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At least 37 records · Page 2Linked to original sources
USGS2007

Magnesium compounds

Seawater and natural brines accounted for about 52 percent of U.S. magnesium compounds production in 2006. Dead-burned magnesia was produced by Martin Marietta Magnesia Specialties from well brines in Michigan. Caustic-calcined magnesia was recovered from sea-water by Premier Chemicals in Florida; from well brines in Michigan by Martin Marietta and Rohm and Haas; and from magnesite in Nevada by Premier Chemicals. Intrepid Potash-Wendover and Great Salt Lake Minerals recovered magnesium chloride brines from the Great Salt Lake in Utah. Magnesium hydroxide was produced from brucite by Applied Chemical Magnesias in Texas, from seawater by SPI Pharma in Delaware and Premier Chemicals in Florida, and by Martin Marietta and Rohm and Haas from their operations mentioned above. About 59 percent of the magnesium compounds consumed in the United States was used for refractories that are used mainly to line steelmaking furnaces. The remaining 41 percent was consumed in agricultural, chemical, construction, environmental and industrial applications.

Mining Engineering↗
USGS2025

Landsat-derived rainfed and irrigated-area product for conterminous United States for the year 2020 (LRIP30 CONUS 2020) using supervised and unsupervised machine learning on the cloud

Accurate maps of irrigated and rainfed croplands are crucial for assessing global food and water security. Irrigated croplands yield two to four times more grain and biomass than rainfed croplands. To meet rising food demand, the proportion of cropland that is irrigated must be increased globally. Because agriculture uses 80% to 90% of global fresh water, understanding changes in cropland extent, crop type, and irrigation is critical for meeting nutritional needs sustainably. The United States has one of the most productive rainfed and irrigated croplands in the world and is a leading producer and exporter of agricultural crops. Precise maps of irrigated and rainfed croplands in the United States are crucial for assessing the current and the future agricultural production capacity in supporting food security. We developed a 30-m resolution rainfed and irrigated area map for the conterminous United States derived from 2019 to 2021 multi-date Landsat-8 data (LRIP30 CONUS 2020). A total of 96 harmonized spectral bands comprising monthly median value composites of eight bands (blue, green, red, NIR, SWIR1, SWIR2, TIR, and enhanced vegetation index [EVI]) were used. A cropland mask was then applied, and reference data were sourced from various sources. A pixel based supervised random forest classifier, and pixel based unsupervised ISODATA clustering classifier were implemented on Google Earth Engine and the ERDAS Imagine workstation to classify, identify, map, and assess accuracies of irrigated and rainfed cropland areas. The LRIP30 CONUS 2020 product achieved an overall accuracy of 93.9%. The irrigated and rainfed classes had producer's accuracies of 90.2% and 95.7%, respectively, and user's accuracies of 90.8% and 95.4%, respectively. The total net cropland area was estimated at 139.4 million hectares (Mha), of which 94.9 Mha (68%) was classified as rainfed and 44.5 Mha (32%) was classified as irrigated. State level summaries highlight regional differences and their implications for national and global food and water security.

conterminous United States↗
USGS2008

Development, Testing, and Sensitivity and Uncertainty Analyses of a Transport and Reaction Simulation Engine (TaRSE) for Spatially Distributed Modeling of Phosphorus in South Florida Peat Marsh Wetlands

Alterations to the predevelopment delivery of water and nutrients into the Everglades of southern Florida have been occurring for nearly a century. Major regional drainage projects, large-scale agricultural development, and changes to the hydrology of the Kissimmee River-Lake Okeechobee watershed have resulted in substantial phosphorus transport increases by surface waters. Excess phosphorus has accumulated in the soils of northern Everglades marshes to levels that have impaired the natural resources of the region. Regulations now limit the amount of phosphorous that enters the Everglades through an extensive network of water-control structures. This study involved the development and application of water-quality modeling components that may be applied to existing hydrologic models of southern Florida to evaluate the effects of different management scenarios. The result of this work is a spatially distributed water-quality model for phosphorus transport and cycling in wetlands. The model solves the advection-dispersion equation on an unstructured triangular mesh and incorporates a wide range of user-selectable mechanisms for phosphorus uptake and release parameters. In general, the phosphorus model contains transfers between stores; examples of stores that can be included are soil, water column (solutes), pore water, macrophytes, suspended solids (plankton), and biofilm. Examples of transfers are growth, senescence, settling, diffusion, and so forth, described with first order, second order, and Monod types of transformations. Local water depths and velocities are determined from an existing two-dimensional, overland-flow hydrologic model. The South Florida Water Management District Regional Simulation Model was used in this study. The model is applied to three case studies: intact cores of wetland soils with water, outdoor mesocosoms, and a large constructed wetland; namely, Cell 4 of Stormwater Treatment Area 1 West (STA-1W Cell 4). Different levels of complexity in the phosphorus cycling mechanisms were simulated in these case studies using different combinations of phosphorus reaction equations. Changes in water column phosphorus concentrations observed under the controlled conditions of laboratory incubations, and mesocosm studies were reproduced with model simulations. Short-term phosphorus flux rates and changes in phosphorus storages were within the range of values reported in the literature, whereas unknown rate constants were used to calibrate the model output. In STA-1W Cell 4, the dominant mechanism for phosphorus flow and transport is overland flow. Over many life cycles of the biological components, however, soils accrue and become enriched in phosphorus. Inflow total phosphorus concentrations and flow rates for the period between 1995 and 2000 were used to simulate Cell 4 phosphorus removal, outflow concentrations, and soil phosphorus enrichment over time. This full-scale application of the model successfully incorporated parameter values derived from the literature and short-term experiments, and reproduced the observed long-term outflow phosphorus concentrations and increased soil phosphorus storage within the system. A global sensitivity and uncertainty analysis of the model was performed using modern techniques such as a qualitative screening tool (Morris method) and the quantitative, variance-based, Fourier Amplitude Sensitivity Test (FAST) method. These techniques allowed an in-depth exploration of the effect of model complexity and flow velocity on model outputs. Three increasingly complex levels of possible application to southern Florida were studied corresponding to a simple soil pore-water and surface-water system (level 1), the addition of plankton (level 2), and of macrophytes (level 3). In the analysis for each complexity level, three surface-water velocities were considered that each correspond to residence times for the selected area (1-kilometer long) of 2, 10, and 20

Scientific Investigations Report↗
USGS2013

Nitrous oxide emissions from cropland: a procedure for calibrating the DayCent biogeochemical model using inverse modelling

DayCent is a biogeochemical model of intermediate complexity widely used to simulate greenhouse gases (GHG), soil organic carbon and nutrients in crop, grassland, forest and savannah ecosystems. Although this model has been applied to a wide range of ecosystems, it is still typically parameterized through a traditional “trial and error” approach and has not been calibrated using statistical inverse modelling (i.e. algorithmic parameter estimation). The aim of this study is to establish and demonstrate a procedure for calibration of DayCent to improve estimation of GHG emissions. We coupled DayCent with the parameter estimation (PEST) software for inverse modelling. The PEST software can be used for calibration through regularized inversion as well as model sensitivity and uncertainty analysis. The DayCent model was analysed and calibrated using N2O flux data collected over 2 years at the Iowa State University Agronomy and Agricultural Engineering Research Farms, Boone, IA. Crop year 2003 data were used for model calibration and 2004 data were used for validation. The optimization of DayCent model parameters using PEST significantly reduced model residuals relative to the default DayCent parameter values. Parameter estimation improved the model performance by reducing the sum of weighted squared residual difference between measured and modelled outputs by up to 67 %. For the calibration period, simulation with the default model parameter values underestimated mean daily N2O flux by 98 %. After parameter estimation, the model underestimated the mean daily fluxes by 35 %. During the validation period, the calibrated model reduced sum of weighted squared residuals by 20 % relative to the default simulation. Sensitivity analysis performed provides important insights into the model structure providing guidance for model improvement.

Water, Air, & Soil Pollution↗
USGS2014

Water-quality modeling of Klamath Straits Drain recirculation, a Klamath River wetland, and 2011 conditions for the Link River to Keno Dam reach of the Klamath River, Oregon

The upper Klamath River and adjacent Lost River are interconnected basins in south-central Oregon and northern California. Both basins have impaired water quality with Total Maximum Daily Loads (TMDLs) in progress or approved. In cooperation with the Bureau of Reclamation, the U.S. Geological Survey (USGS) and Watercourse Engineering, Inc., have conducted modeling and research to inform management of these basins for multiple purposes, including agriculture, endangered species protection, wildlife refuges, and adjacent and downstream water users. A water-quality and hydrodynamic model (CE-QUAL-W2) of the Link River to Keno Dam reach of the Klamath River for 2006–09 is one of the tools used in this work. The model can simulate stage, flow, water velocity, ice cover, water temperature, specific conductance, suspended sediment, nutrients, organic matter in bed sediment and the water column, three algal groups, three macrophyte groups, dissolved oxygen, and pH. This report documents two model scenarios and a test of the existing model applied to year 2011, which had exceptional water quality. The first scenario examined the water-quality effects of recirculating Klamath Straits Drain flows into the Ady Canal, to conserve water and to decrease flows from the Klamath Straits Drain to the Klamath River. The second scenario explicitly incorporated a 2.73×10 6 m 2 (675 acre) off-channel connected wetland into the CE-QUAL-W2 framework, with the wetland operating from May 1 through October 31. The wetland represented a managed treatment feature to decrease organic matter loads and process nutrients. Finally, the summer of 2011 showed substantially higher dissolved-oxygen concentrations in the Link-Keno reach than in other recent years, so the Link-Keno model (originally developed for 2006–09) was run with 2011 data as a test of model parameters and rates and to develop insights regarding the reasons for the improved water-quality conditions.

Oregon↗
USGS2020

Exploring the potential of ground-penetrating radar (GPR) to measure the extent of chronic disturbance in peatlands: Examples from acid mine drainage and peat fire

Peatlands are accumulations of partially decayed organic soil that cover approximately 3% of Earth’s surface and have been shown to serve essential environmental and ecological functions such as sequestering carbon, purifying water, and providing habitat for organisms. However, peatlands are threatened by pressures from agriculture, urban development, mining, and climate change. Geophysical methods have been used in peatlands to determine peat volume and carbon stocks (e.g., Comas et al., 2017), observe differences in humification and water content (e.g., Ulriksen, 1982), guide engineering projects (e.g., Jol and Smith, 1995), learn about subsurface greenhouse gas dynamics (Wright and Comas, 2016), observe seasonal variations in pore water salinity (Walter et al., 2018), and assess hydrological processes (Hare et al., 2017). Among various geophysical methods, ground penetrating radar (GPR) is arguably the most popular for studying peat properties given the method’s sensitivity to variations in water content and ability to resolve major structural properties within the peat at high spatial resolution. Though less widely applied, frequency-domain analysis of GPR may also yield useful information.

Conference Paper↗
USGS2023

Mapping vegetation index-derived actual evapotranspiration across croplands using the Google Earth Engine platform

Precise knowledge of crop water consumption is essential to better manage agricultural water use, particularly in regions where most countries struggle with increasing water and food insecurity. Approaches such as cloud computing and remote sensing (RS) have facilitated access, process, and visualization of big geospatial data to map and monitor crop water requirements. To find the most reliable Vegetation Index (VI)-based evapotranspiration (ETa) for croplands in drylands, we modeled and mapped ETa using empirical RS methods across the Zayandehrud river basin in Iran for two decades (2000–2019) on the Google Earth Engine platform using the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index 2 (EVI2). Developed ET-VI products in this study comprise three NDVI-based ETa (ET-NDVI*, ET-NDVI* scaled , and ET-NDVI Kc ) and an EVI2-based ETa (ET-EVI2). We (a) applied, for the first time, the ET-NDVI* method to croplands as a crop-independent index and then compared its performance with the ET-EVI2 and crop ET, and (b) assessed the ease and feasibility of the transferability of these methods to other regions. Comparing four ET-VI products showed that annual ET-EVI2 and ET-NDVI* scaled estimations were close. ET-NDVI Kc consistently overestimated ETa. Our findings indicate that ET-EVI2 and ET-NDVI Kc were easy to parametrize and adopt to other regions, while ET-NDVI* and ET-NDVI* scaled are site-dependent and sensitive to image acquisition time. ET-EVI2 performed robustly in arid and semi-arid regions making it a better tool. Future research should further develop and confirm these findings by characterizing the accuracy of VI-based ETa over croplands in drylands by comparing them with available ETa products and examining their performance using crop-specific comparisons.

Remote Sensing↗
USGS2005

Inventory of ground-water resources in the Kabul Basin, Afghanistan

In 2004, the U.S. Geological Survey began working with engineers at the Afghanistan Geological Survey to provide hydrologic training and equipment and to apply these tools to build an inventory of water wells in the Kabul Basin of Afghanistan. An inventory of 148 wells now includes information on well location, depth, and access. Water-level and water-quality measurements have been made at most of these wells. A water-level elevation map has been constructed, and general directions of ground-water flow have been defined. Ground-water flow in the Kabul Basin is primarily through saturated alluvium and other basin-fill sediments. The water-table surface generally mirrors topography, and ground water generally flows in the directions of surface-water discharge. The quality of ground water in the Kabul Basin varies widely. In some areas, ground-water quality is excellent, with low concentrations of dissolved solids and no problematic constituents. In other areas, however, high concentrations of dissolved solids and the presence of some constituents at concentrations deemed harmful to humans and crops render untreated ground water marginal or unsuitable for public supply and/or agricultural use. Of particular concern are elevated concentrations of nitrate, boron, and dissolved solids, and an indication of fecal pollution in some parts of the basin. As Afghanistan emerges from years of conflict, as institutional capacities rejuvenate and grow, and as the need for wise water-management decisions continues, adequate data and a fuller understanding of the ground-water resource in the Kabul Basin will be imperative. The work described in this report represents only a modest beginning in what will be a long-term data-collection and interpretive effort.

Scientific Investigations Report↗
USGS2003

Ground-water use, locations of production wells, and areas irrigated using ground water in 1998, middle Humboldt River basin, north-central Nevada

In 1998, ground water was being pumped from about 420 production wells in the middle Humboldt River Basin for a variety of uses. Principal uses were for agriculture, industry, mining, municipal, and power plant purposes. This report presents a compilation of the number and types of production wells, areas irrigated by ground water, and ground-water use in 14 hydrographic areas of the middle Humboldt River Basin in 1998. Annual pumping records for production wells usually are reported to the Nevada Division of Water Resources. However, operators of irrigation wells are not consistently required to report annual pumpage. Daily power-consumption and pump-discharge rates measured at 20 wells during the 1998 irrigation season and total power use at each well were used to estimate the amount of water, in feet of depth, applied to 20 alfalfa fields. These fields include about 10 percent of the total area, 36,700 acres, irrigated with ground water in the middle Humboldt River Basin. In 1998 an average of 2.0 feet of water was applied to 14 fields irrigated using center-pivot sprinkler systems, and an average of 2.6 feet of water was applied to 6 fields irrigated using wheel-line sprinkler systems. A similar approach was used to estimate the amount of water pumped at three wells using pumps powered by diesel engines. The two fields served by these three wells received 3.9 feet of water by flood irrigation during the 1998 irrigation season. The amount of water applied to the fields irrigated by center-pivot and wheel-line irrigation systems during the 1998 irrigation season was less than what would have been applied during a typical irrigation season because late winter and spring precipitation exceeded long-term monthly averages by as much as four times. As a result, the health of crops was affected by over-saturated soils, and most irrigation wells were only used sporadically in the first part of the irrigation season. Power consumption at 19 of the 20 wells in the 1994-97 irrigation seasons was 110 to 235 percent of the power consumption in the 1998 irrigation season. If the amount of water applied to fields during the 1998 irrigation season were adjusted to account for these differences in power consumption, the average amount of water applied to a field during a typical season using center-pivot and wheel-line sprinkler systems would be 3.1 feet and 3.7 feet, respectively. Total ground water pumped in the middle Humboldt River Basin during 1998 was about 298,000 acre-feet. This pumpage was distributed as follows: 78 percent for mining, 19 percent for irrigation, and 3 percent for industrial, municipal, and power plants combined. Mining pumpage is by far the largest source of ground-water use because several large gold mines have extended below local ground-water levels and the area around each mine must be dewatered in order to maintain a dry and workable mine. Total mining pumpage in 1998 was 233,000 acre-feet, of this total, 23,600 acre-feet was for consumptive use and 209,000 acre-feet was for dewatering eight mines. Excess water from the mines being dewatered was distributed as follows: 74,500 acre-feet was returned to aquifers by infiltration; 33,100 acre-feet was used for irrigation and for consumptive use at two mines and a power plant; 96,700 acre-feet was released to the Humboldt River or one of its tributaries; and 5,260 acre-feet was lost to evaporation.

Water-Resources Investigations Report↗
USGS2026

From landslide susceptibility to risk assessment in the conterminous U.S.

Understanding the spatial distribution of landslide prone-areas and what consequences they may have is important for risk management and land-use planning. In the United States, although landslides occur in every state, a comprehensive landslide risk assessment is still missing. Existing efforts, such as the Federal Emergency Management Agency (FEMA)’s National Risk Index, rely on aggregated products and coarse cartographic units, limiting their geomorphological and practical accuracy. In this study, we present a methodological advance for landslide risk assessment across large areas with incomplete and sparse data. We apply our procedures to the conterminous United States by integrating geomorphologically meaningful partitions and spatial and temporal probability data-driven models. Landslide susceptibility is estimated using a Generalized Additive Mixed Model incorporating a bias capture/correction scheme to account for inventory inaccuracies (reference Area Under the Curve = 0.75). The exceedance probabilities of landslide occurrence are defined for three temporal scenarios (2, 5, and 10 year). Then, we explore the associated potential economic consequences for human settlements and agricultural areas. The findings indicate that the spatial variability of risk is primarily controlled by exposure rather than by susceptibility/hazard alone. The mean risk increases by ∼170% from the 2-year to the 10-year scenario. Beyond its quantitative outcomes, this study offers a blueprint for continental or sub-continental scale landslide risk assessments, demonstrating both the opportunities and current limitations.

Engineering Geology↗
USGS2017

A guide to multi-objective optimization for ecological problems with an application to cackling goose management

Choices in ecological research and management are the result of balancing multiple, often competing, objectives. Multi-objective optimization (MOO) is a formal decision-theoretic framework for solving multiple objective problems. MOO is used extensively in other fields including engineering, economics, and operations research. However, its application for solving ecological problems has been sparse, perhaps due to a lack of widespread understanding. Thus, our objective was to provide an accessible primer on MOO, including a review of methods common in other fields, a review of their application in ecology, and a demonstration to an applied resource management problem. A large class of methods for solving MOO problems can be separated into two strategies: modelling preferences pre-optimization (the a priori strategy), or modelling preferences post-optimization (the a posteriori strategy). The a priori strategy requires describing preferences among objectives without knowledge of how preferences affect the resulting decision. In the a posteriori strategy, the decision maker simultaneously considers a set of solutions (the Pareto optimal set) and makes a choice based on the trade-offs observed in the set. We describe several methods for modelling preferences pre-optimization, including: the bounded objective function method, the lexicographic method, and the weighted-sum method. We discuss modelling preferences post-optimization through examination of the Pareto optimal set. We applied each MOO strategy to the natural resource management problem of selecting a population target for cackling goose ( Branta hutchinsii minima ) abundance. Cackling geese provide food security to Native Alaskan subsistence hunters in the goose's nesting area, but depredate crops on private agricultural fields in wintering areas. We developed objective functions to represent the competing objectives related to the cackling goose population target and identified an optimal solution first using the a priori strategy, and then by examining trade-offs in the Pareto set using the a posteriori strategy. We used four approaches for selecting a final solution within the a posteriori strategy; the most common optimal solution, the most robust optimal solution, and two solutions based on maximizing a restricted portion of the Pareto set. We discuss MOO with respect to natural resource management, but MOO is sufficiently general to cover any ecological problem that contains multiple competing objectives that can be quantified using objective functions.

Ecological Modelling↗
USGS2024

Land-use interactions, Oil-Field infrastructure, and natural processes control hydrocarbon and arsenic concentrations in groundwater, Poso Creek Oil Field, California, USA

Like many hydrocarbon production areas in the U.S., the Poso Creek Oil Field in California includes and is adjacent to other land uses (agricultural and other developed lands) that affect the hydrology and geochemistry of the aquifer overlying and adjacent to oil development. We hypothesize that the distributions of hydrocarbons and arsenic in groundwater in such areas will be controlled by complex interactions between mixed land uses, oil-field infrastructure, and natural processes. In 2020–2021, samples of groundwater and surface water were collected and analyzed for a large suite of inorganic and organic chemicals and isotope and gas tracers to test this hypothesis. Those data are supplemented with ancillary data on historical geochemistry, hydrology, geology, and oil-field infrastructure. Hydrocarbons in groundwater (e.g., methane through pentane gases and benzene) are associated with natural processes (e.g., fault offsets or transition in sediment depositional environment) and oil-field infrastructure (e.g., fluid-migration pathways associated with uncemented annulus in oil wells or unlined pits). Arsenic concentrations >10 μg per liter (μg/L; maximum concentration 12.9 μg/L) are associated with natural processes in old, high-pH groundwater, and more recent recharge of water from natural and/or engineered recharge processes. Along the southwest margin of the oil field, pumping for drinking-water and irrigation supplies in combination with engineered groundwater recharge produce a depression in groundwater elevations where groundwater with elevated sulfate concentrations from agricultural areas and groundwater with hydrocarbons from the oil field mix to produce a zone of sulfate reduction that removes hydrocarbons and arsenic from groundwater but produces elevated sulfide (S 2- ) concentrations (maximum concentration 29 mg per liter, mg/L). In this study, multiple approaches were required to resolve the overlapping effects of land uses, oil-field infrastructure, and natural processes on the distributions of hydrocarbons and arsenic in groundwater. The combined use of geographic, historical, physical, chemical, isotopic, and other information to constrain processes could be a useful approach for studies in other hydrocarbon-production areas. This is particularly important where land uses affect aquifer hydrology to an extent that causes mixing of groundwaters with different chemical compositions.

California↗
USGS2003

Use of multispectral Ikonos imagery for discriminating between conventional and conservation agricultural tillage practices

There is a global concern about the increase in atmospheric concentrations of greenhouse gases. One method being discussed to encourage greenhouse gas mitigation efforts is based on a trading system whereby carbon emitters can buy effective mitigation efforts from farmers implementing conservation tillage practices. These practices sequester carbon from the atmosphere, and such a trading system would require a low-cost and accurate method of verification. Remote sensing technology can offer such a verification technique. This paper is focused on the use of standard image processing procedures applied to a multispectral Ikonos image, to determine whether it is possible to validate that farmers have complied with agreements to implement conservation tillage practices. A principal component analysis (PCA) was performed in order to isolate image variance in cropped fields. Analyses of variance (ANOVA) statistical procedures were used to evaluate the capability of each Ikonos band and each principal component to discriminate between conventional and conservation tillage practices. A logistic regression model was implemented on the principal component most effective in discriminating between conventional and conservation tillage, in order to produce a map of the probability of conventional tillage. The Ikonos imagery, in combination with ground-reference information, proved to be a useful tool for verification of conservation tillage practices.

Photogrammetric Engineering and Remote Sensing↗
USGS2011

Compilation of watershed models for tributaries to the Great Lakes, United States, as of 2010, and identification of watersheds for future modeling for the Great Lakes Restoration Initiative

As part of the Great Lakes Restoration Initiative (GLRI) during 2009–10, the U.S. Geological Survey (USGS) compiled a list of existing watershed models that had been created for tributaries within the United States that drain to the Great Lakes. Established Federal programs that are overseen by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corps of Engineers (USACE) are responsible for most of the existing watershed models for specific tributaries. The NOAA Great Lakes Environmental Research Laboratory (GLERL) uses the Large Basin Runoff Model to provide data for the management of water levels in the Great Lakes by estimating United States and Canadian inflows to the Great Lakes from 121 large watersheds. GLERL also simulates streamflows in 34 U.S. watersheds by a grid-based model, the Distributed Large Basin Runoff Model. The NOAA National Weather Service uses the Sacramento Soil Moisture Accounting model to predict flows at river forecast sites. The USACE created or funded the creation of models for at least 30 tributaries to the Great Lakes to better understand sediment erosion, transport, and aggradation processes that affect Federal navigation channels and harbors. Many of the USACE hydrologic models have been coupled with hydrodynamic and sediment-transport models that simulate the processes in the stream and harbor near the mouth of the modeled tributary. Some models either have been applied or have the capability of being applied across the entire Great Lakes Basin; they are (1) the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model, which was developed by the USGS; (2) the High Impact Targeting (HIT) and Digital Watershed models, which were developed by the Institute of Water Research at Michigan State University; (3) the Long-Term Hydrologic Impact Assessment (L–THIA) model, which was developed by researchers at Purdue University; and (4) the Water Erosion Prediction Project (WEPP) model, which was developed by the National Soil Erosion Research Laboratory of the U.S. Department of Agriculture. During 2010, the USGS used the Precipitation-Runoff Modeling System (PRMS) to create a hydrologic model for the Lake Michigan Basin to assess the probable effects of climate change on future groundwater and surface-water resources. The Water Availability Tool for Environmental Resources (WATER) model and the Analysis of Flows In Networks of CHannels (AFINCH) program also were used to support USGS GLRI projects that required estimates of streamflows throughout the Great Lakes Basin. This information on existing watershed models, along with an assessment of geologic, soils, and land-use data across the Great Lakes Basin and the identification of problems that exist in selected tributary watersheds that could be addressed by a watershed model, was used to identify three watersheds in the Great Lakes Basin for future modeling by the USGS. These watersheds are the Kalamazoo River Basin in Michigan, the Tonawanda Creek Basin in New York, and the Bad River Basin in Wisconsin. These candidate watersheds have hydrogeologic, land-type, and soil characteristics that make them distinct from each other, but that are representative of other tributary watersheds within the Great Lakes Basin. These similarities in the characteristics among nearby watersheds will enhance the usefulness of a model by improving the likelihood that parameter values from a previously modeled watershed could reliably be used in the creation of a model of another watershed in the same region. The software program Hydrological Simulation Program–Fortran (HSPF) was selected to simulate the hydrologic, sedimentary, and water-quality processes in these selected watersheds. HSPF is a versatile, process-based, continuous-simulation model that has been used extensively by the scientific community, has the ongoing technical support of the U.S. Environmental Protection Agency and USGS, and provides a means to evaluate the effects that land-use changes or management practices might have on the simulated processes.

Great Lakes Basin↗
USGS2019

Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine

Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used to estimate agricultural productivity as well as degree of disturbance on food security from natural disasters and political conflict. However, existing cropland extent maps over large areas (e.g., Country, region, continent, world) are derived from coarse resolution imagery (250 m to 1 km pixels) and have many limitations such as missing fragmented and\or small farms with mixed signatures from different crop types and\or farming practices that can be, confused with other land cover. As a result, the coarse resolution maps have limited useflness in areas where fields are small (<1 ha), such as in Southeast Asia. Furthermore, coarse resolution cropland maps have known uncertainties in both geo-precision of cropland location as well as accuracies of the product. To overcome these limitations, this research was conducted using multi-date, multi-year 30-m Landsat time-series data for 3 years chosen from 2013 to 2016 for all Southeast and Northeast Asian Countries (SNACs), which included 7 refined agro-ecological zones (RAEZ) and 12 countries (Indonesia, Thailand, Myanmar, Vietnam, Malaysia, Philippines, Cambodia, Japan, North Korea, Laos, South Korea, and Brunei). The 30-m (1 pixel = 0.09 ha) data from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) were used in the study. Ten Landsat bands were used in the analysis (blue, green, red, NIR, SWIR1, SWIR2, Thermal, NDVI, NDWI, LSWI) along with additional layers of standard deviation of these 10 bands across 1 year, and global digital elevation model (GDEM)-derived slope and elevation bands. To reduce the impact of clouds, the Landsat imagery was time-composited over four time-periods (Period 1: January- April, Period 2: May-August, and Period 3: September-December) over 3-years. Period 4 was the standard deviation of all 10 bands taken over all images acquired during the 2015 calendar year. These four period composites, totaling 42 band data-cube, were generated for each of the 7 RAEZs. The reference training data (N = 7849) generated for the 7 RAEZ using sub-meter to 5-m very high spatial resolution imagery (VHRI) helped generate the knowledge-base to separate croplands from non-croplands. This knowledge-base was used to code and run a pixel-based random forest (RF) supervised machine learning algorithm on the Google Earth Engine (GEE) cloud computing environment to separate croplands from non-croplands. The resulting cropland extent products were evaluated using an independent reference validation dataset (N = 1750) in each of the 7 RAEZs as well as for the entire SNAC area. For the entire SNAC area, the overall accuracy was 88.1% with a producer’s accuracy of 81.6% (errors of omissions = 18.4%) and user’s accuracy of 76.7% (errors of commissions = 23.3%). For each of the 7 RAEZs overall accuracies varied from 83.2 to 96.4%. Cropland areas calculated for the 12 countries were compared with country areas reported by the United Nations Food and Agriculture Organization and other national cropland statistics resulting in an R 2 value of 0.93. The cropland areas of provinces were compared with the province statistics that showed an R 2 = 0.95 for South Korea and R 2 = 0.94 for Thailand. The cropland products are made available on an interactive viewer at www.croplands.org and for download at National Aeronautics and Space Administration’s (NASA) Land Processes Distributed Active Archive Center (LP DAAC): https://lpdaac.usgs.gov/node/1281 .

International Journal of Applied Earth Observation↗
USGS2017

Tracking the fate of nitrate through pulse-flow wetlands: A mesocosm scale 15N enrichment tracer study

Quantitative information about the fate of applied nitrate (NO 3 -N) in pulse-flow constructed wetlands is essential for designing wetland treatment systems and assessing their nitrogen removal services for agricultural and stormwater applications. Although many studies have documented NO 3 -N losses in wetlands, controlled experiments indicating the relative importance of different processes and N sinks are scarce. In the current study, 15 NO 3 -N isotope enrichment tracer experiments were conducted in wetland mesocosms of two different wetland soil types at two realistic agricultural NO 3 -N source loads. The 15 N label was traced from the source NO 3 -N into plant biomass, soil (including organic matter and ammonium), and N-gas constituents over 7–10 day study periods. All sinks responded positively to higher NO 3 -N loading. Plant uptake exceeded denitrification 2–3 fold in the low NO 3 -N loading experiments, while both fates were nearly equivalent in the high loading experiments. One to two years later, soils largely retained the assimilated tracer N, whereas plants had lost much of it. Results demonstrated that plant and microbial assimilation in the soil (temporary N sinks) can exceed denitrification (permanent N loss) in pulse-flow environments and must be considered by wetland designers and managers for optimizing nitrogen removal potential.

Ecological Engineering↗
USGS1979

Evaluation of methods for estimating ground-water withdrawals in western Kansas

During 1978, methods of estimating ground-water withdrawals in western Kansas were examined and evaluated, using both existing data from the files of the U.S. Geological Survey and newly collected data. Values for annual ground-water withdrawals reported to the Division of Water Resources, Kansas State Board of Agriculture, by water users probably contain substantial errors because most individual users do not possess the means to measure or accurately estimate the discharge rates of their wells. Such reported values are estimated to average 10 to 15 percent higher than the actual discharge rate. Values obtained from discharge-totaling meters are reasonably accurate, but few wells are equipped with these meters, and the cost of equipping all wells with meters may be prohibitive. Measured rates of power consumption can give good estimates of total withdrawal from wells where the power consumption is measured. However, power-consumption values cannot be extrapolated reliably from one well to another. Three techniques are regarded as promising for estimating areal ground-water withdrawals from readily collected data: Examination of a small sample of withdrawal values from metered wells indicates that the statistical approach used by Luckey (1972) may be applied to western Kansas to estimate total withdrawal with acceptable accuracy in a large area from a statistical sample of measured values. Measured values of irrigation application at a small number of selected wells might be used to compute total withdrawal for irrigation by crop type and precipitation zone. Evaluation of reported values of irrigation-water application for selected crops in zones of generally similar precipitation showed that, although the reported values are judged to be erroneously high, the reported values were consistent with each other and with average precipitation. Power-consumption coefficients may be used to calculate an average coefficient for an area. The method described by Luckey (1972) was used to calculate the number of power-consumption coefficients that would have to be determined to estimate the mean power consumption of wells pumped by electric or natural-gas engines. The results indicate that as few as 100 values would produce results accurate to within 10 percent of the true average at the 95-percent confidence level. Thus, power coefficients for a particular type of irrigation system in any given area can be used even though values of power coefficients have little transfer value from well to well. Efforts by the Instrument Development Laboratofy of the U.S. Geological Survey to design improved instruments for measuring ground-water withdrawals have produced two promising results: An electronic running-time meter (Running-time Sentry) that was tested during 1978 in western Kansas and Florida appears to give accurate values of total pumping time. Large-scale testing of this prototype running-time meter is planned for 1979. A low-cost discharge-totaling meter (REELTOT), based on the concept of sensing the velocity head in a pipe with differential-pressure transducers permanently installed in the pipe, is nearly complete. Early prototypes of this instrument may be tested in western Kansas during 1979. For the remainder of this study, the three techniques for estimating areal ground-water withdrawals described above will be tested on a larger scale in Groundwater Management District No. 1, an area of about 1,800 square miles in west-central Kansas. About 150 randomly selected wells will be equipped with Running-time Sentry units and monitored for total withdrawal, instantaneous discharge, and power consumption. A few wells will be equipped with prototype discharge-totaling meters. The performance of the Sentry units and discharge-totaling meters will be evaluated. Areal estimates of withdrawal from measured withdrawal values, from average power-consumption coefficients, and from irrigation application by crop will be calculated and compared with each other and with reported values of withdrawal.

Kansas↗
USGS2017

A review of surface energy balance models for estimating actual evapotranspiration with remote sensing at high spatiotemporal resolution over large extents

Many approaches have been developed for measuring or estimating actual evapotranspiration ( ET a ), and research over many years has led to the development of remote sensing methods that are reliably reproducible and effective in estimating ET a . Several remote sensing methods can be used to estimate ET a at the high spatial resolution of agricultural fields and the large extent of river basins. More complex remote sensing methods apply an analytical approach to ET a estimation using physically based models of varied complexity that require a combination of ground-based and remote sensing data, and are grounded in the theory behind the surface energy balance model. This report, funded through cooperation with the International Joint Commission, provides an overview of selected remote sensing methods used for estimating water consumed through ET a and focuses on Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Operational Simplified Surface Energy Balance (SSEBop), two energy balance models for estimating ET a that are currently applied successfully in the United States. The METRIC model can produce maps of ET a at high spatial resolution (30 meters using Landsat data) for specific areas smaller than several hundred square kilometers in extent, an improvement in practice over methods used more generally at larger scales. Many studies validating METRIC estimates of ET a against measurements from lysimeters have shown model accuracies on daily to seasonal time scales ranging from 85 to 95 percent. The METRIC model is accurate, but the greater complexity of METRIC results in greater data requirements, and the internalized calibration of METRIC leads to greater skill required for implementation. In contrast, SSEBop is a simpler model, having reduced data requirements and greater ease of implementation without a substantial loss of accuracy in estimating ET a . The SSEBop model has been used to produce maps of ET a over very large extents (the conterminous United States) using lower spatial resolution (1 kilometer) Moderate Resolution Imaging Spectroradiometer (MODIS) data. Model accuracies ranging from 80 to 95 percent on daily to annual time scales have been shown in numerous studies that validated ET a estimates from SSEBop against eddy covariance measurements. The METRIC and SSEBop models can incorporate low and high spatial resolution data from MODIS and Landsat, but the high spatiotemporal resolution of ET a estimates using Landsat data over large extents takes immense computing power. Cloud computing is providing an opportunity for processing an increasing amount of geospatial “big data” in a decreasing period of time. For example, Google Earth Engine TM has been used to implement METRIC with automated calibration for regional-scale estimates of ET a using Landsat data. The U.S. Geological Survey also is using Google Earth Engine TM to implement SSEBop for estimating ET a in the United States at a continental scale using Landsat data.

Scientific Investigations Report↗