ranges was likely primarily elastic. Land-surface deformation measurements indicated that some parts of the California Aqueduct that traverse farther from the Coast Ranges toward the valley center subsided. Some parts of the California Aqueduct subsided locally, but generally the California Aqueduct is within part of a 12,000-square-kilometer area affected by 25 millimeters or more of subsidence during 2008–10, with maxima in Madera County, south of the town of El Nido near the San Joaquin River and the Eastside Bypass (540 millimeters), and in Tulare County, west of the town of Pixley (345 millimeters). Interferometric Synthetic Aperture Radar-derived subsidence maps for various periods during 2003–10 show that the area of maximum active subsidence (that is, the largest rates of subsidence) shifted from its historical (1926–70) location southwest of the town of Mendota to these areas nearer the valley center. Calculations indicated that the subsidence rate doubled in 2008 in parts of the study area. Water levels declined during 2007–10 in many shallow and deep wells in the most rapidly subsiding areas, where water levels in many deep wells reached their historical lows, indicating that subsidence measured during this period was largely inelastic. Continued groundwater-level and land-subsidence monitoring in the San Joaquin Valley is important because (1) operational- and drought-related reductions in surface-water deliveries since 1976 have resulted in increased groundwater pumping and associated water-level declines and land subsidence, (2) land use and associated pumping continue to change throughout the valley, and (3) subsidence management is stipulated in the Sustainable Groundwater Management Act. The availability of surface water remains uncertain; even during record-setting precipitation years, such as 2010–11, water deliveries fell short of requests and groundwater pumping was required to meet the irrigation demand. In some areas, the infrastructure is not available to supply surface water, and groundwater is the only source of water. Because of the expected continued demand for water and the limitations and uncertainty of surface-water supplies, groundwater pumping and associated land subsidence remains a concern. Spatially detailed information on land subsidence is needed to minimize future subsidence-related damages to the California Aqueduct and other infrastructure in the San Joaquin Valley, as well as alterations to natural resources such as stream gradients, water depths, and water temperatures. The integration of data on land-surface elevation, subsurface deformation, and water levels—particularly continuous measurements—enables the analysis of aquifer-system response to groundwater pumping, which in turn, enables estimation of the preconsolidation head and calculation of aquifer-system storage properties. This information can be used to improve numerical model simulations of groundwater flow and aquifer-system compaction and allow for consideration of land subsidence in the evaluation of water resource management alternatives and compliance with the Sustainable Groundwater Management Act.

California↗

USGS2024

Federal lands greenhouse gas emissions and sequestration in the United States: Estimates for 2005–22

In 2016, the Secretary of the U.S. Department of the Interior requested that the U.S. Geological Survey (USGS) produce a publicly available and annually updated database of estimated greenhouse gas emissions associated with the extraction and use of fossil fuels from Federal lands. The first report in this series included emissions estimates from 2005 to 2014 and were reported for 29 States and two offshore areas. Native American and Tribal lands were not included in that analysis. This report recalculates those previous years (2005–14) with updated data and methods and extends the estimates to 2022. Nationwide emissions from fossil fuels produced on Federal lands in 2022 were 1,081.2 million metric tons of carbon dioxide equivalent (MMT CO 2 Eq.) for CO 2 , 33.4 MMT CO 2 Eq. for methane (CH 4 ), and 4.3 MMT CO 2 Eq. for nitrous oxide (N 2 O). Compared to 2005, the 2022 totals represent decreases in emissions for all three greenhouse gases (by 17 percent for CO 2 , 37 percent for CH 4 , and 30 percent for N 2 O). Emissions from fossil fuels produced on Federal lands represent, on average, 21.8 percent of U.S. emissions for CO 2 , 6.1 percent for CH 4 , and 1.3 percent for N 2 O over the 18 years included in this estimate. The trends and relative magnitudes of the greenhouse gas emissions estimated are roughly parallel to the Federal lands fossil fuel production volumes. In 2021, Federal lands of the conterminous United States stored 70,424 MMT CO 2 Eq. in terrestrial ecosystems. Soils stored most of the terrestrial ecosystem carbon (66 percent), followed by live vegetation (25 percent), deadwood (5 percent), and litter (4 percent). Carbon sequestration on Federal lands was highly variable over time, owing primarily to interannual variability in climate and weather, and variability in land use and land cover (LULC) change and disturbances, among these are wildfires and logging. Between 2005 and 2021, Federal lands sequestered an average of 83 MMT CO 2 Eq./yr. By subtracting the cumulative effects of LULC and disturbance-related CO 2 losses to the atmosphere from the total, we estimate that ecosystems at the national level sequestered CO 2 at an annual mean rate of 17 MMT CO 2 Eq./yr in a term called the net ecosystem exchange (NEE). This annual NEE sequestration value represents about 1.4 percent of average fossil fuel emissions over the same period. The USGS estimates presented in this report represent an accounting for the emissions resulting from fossil fuel extraction on Federal lands and the end-use combustion of those fuels, as well as for the sequestration of carbon in terrestrial ecosystems on Federal lands. A combined net CO 2 emissions estimate, which is the difference between the emitted and sequestered CO 2 from both the fossil fuel and ecosystems estimates, provides context for evaluating the greenhouse gas contributions of activities on these lands. The estimates included in this report can provide context for future energy decisions, as well as a basis to track change in the future.

Scientific Investigations Report↗

USGS2026

Colocating artificial intelligence data centers with energy infrastructure on Federal public lands—A science synthesis and spatial analysis to inform decision making

Executive Summary Artificial intelligence (AI) is rapidly transforming industries and economies, creating an urgent need to strategically plan for the energy and infrastructure required to support increasing AI use. U.S. Federal agencies and bureaus have been directed to explore ways to accelerate permitting, development, and deployment of energy resources and AI technologies, including encouraging the colocation of energy infrastructure and data centers. To inform these initiatives, this report synthesizes relevant scientific information and presents a spatial analysis of existing energy infrastructure and data centers on or near U.S. Federal public lands managed by the Bureau of Land Management (BLM). The purpose of this science synthesis and spatial analysis is to provide the BLM with foundational information for considering potential colocation of data centers with energy infrastructure on Federal public lands to support evidence-based decisions. Additionally, this report provides insight into current (2025) and potential future energy demands by providing projections of a range of potential future environmental conditions relevant to maintaining industry-recommended cooling temperature standards necessary for efficient data center operations. As a part of this effort, a rapid response literature review was conducted of the best available science on the topic of data center development and energy infrastructure in July–August 2025, supplemented by additional resources recommended by U.S. Federal agency and bureau subject matter experts (hereafter experts; including the U.S. Department of Energy National Laboratory of the Rockies) and peer reviewers. To better understand current conditions relevant to AI data center development, a spatial analysis was conducted across Alaska and 11 States in the Western United States, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming, all of which contain extensive BLM-managed surface lands (hereafter referred to as “BLM lands”) that could be considered for the colocation of energy infrastructure and AI data centers. This effort identified BLM lands within 10 miles of existing transmission lines, consistent with methods used in previous BLM programmatic environmental impact statements. This report describes the types of data centers operating within the United States, which vary in ownership, size, technology, and proximity to end users. This report then outlines the primary considerations of data center development, including reliable energy supply, natural resources (such as water availability to support cooling requirements), and relevant policy and regulatory considerations. Energy supply considerations are pivotal for data center operation. Between 2014 and 2018, data centers in the United States accounted for nearly 2 percent of the Nation’s total electricity consumption, and data center energy consumption is projected to increase from 2 to 6.7–12 percent of total U.S. electricity use by 2028. These energy requirements necessitate careful consideration of energy supply when considering potentially suitable locations for data center development. Experts anticipate that an increase in renewable energy generation will likely support most potential future power demand needs, including for data centers, followed by increases in natural gas, nuclear, and geothermal energy production. Additional capacity in the form of battery storage will likely not generate electricity, but may improve the reliability and flexibility of supply, helping to ensure that growing data center loads can be met. However, the U.S. Department of Energy estimates that the United States will need, on average, 57 percent more energy transmission infrastructure by 2035 to account for the growing power demand introduced by development such as data centers. Cooling server equipment in data centers requires large amounts of electricity and water, and this demand can be exacerbated by hot and humid conditions. Energy efficient water-based cooling technologies may reduce electricity consumption onsite but require more water consumption. This additional water demand has the potential to increase water stress and competition with other users. As such, developing data centers will likely need a thorough assessment of current and potential future water availability, as well as consideration of how water demand may change across other sectors. Data center development involves policy and regulatory considerations, as projects must undergo environmental review and authorization processes that can take 18–24 months. Coordinating these environmental reviews and authorizations with other energy development projects, such as building new transmission lines, may cause additional delays. Recent efforts by the U.S. Department of Energy and U.S. Department of the Interior aim to expedite environmental reviews and authorizations and improve coordination across agencies. The spatial analysis identified 771 existing AI data centers and more than 3,300 power plants. The spatial analysis found that 6 percent of AI data centers and 22 percent of power plants in the Western United States were on or within 1 mile of BLM lands, and California had the largest number of facilities. Most existing AI data centers were near high-voltage transmission lines and close to power plants, supporting efficient energy delivery. More than 90,000,000 acres of BLM lands were within 10 miles of existing high-voltage transmission lines, representing 38 percent of BLM lands in the study area. Available transmission infrastructure and the overlap with BLM lands varied by State, and Alaska had limited overlap compared to the rest of the Western United States. To operate most efficiently, data center temperatures must be at or below 80.6 degrees Fahrenheit. This analysis of future temperature and precipitation projections indicated increasing cooling demands for data centers, particularly in Arizona, California, and Nevada, where rising temperatures are expected to increase energy and operational costs while potentially stressing current regional electrical grid infrastructure. This report highlights relevant energy supply, natural resources, and regulatory considerations for data center development on BLM lands. This report does not provide a comprehensive ecological, regulatory, land suitability, or permitting analysis. The factors described here are contextual considerations only and are not intended to identify, rank, quantify, or recommend optimal areas for data center colocation. This spatial analysis focused solely on energy considerations relevant to data centers and did not consider water availability, critical habitats, BLM National Conservation Lands, areas of cultural or historical significance, and other sensitive resources. These topics are recognized as critical but were not within the scope of this science synthesis and spatial analysis.

Scientific Investigations Report↗

USGS1998

Regional characterization of land cover using multiple sources of data

Many organizations require accurate intermediate-scale land-cover information for many applications, including modeling nutrient and pesticide runoff, understanding spatial patterns of biodiversity, land-use planning, and policy development. While many techniques have been successfully used to classify land cover in relatively small regions, there are substantial obstacles in applying these methods to large, multiscene regions. The purpose of this study was to generate and evaluate a large region land-cover classification product using a multiple-layer land-characteristics database approach. To derive land-cover information, mosaicked Landsat thematic mapper (TM) scenes were analyzed in conjunction with digital elevation data (and derived slope, aspect, and shaded relief), population census information, Defense Meteorological Satellite Program city lights data, prior land-use and land-cover data, digital line graph data, and National Wetlands Inventory data. Both leaf-on and leaf-off TM data sets were analyzed. The study area was U.S. Federal Region III, which includes the states of Pennsylvania, Virginia, Maryland, Delaware, and West Virginia. The general procedure involved (1) generating mosaics of multiple scenes of leaves-on TM data using histogram equalization methods; (2) clustering mosaics into 100 spectral classes using unsupervised classification; (3) interpreting and labeling spectral classes into approximately 15 land-cover categories (analogous to Anderson Level 1 and 2 classes) using aerial photographs; (4) developing decision-making rules and models using from one to several ancillary data layers to resolve confusion in spectral classes that represented two or more targeted land-cover categories; and (5) incorporating data from other sources (for example, leaf-off TM data and National Wetlands Inventory data) to yield a final land-cover product. Although standard accuracy assessments were not done, a series of consistency checks using available sources of land-cover information were conducted to evaluate the effectiveness of this approach for generating accurate land-cover information for large regions.

Photogrammetric Engineering and Remote Sensing↗

USGS2007

The FORE-SCE model: a practical approach for projecting land cover change using scenario-based modeling

A wide variety of ecological applications require spatially explicit, historic, current, and projected land use and land cover data. The U.S. Land Cover Trends project is analyzing contemporary (1973–2000) land-cover change in the conterminous United States. The newly developed FORE-SCE model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land cover change through 2020 for multiple plausible scenarios. Projected proportions of future land use were initially developed, and then sited on the lands with the highest potential for supporting that land use and land cover using a statistically based stochastic allocation procedure. Three scenarios of 2020 land cover were mapped for the western Great Plains in the US. The model provided realistic, high-resolution, scenario-based land-cover products suitable for multiple applications, including studies of climate and weather variability, carbon dynamics, and regional hydrology.

Journal of Land Use Science↗

USGS2014

Land-use threats and protected areas: a scenario-based, landscape level approach

Anthropogenic land use will likely present a greater challenge to biodiversity than climate change this century in the Pacific Northwest, USA. Even if species are equipped with the adaptive capacity to migrate in the face of a changing climate, they will likely encounter a human-dominated landscape as a major dispersal obstacle. Our goal was to identify, at the ecoregion-level, protected areas in close proximity to lands with a higher likelihood of future land-use conversion. Using a state-and-transition simulation model, we modeled spatially explicit (1 km 2 ) land use from 2000 to 2100 under seven alternative land-use and emission scenarios for ecoregions in the Pacific Northwest. We analyzed scenario-based land-use conversion threats from logging, agriculture, and development near existing protected areas. A conversion threat index (CTI) was created to identify ecoregions with highest projected land-use conversion potential within closest proximity to existing protected areas. Our analysis indicated nearly 22% of land area in the Coast Range, over 16% of land area in the Puget Lowland, and nearly 11% of the Cascades had very high CTI values. Broader regional-scale land-use change is projected to impact nearly 40% of the Coast Range, 30% of the Puget Lowland, and 24% of the Cascades (i.e., two highest CTI classes). A landscape level, scenario-based approach to modeling future land use helps identify ecoregions with existing protected areas at greater risk from regional land-use threats and can help prioritize future conservation efforts.

Pacific Northwest↗

USGS2018

Sensitivity of streamflow simulation in the Delaware River Basin to forecasted land‐cover change for 2030 and 2060

In order to simulate the potential effect of forecasted land‐cover change on streamflow and water availability, there has to be confidence that the hydrologic model used is sensitive to small changes in land cover (<10%) and that this land‐cover change exceeds the inherent uncertainty in forecasted conditions. To investigate this, a 26‐year streamflow record was simulated for 33 basins (54–928 km 2 ) in the Delaware River Basin using three dates of land cover: the 2011 National Land‐Cover Dataset (Homer, Fry, & Barnes, 2012 ), 2030 land‐cover conditions representing median values from 101 equally‐likely forecasts, and 2060 land‐cover conditions corresponding to the same iterations used to represent 2030. Streamflow was simulated using a process‐based hydrologic model that includes both pervious and impervious methods as parameterized by three land‐cover‐based hydrologic response units (HRUs)—forested, agricultural, and developed land. Small, but significant differences in streamflow magnitude, variability, and seasonality were seen among the three time periods—2011, 2030, and 2060. Temporal differences were discernible from the range of conditions simulated with 101 equally likely forecasts for 2030. Development was co‐located with the most frequent landscape components, as characterized by topographic wetness index, resulting in a change in hydrology for each HRU, highlighting that knowing the location of disturbance is key to understanding potential streamflow changes. These results show that streamflow simulation using regional calibration that incorporates land‐cover‐based HRUs can be sensitive to relatively small changes in land‐cover and that temporal trends resulting from land‐cover change can be isolated in order to evaluate other changes that might affect water resources.

Delaware River Basin↗

USGS2014

Potential future land use threats to California's protected areas

Increasing pressures from land use coupled with future changes in climate will present unique challenges for California’s protected areas. We assessed the potential for future land use conversion on land surrounding existing protected areas in California’s twelve ecoregions, utilizing annual, spatially explicit (250 m) scenario projections of land use for 2006–2100 based on the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios to examine future changes in development, agriculture, and logging. We calculated a conversion threat index (CTI) for each unprotected pixel, combining land use conversion potential with proximity to protected area boundaries, in order to identify ecoregions and protected areas at greatest potential risk of proximal land conversion. Our results indicate that California’s Coast Range ecoregion had the highest CTI with competition for extractive logging placing the greatest demand on land in close proximity to existing protected areas. For more permanent land use conversions into agriculture and developed uses, our CTI results indicate that protected areas in the Central California Valley and Oak Woodlands are most vulnerable. Overall, the Eastern Cascades, Central California Valley, and Oak Woodlands ecoregions had the lowest areal percent of protected lands and highest conversion threat values. With limited resources and time, rapid, landscape-level analysis of potential land use threats can help quickly identify areas with higher conversion probability of future land use and potential changes to both habitat and potential ecosystem reserves. Given the broad range of future uncertainties, LULC projections are a useful tool allowing land managers to visualize alternative landscape futures, improve planning, and optimize management practices.

California↗

USGS2009

Addressing foundational elements of regional land-use change forecasting

Regional land-use models must address several foundational elements, including understanding geographic setting, establishing regional land-use histories, modeling process and representing drivers of change, representing local land-use patterns, managing issues of scale and complexity, and development of scenarios. Key difficulties include managing an array of biophysical and socioeconomic processes across multiple spatial and temporal scales, and acquiring and utilizing empirical data to support the analysis of those processes. The Southeastern and Pacific Northwest regions of the United States, two heavily forested regions with significant forest industries, are examined in the context of these foundational elements. Geographic setting fundamentally affects both the primary land cover (forest) in the two regions, and the structure and form of land use (forestry). Land-use histories of the regions can be used to parameterize land-use models, validate model performance, and explore land-use scenarios. Drivers of change in the two regions are many and varied, with issues of scale and complexity posing significant challenges. Careful scenario development can be used to simplify process-based land-use models, and can improve our ability to address specific research questions. The successful modeling of land-use change in these two areas requires integration of both top-down and bottom-up drivers of change, using scenario frameworks to both guide and simplify the modeling process. Modular approaches, with utilization and integration of existing process models, allow regional land-use modelers the opportunity to better represent primary drivers of land-use change. However, availability of data to represent driving forces remains a primary obstacle.

Landscape Ecology↗

USGS2026

Aligning legacy NLCD land cover maps based on Landsat Collection 1 to Collection 2

The transition from Landsat Collection 1 to Collection 2 introduced significant improvements in radiometric and geometric accuracy. However, the improvements cause location misalignment between the existing Landsat-derived land cover products and the new collection. The legacy National Land Cover Database (NLCD) has been used as a cornerstone land cover source for a variety of research. Therefore, a method aligning the legacy NLCD product to Collection 2 is required to ensure its continuity and consistency of service. We developed a strategy to not only align legacy NLCD to match new Collection 2 geometric locations but also improve land cover labeling in the region that was affected by the geometric shifts. The method identifies boundary pixels of homogeneous land cover patches as potential problem areas that are likely impacted by geometric shifts and generates candidate labels from 3 × 3 window with the target pixel at the center and segmentation-derived majority label. Standard phenology patterns of each candidate land cover type are established based on the random samples except boundary pixels within a 1000-pixels × 1000-pixels processing window region. The phenological distance to each standard land cover type pattern is calculated through a penalty dynamic time warping (DTW) method for each target pixel in the boundary region. Finally, the method determines the most suitable label based on the phenological distance from the candidate labels. Both visual and accuracy assessment results demonstrate that the alignment preserves the overall land cover patterns in the original legacy NLCD product while reducing the spatial discrepancies between the Landsat Collection 2 and land cover. In addition, it enhances the accuracy of land cover labeling of boundary pixels. The overall accuracy (OA) was increased by 7% in the land cover boundary regions after alignment. The quality and confusion matrix comparison between the alignment results and the original legacy NLCD confirm the reliability of the method. Our alignment method has the potential to serve as a framework for aligning other Landsat-derived land cover products to future collections.

conterminous United States↗

USGS2015

Combining NLCD and MODIS to create a land cover-albedo database for the continental United States

Land surface albedo is an essential climate variable that is tightly linked to land cover, such that specific land cover classes (e.g., deciduous broadleaf forest, cropland) have characteristic albedos. Despite the normative of land-cover class specific albedos, there is considerable variability in albedo within a land cover class. The National Land Cover Database (NLCD) and the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo product were combined to produce a long-term (14 years) integrated land cover-albedo database for the continental United States that can be used to examine the temporal behavior of albedo as a function of land cover. The integration identifies areas of homogeneous land cover at the nominal spatial resolution of the MODIS (MCD43A) albedo product (500 m × 500 m) from the NLCD product (30 m × 30 m), and provides an albedo data record per 500 m × 500 m pixel for 14 of the 16 NLCD land cover classes. Individual homogeneous land cover pixels have up to 605 albedo observations, and 75% of the pixels have at least 319 MODIS albedo observations (≥ 50% of the maximum possible number of observations) for the study period (2000–2013). We demonstrated the utility of the database by conducting a multivariate analysis of variance of albedo for each NLCD land cover class, showing that locational (pixel-to-pixel) and inter-annual variability were significant factors in addition to expected seasonal (intra-annual) and geographic (latitudinal) effects.

Remote Sensing of Environment↗

USGS2022

Monitoring and characterizing multi-decadal variations of urban thermal condition using time-series thermal remote sensing and dynamic land cover data

Urban development and associated land cover and land use change alter the thermal, hydrological, and physical properties of the land surface. Assessments of surface urban heat island (UHI) usually focused on using remote sensing and land cover data to quantify UHI intensity and spatial distribution within a certain period. However, the mechanisms and complex interactions in landscape dynamics and land surface thermal features are still being assessed. In this study, we developed and implemented a novel approach to characterize landscape thermal conditions by focusing on UHI intensity and its spatiotemporal variation using the recently available time series of Landsat land surface temperature and land cover change products. We analyzed land surface temperature changes in urban and surrounding non-urban lands to quantify the UHI intensity and landscape thermal conditions in the Atlanta and Minneapolis metropolitan areas of the United States. Our results revealed that UHI intensities had averages of 3.4 °C and 3.3 °C in the Atlanta and Minneapolis metropolitan areas, respectively. The dominant land cover type in rural areas and urban imperviousness cover determines the UHI intensity. Increasing trends of 0.04 °C/year and 0.01 °C/year in UHI intensity between 1985 and 2018 were found in Atlanta and Minneapolis, respectively. The UHI intensity variations in 1985 and 2018 suggest that the magnitudes and temporal variations of UHI intensity averaged from all urban land cover classes are close to the UHI intensity estimated from the low intensity urban area only while the UHI intensities are more than 2 °C larger in medium to high and high intensity urban areas. The UHI intensities estimated from the maximum temperature that have statistically significant increasing trends suggest that the maximum temperature is a good element for measuring UHI effect. Urban land cover dynamics play an important role in controlling temporal variation of UHI and the UHI hotspots. Our findings support the scientific value of implementing the prototype approach as an objective framework to quantify and monitor UHI intensity at a large geographic extent.

Remote Sensing of Environment↗

USGS2010

Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.

International Journal of Remote Sensing↗

USGS2025

Land application of drill waste: A scope analysis

Drilling fluid waste land application, a process where drilling wastes are spread and tilled into the land surface, has become common in some petroleum-producing states, however, the potential benefits and risks of this practice are not well studied. Drilling fluids can be water- or oil-based and can have high concentrations of total soluble salts and total petroleum hydrocarbons. Comprehensive chemical characterization of these fluids is not well documented in the literature, and the extent of land application is largely unknown. We hypothesized that the land application of drill waste would fluctuate over time due to economic factors. To begin to understand the extent of historical and potential future land application, we analyzed data from over 5,800 drilling fluid land application permits collected by the Oklahoma Corporation Commission for years 2000, 2005, 2010, and 2015–2020. During the years studied, drilling fluid wastes were applied to more than 250,000 acres in Oklahoma, with over 54,000 thousand barrels (Mbbl) of liquids and nearly 21,000 Mbbl of solids applied. Land application is widespread (occurring in 59/77 counties), however recent drilling activity, land availability, and the economics of transportation have created conditions favorable for land application specifically in the Anadarko Basin. Land application can co-occur with sensitive areas, such as important groundwater and surface-water drinking sources and agricultural fields used for subsistence or feed crop production. Our approach for quantifying the extent of land application, along with further chemical characterization studies, can aid operators and land managers who are considering this practice in assessing the associated benefits and risks.

Oklahoma↗

USGS2026

Thematic accuracy assessment of the National Land Cover Database (NLCD2021) for the conterminous United States

The MultiResolution Land Characteristics (MRLC) consortium’s National Land Cover Database (NLCD) was established as an operational, stakeholder-oriented land cover monitoring program with the release of the NLCD2001 database. Both land cover and land cover change data became available with the release of NLCD2006. Here, we report the land cover and land cover change accuracies for NLCD2021, documenting Level II and I accuracies for the 2016, 2019, and 2021 land cover datasets and 2016–2021 land cover change. An additional objective, not addressed in previous NLCD assessments, is the estimation of the total variance of area estimates, where total variance includes sampling variance and variability in reference label assignment. We estimate the total variance of the area estimates for the stable and change classes targeted by the strata used in the sampling design. For the 16 Level II classes, the overall accuracy (OA) was 73% ± 1% when agreement was defined using only the primary reference class label and 89% ± 0.7% when agreement was defined as a match between the map label and either the primary or alternate reference label (± standard error, SE). For the eight Level I classes, the corresponding OA estimates were 81% ± 0.9% and 89% ± 0.7%. Level II and Level I OA tended to be higher for 2016 land cover and lower and more similar for 2019 and 2021 land cover. Land cover change user and producer accuracies (UA and PA) tended to be <50%. When the alternate reference label was included in the definition of agreement, exceptions of high class-specific accuracies (≥75%) were more prevalent for PA than UA. The consistency of reference label interpretations was greater for no-change classes than for change classes. The estimates of the total variance incorporating interpreter variability were often smaller than the standard variance estimates, indicating the possibility that the total variance estimator is highly unstable. Further study is needed to improve the utility of this total variance estimator for practical applications.

conterminous United States↗

USGS2019

Scenarios of climate adaptation potential on protected working lands from management of soils

Management of protected lands may enhance ecosystem services that conservation programs were designed to protect. Practices that build soil organic matter (SOM) on agricultural lands also increase soil water holding capacity, potentially reducing climatic water deficit (CWD), increasing actual evapotranspiration (AET) and increasing groundwater recharge (RCH). We developed nine spatially-explicit land use and conservation scenarios (2001 - 2100) in the LUCAS land use change model to address two questions for California working lands (cropland and rangeland): How does land use change limit opportunities to manage soils for hydrologic climate adaptation benefits? To what extent and where can soil management practices increase climate adaptation on protected working lands? Hydrologic benefits [∑(∆CWD, ∆AET, ∆RCH)] due to soil management were simulated in the Basin Characterization Model (a state-wide water balance model) for two Representative Concentration Pathway 8.5 climate models. LUCAS simulated land conversion and new conservation easements with potential for maximum hydrologic benefits. Climate drove differences in lost potential for water benefits due to urbanization (33.9 - 87.6 m3 x 106) in 2050. Conflict between development pressure and potential hydrologic benefits occurred most in Santa Clara County in the San Francisco Bay Area and Shasta County in Northern Sacramento Valley. Hydrologic benefits on easements were similar in magnitude to losses from development. Water savings from management of California Land Conservation (a.k.a. Williamson) Act contract lands were an order of magnitude greater, totaling over 460 m3 x106 annually in a drier climate by 2050. Few counties provide most benefits because of soil properties, climate and land area protected. The increase in hydrologic benefits varies by agricultural practice and adoption rate, land use type and configuration, and terms of conservation agreements. The effectiveness of programs designed to improve climate adaptation at county to state scales will likely increase by taking this variability into consideration.

California↗

USGS2011

Data compilation and assessment for water resources in Pennsylvania state forest and park lands

As a result of a cooperative study between the U.S. Geological Survey and the Pennsylvania Department of Conservation and Natural Resources (PaDCNR), available electronic data were compiled for Pennsylvania state lands (state forests and parks) to allow PaDCNR to initially determine if data exist to make an objective evaluation of water resources for specific basins. The data compiled included water-quantity and water-quality data and sample locations for benthic macroinvertebrates within state-owned lands (including a 100-meter buffer around each land parcel) in Pennsylvania. In addition, internet links or contacts for geographic information system coverages pertinent to water-resources studies also were compiled. Water-quantity and water-quality data primarily available through January 2007 were compiled and summarized for site types that included streams, lakes, ground-water wells, springs, and precipitation. Data were categorized relative to 35 watershed boundaries defined by the Pennsylvania Department of Environmental Protection for resource-management purposes. The primary sources of continuous water-quantity data for Pennsylvania state lands were the U.S. Geological Survey (USGS) and the National Weather Service (NWS). The USGS has streamflow data for 93 surface-water sites located in state lands; 38 of these sites have continuous-recording data available. As of January 2007, 22 of these 38 streamflow-gaging stations were active; the majority of active gaging stations have over 40 years of continuous record. The USGS database also contains continuous ground-water elevation data for 32 wells in Pennsylvania state lands, 18 of which were active as of January 2007. Sixty-eight active precipitation stations (primarily from the NWS network) are located in state lands. The four sources of available water-quality data for Pennsylvania state lands were the USGS, U.S. Environmental Protection Agency, Pennsylvania Department of Environmental Protection (PaDEP), and the Susquehanna River Basin Commission. The water-quality data, which were primarily collected after 1970, were summarized by categorizing the analytical data for each site into major groups (for example, trace metals, pesticides, major ions, etc.) for each type (streams, lakes, ground-water wells, and springs) of data compiled. The number of samples and number of detections for each analyte within each group also were summarized. A total of 410 stream sites and 205 ground-water wells in state lands had water-quality data from the available data sets, and these sites were well-distributed across the state. A total of 107 lakes and 47 springs in state lands had water-quality data from the available data sets, but these data types were not well-distributed across the state; the majority of water-quality data for lakes was in the western or eastern sections of the state and water-quality data for springs was primarily located in the central part of the Lower Susquehanna River Valley. The most common types of water-quality data collected were major ions, trace elements, and nutrients. Physical parameters, such as water temperature, stream discharge, or water level, typically were collected for most water-quality samples. Given the large database available from PaDEP for benthic macroinvertebrates, along with some data from other agencies, there is very good distribution of benthic-macroinvertebrate data for state lands. Benthic macroinvertebrate samples were collected at 1,077 locations in state lands from 1973 to 2006. Most (980 samples) of the benthic-macroinvertebrate samples were collected by PaDEP as part of the state assessment of stream conditions required by the Clean Water Act. Data compiled in this report can be used for various water-resource issues, such as basin-wide water-budget analysis, studies of ecological or instream flow, or water-quality assessments. The determination of an annual water budget in selected basins is best supported by the availab

Pennsylvania↗