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USGS2010

Land-use pressure and a transition to forest-cover loss in the Eastern United States

Contemporary land-use pressures have a significant impact on the extent and condition of forests in the eastern United States, causing a regional-scale decline in forest cover. Earlier in the 20th century, land cover was on a trajectory of forest expansion that followed agricultural abandonment. However, the potential for forest regeneration has slowed, and the extent of regional forest cover has declined by more than 4.0%. Using remote-sensing data, statistical sampling, and change-detection methods, this research shows how land conversion varies spatially and temporally across the East from 1973–2000, and how those changes affect regional land-change dynamics. The analysis shows that agricultural land use has continued to decline, and that this enables forest recovery; however, an important land-cover transition has occurred, from a mode of regional forest-cover gain to one of forest-cover loss caused by timber cutting cycles, urbanization, and other land-use demands.

BioScience↗

USGS2023

Assessment of public and private land cover change in the United States from 1985–2018

An assessment of annual land cover on publicly and privately managed lands across the conterminous United States (CONUS) from 1985–2018 was performed, including land cover conversions within their management category, to inform future policy and land-use decision-making in natural resource management. Synthesizing land cover data with land management delineations aids our ability to address effects of land management decisions by public or private entities. The U.S. Geological Survey (USGS) Protected Areas Database of the United States (PAD-US) version 2.1 data delineate land management categories and enable examination of land cover composition and change using the USGS Land Change Monitoring, Assessment, and Projection (LCMAP) reference data. Average composition of our delineated CONUS results using LCMAP land cover classes is 40% Grass/Shrub (GS), 29% Tree Cover (TC), 18% Cropland (CP), 5% Developed (DV), 5% Wetland (WL), 1.8% Water (WR), and 0.9% Barren (BN). Private (public) land is composed of 35% (52%) GS, 27% (36%) TC, 25% (1%) CP, 7% (1%) DV, 5% (5%) WL, 2% (2%) WR, and less than 1% (3%) BN. Land cover change averaged less than 1% per year. The largest net percentage gains across CONUS were in DV land and GS, and the greatest net losses were in CP and TC. Approximately 73% of CONUS is private land and, thus, land cover change across CONUS is largely a reflection of private land change dynamics. Private compositional changes show net gains from 1985–2018 in DV (2.3%), WR (0.2%), and GS (0.1%) classes, while net losses occurred in CP (−1.9%), TC (−0.6%), WL (−0.1%), and BN (−0.01%). Public land cover changes show net gains in GS (1%), DV (0.2%), WR (0.01%), WL (0.05%), and BN (0.1%) classes, and net losses in CP (−0.3%) and TC (−1%). Our study reveals connections between land cover conversion and various policy and socioeconomic decisions through time.

Environmental Research Communications↗

USGS2021

A novel automatic phenology learning (APL) method of training sample selection using multiple datasets for time-series land cover mapping

The long record of Landsat imagery, which is the cornerstone of Earth observation, provides an opportunity to monitor land use and land cover (LULC) change and understand the interactions between the climate and earth system through time. A few change detection algorithms such as Continuous Change Detection and Classification (CCDC) have been developed to utilize all available Landsat images for change detection and characterization at local or global scales. However, the reliable, rapid, and reproducible collection of training samples have become a challenge for time series land cover classification at a large scale. To meet the challenge, we proposed an automatic phenology learning (APL) method with the assumption that the temporal profiles of samples within the same land cover type are the same or similar at a local scale to generate evenly distributed training samples automatically. We designed the method to build land cover patterns for each category based on consensus samples derived from multiple existing scientific datasets including LANDFIRE's (LF) Existing Vegetation Type (EVT), USGS National Land Cover Database (NLCD), National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL), and National Wetlands Inventory (NWI). Then we calculated the Time-Weighted Dynamic Time Warping (twDTW) distance between any undefined samples and land cover patterns in the same geographical region as prior knowledge. Finally, we selected the optimal land cover category for each undefined sample from the land cover products based on the designed criteria iteratively using the twDTW distance as an indicator. The method was applied in the footprint of 10 selected Landsat Analysis Ready Data (ARD) tiles in the eastern and western conterminous United States (CONUS) to produce annual land cover maps from 1985 to 2017. The accuracy assessment and visual comparison revealed that the APL method can generate reliable training samples without any manual interpretation, producing better land cover results especially for the grass/shrub and wetland land cover classes. Applying the APL method, the overall accuracy of the annual land cover maps was improved by 2% over the accuracy of Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Science Products in the research regions. Our results also indicate that the APL method provides an approach for best use of different land cover products and meets the requirement of intensive sampling for training data collection.

Remote Sensing of Environment↗

USGS2017

Population trends, extinction risk, and conservation guidelines for ferruginous pygmy-owls in the Sonoran Desert

Climatic flux together with anthropogenic changes in land use and land cover pose major threats to wildlife, but our understanding of their combined impacts is limited. In arid southwestern North America, ferruginous pygmy-owls ( Glaucidium brasilianum ) are of major conservation concern due to marked declines in abundance linked to changes in land use and land cover during the past century. We reassessed abundance trends of pygmy-owls in northern Mexico across 17 years (2000-2016), which included data gathered over four additional years since inferences were last reported. We also assessed spatiotemporal trends in territory occupancy (n = 151 territories) across a much larger area that spanned 14 watershed regions in northern Mexico and adjacent Arizona over 16 years (2001-2016). Finally, we evaluated the influence of temperature, precipitation, land-use and land-cover change, spatial variation in local habitat quality, and interactions among these factors on occupancy dynamics. Large increases in abundance in 2015 and 2016 eliminated evidence of population declines that was described recently (e.g., Flesch 2014a) based on two modeling approaches. Moreover, there was little evidence of systematic temporal declines in territory occupancy across the broader bi-national study area, or for population units in Mexico and the adjacent U.S. Instead, occupancy dynamics varied at smaller spatial scales among watershed regions. We found that subpopulations in six regions declined or marginally declined across time, including two in the U.S. that declined to extinction; subpopulations in six other regions were stable; and those in two regions increased or marginally increased. Although variation in territory occupancy was associated with changes in temperature, precipitation, anthropogenic disturbance, and local differences in habitat quality, evidence for interactions among these factors was much greater than that for additive relationships. Territory occupancy declined with rising minimum air temperatures during winter at a much greater rate in disturbed landscapes compared to those with little to no anthropogenic disturbance. Moreover, occupancy increased with annual precipitation at increasingly positive rates as local territory quality increased. Such results suggest a complex set of processes simultaneously drove changes in territory occupancy, likely by influencing food abundance and the quantity, connectivity, and quality of habitat. Management focused on 1) protecting high-quality habitat, 2) enhancing and creating habitat (e.g., nest-cavity augmentation, riparian restoration), 3) reducing deleterious changes in land use and land cover, and 4) increasing landscape connectivity through both passive (e.g., landscape planning and restoration) and active (e.g., facilitated dispersal, translocations) techniques will enhance recovery prospects for pygmyowls.

Sonoran Desert↗

USGS1971

Effects of irrigation on streamflow in the Central Sand Plain of Wisconsin

Development of ground water for irrigation affects streamflow and water levels in the sand-plain area of central Wisconsin. Additional irrigation development may reduce opportunities for water-based recreation by degrading the streams as trout habitat and by lowering lake levels. This study was made to inventory present development of irrigation in the sand-plain area, assess potential future development, and estimate the effects of irrigation on streamflow and ground-water levels. The suitability of land and the availability of ground water for irrigation are dependent, to a large extent, upon the geology of the area. Rocks making up the ground-water reservoir include outwash, morainal deposits, and glacial lake deposits. These deposits are underlain by crystalline rocks and by sandstone, which act as the floor of the ground-water reservoir. Outwash, the main aquifer, supplies water to about 300 irrigation wells and maintains relatively stable flow in the streams draining the area. The saturated thickness of these deposits is more than 100 feet over much of the area and is as much as 180 feet in bedrock valleys. The saturated thickness of the outwash generally is great enough to provide sufficient water for large-scale irrigation in all but two areas --one near the town of Wisconsin Rapids and one near Dorro Couche Mound. Aquifer tests indicate that the permeability of the outwash is quite high, ranging from about 1,000 gpd per square foot to about 3,800 gpd per square foot, Specific capacities of irrigation wells in the area range from 14 to 157 gpm per foot of drawdown. Water use in the sand-plain area is mainly for irrigation and waterbased recreation. Irrigation development began in the area in the late 1940's, and by 1967 about 19,500 acre-feet of water were pumped to irrigate 34,000 acres of potatoes, snap beans, corn, cucumbers, and other crops. About 70 percent of the applied water was lost to evapotranspiration, and about 30 percent was returned to the ground-water reservoir. Irrigation development should continue in the sand plain; future development probably will include improved artificial drainage and land clearing. The hydrology of the sand-plain area was studied from water budgets for seven basins and from water balances for eight types of vegetative cover or land use. During the study period about 16-20 inches of the 28- to 30-inch average annual precipitation were lost to evapotranspiration from different basins in the area, Evapotranspiration from different types of vegetative cover or land use ranged from about 14 inches per year for bare ground to about 25 inches per year from land covered by phreatophytes. Evapotranspiration is about 19 inches from forested land, about 16 inches from grassland and unirrigated row crops, about 19 inches from irrigated beans, and about 22 inches from irrigated potatoes. Variations in evapotranspiration from the different types of vegetative cover result mainly from differences in soil moisture available to the plants. Available soil moisture ranges from about 1 inch for shallow-rooted grasses and row crops to about 3 inches for forest. Most of the precipitation not used by plants or to replenish soil moisture seeps to the water table, and ground-water recharge in the area averages about 12-14 inches per year. However, computed recharge ranged from about 3 inches to about 22 inches during the 1948-67 period, depending upon the amount and seasonal distribution of precipitation. Of the average 12-14 inches of recharge, about lo-13 inches are discharged to the streams draining the area, and about l-2 inches are used by phreatophytes or by irrigated crops. Annual streamflow in the area averages about 11-12 inches per year, and because it is sustained mainly by ground water, its seasonal distribution is fairly uniform, However, streamflow varies seasonally, being highest in the spring, low in the summer, higher

Wisconsin↗

USGS1983

Application of total-count aeroradiometric maps to the exploration for heavy-mineral deposits in the coastal plain of Virginia, with a section on field-spectrometer-data reduction

Total-count contoured aeroradiometric maps for the Coastal Plain of Virginia were used in an effort to locate economic heavy-mineral placer deposits. The principle behind this approach is that heavy- mineral suites commonly contain radioactive minerals that, if the concentration of heavy minerals is exposed at or within inches of the surface, enable the deposit to be located by use of airborne instruments because of its radiometric contrast with the host sediment. Detailed and regional geologic maps, soil maps, land-use and land- cover maps, information on fertilizer use, and ground-spectrometer data were used to study aeroradiometric anomalies for efficient exploration. Aeroradiometric anomalies in the Coastal Plain of Virginia have three general causes. First, the most intense anomalies are associated with cultural features, such as roads made of granitic material. Second, most anomalies of high to intermediate intensity are associated with land used for agricultural purposes and evidently are caused by applications of radioactive fertilizer. Third, anomalies of intermediate to low intensity are associated with heavy-mineral deposits. Results of this study show that aeroradiometric anomalies associated with heavy-mineral accumulations in the Coastal Plain of Virginia have ground radiometric spectra in which thorium is the strongest component and uranium and potassium are lesser components. Heavy-mineral accumulations found in this study by use of the aeroradiometric data are not considered to be of economic importance, mostly because of the low percentage of economic minerals in the heavy-mineral suites and also because of other factors such as the very fine grained nature of the host sediments and competing land use.

Virginia↗

USGS2021

Precipitation characteristics and land cover control wet season runoff source and rainfall partitioning in three humid tropical catchments in central Panama

Mechanisms of runoff generation in the humid tropics are poorly understood, particularly in the context of land-use/land cover change. This study analyzed the results of 124 storm hydrographs from three humid tropical catchments of markedly different vegetation cover and land-use history in central Panama during the 2017 wet season: actively grazed pasture, young secondary succession, and near-mature forest. We used electrical conductivity to separate baseflow (old water) from storm-event water (new-water). In all three land covers, new-water dominated storm runoff generation in 44% of the sampled storm events, indicating the dominance of fast shallow flow paths in the landscape. Activation of these flow paths was found to depend on a combination of maximum rainfall intensity and total storm rainfall, which, in turn, relates to markedly contrasting hydrograph separation results among land covers. Relationships between these rainfall characteristics and storm runoff generation were nonlinear, producing a threshold response with the exceedance of specific rainfall volumes and/or intensities. The pastoral catchment delivered order of magnitude more new-water during storm events than the two forested catchments. Although new-water contributed minimally (<10%) to total wet season runoff in the forested catchments, 43% of runoff generation in the pasture came from five large rainfall events where a threshold response produced substantial increases in total runoff and new-runoff efficiency. Based on our results, we propose a conceptual model of hydrologic flow paths in humid tropical systems that can explain previously observed disparities in seasonal storage and runoff with respect to land use/land cover.

Agua Salud Watershed↗

USGS2009

Land Cover Trends in the Southern Florida Coastal Plain

This report presents an assessment of land use and land cover change in the Southern Florida Coastal Plain ecoregion for the period from 1973 to 2000. The ecoregion is one of 84 level III ecoregions defined by the Environmental Protection Agency; ecoregions have been designed to serve as a spatial framework for environmental resource management and denote areas that contain a geographically distinct assemblage of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The Southern Florida Coastal Plain ecoregion covers an area of approximately 22,407 square kilometers [8,651 square miles] across the lower portion of the Florida peninsula, from Lake Okeechobee southward through the Florida Keys. It comprises flat plains with wet soils, marshland and swamp land cover with Everglades and palmetto prairie vegetation types.

Scientific Investigations Report↗

USGS2006

Temporal evolution of carbon budgets of the Appalachian forests in the U.S. from 1972 to 2000

Estimating dynamic terrestrial ecosystem carbon (C) sources and sinks over large areas is difficult. The scaling of C sources and sinks from the field level to the regional level has been challenging due to the variations of climate, soil, vegetation, and disturbances. As part of an effort to estimate the spatial, temporal, and sectional dimensions of the United States C sources and sinks (the U.S. Carbon Trends Project), this study estimated the forest ecosystem C sequestration of the Appalachian region (186,000 km 2 ) for the period of 1972–2000 using the General Ensemble Biogeochemical Modeling System (GEMS) that has a strong capability of assimilating land use and land cover change (LUCC) data. On 82 sampling blocks in the Appalachian region, GEMS used sequential 60 m resolution land cover change maps to capture forest stand-replacing events and used forest inventory data to estimate non-stand-replacing changes. GEMS also used Monte Carlo approaches to deal with spatial scaling issues such as initialization of forest age and soil properties. Ensemble simulations were performed to incorporate the uncertainties of input data. Simulated results show that from 1972 to 2000 the net primary productivity (NPP), net ecosystem productivity (NEP), and net biome productivity (NBP) averaged 6.2 Mg C ha −1 y −1 (±1.1), 2.2 Mg C ha −1 y −1 (±0.6), and 1.8 Mg C ha −1 y −1 (±0.6), respectively. The inter-annual variability was driven mostly by climate. Detailed C budgets for the year 2000 were also calculated. Within a total 148,000 km 2 forested area, average forest ecosystem C density was estimated to be 186 Mg C ha −1 (±20), of which 98 Mg C ha −1 (±12) was in biomass and 88 Mg C ha −1 (±13) was in litter and soil. The total simulated C stock of the Appalachian forests was estimated to be 2751 Tg C (±296), including 1454 Tg C (±178) in living biomass and 1297 Tg C (±192) in litter and soil. The total net C sequestration (i.e. NBP) of the forest ecosystem in 2000 was estimated to be 19.5 Tg C y −1 (±6.8).

Forest Ecology and Management↗

USGS2006

Analysis of urban land use change in the Las Vegas metropolitan area using multi-temporal satellite imagery

Urban development has expanded rapidly in Las Vegas, Nevada, over the last fifty years. To assess urban land use change in the area, a sub-pixel change detection approach has been used to map urban extent and its temporal changes by determining sub-pixel level impervious surface areas from Landsat satellite remote sensing data in conjunction with digital orthophotography. Sub-pixel percentages of imperviousness are mapped from the 1980s to the 2000s for the Las Vegas metropolitan area using a regression tree model. The spatial-temporal distribution of vegetation in the urban area has also been quantified using the same approach. Analysis suggests that spatial and temporal changes in impervious surface are useful indicators of spatial extent, intensity, and potentially, the types of urban land cover and land use change. Results indicate that areas of 40–60% imperviousness have experienced the largest increase in Las Vegas, suggesting that areas of medium to high development density areas represent the major urban land uses in the region. Urban area fractional vegetation cover has the highest coverage in medium-density urban areas of Las Vegas.

Nevada↗

USGS2013

Estimating the extent of impervious surfaces and turf grass across large regions

The ability of researchers to accurately assess the extent of impervious and pervious developed surfaces, e.g., turf grass, using land-cover data derived from Landsat satellite imagery in the Chesapeake Bay watershed is limited due to the resolution of the data and systematic discrepancies between developed land-cover classes, surface mines, forests, and farmlands. Estimates of impervious surface and turf grass area in the Mid-Atlantic, United States that were based on 2006 Landsat-derived land-cover data were substantially lower than estimates based on more authoritative and independent sources. New estimates of impervious surfaces and turf grass area derived using land-cover data combined with ancillary information on roads, housing units, surface mines, and sampled estimates of road width and residential impervious area were up to 57 and 45% higher than estimates based strictly on land-cover data. These new estimates closely approximate estimates derived from authoritative and independent sources in developed counties.

Delaware;Maryl;New York;Pennsylvania↗

USGS2008

Development and Evaluation of a Riparian Buffer Mapping Tool

Land use and land cover within riparian areas greatly affect the conditions of adjacent water features. In particular, riparian forests provide many environmental benefits, including nutrient uptake, bank stabilization, steam shading, sediment trapping, aquatic and terrestrial habitat, and stream organic matter. In contrast, residential and commercial development and associated transportation infrastructure increase pollutant and nutrient loading and change the hydrologic characteristics of the landscape, thereby affecting both water quality and habitat. Restoring riparian areas is a popular and cost effective restoration technique to improve and protect water quality. Recognizing this, the Chesapeake Executive Council committed to restoring 10,000 miles of riparian forest buffers throughout the Chesapeake Bay watershed by the year 2010. In 2006, the Chesapeake Executive Council further committed to 'using the best available...tools to identify areas where retention and expansion of forests is most needed to protect water quality'. The Chesapeake Bay watershed encompasses 64,000 square miles, including portions of six States and Washington, D.C. Therefore, the interpretation of remotely sensed imagery provides the only effective technique for comprehensively evaluating riparian forest protection and restoration opportunities throughout the watershed. Although 30-meter-resolution land use and land cover data have proved useful on a regional scale, they have not been equally successful at providing the detail required for local-scale assessment of riparian area characteristics. Use of high-resolution imagery (HRI) provides sufficient detail for local-scale assessments, although at greater cost owing to the cost of the imagery and the skill and time required to process the data. To facilitate the use of HRI for monitoring the extent of riparian forest buffers, the U.S. Forest Service and the U.S. Geological Survey Eastern Geographic Science Center funded the development of a prototype semiautomated image classification tool, RBMapper, that is designed for use by technicians with limited image processing training. This document provides an overview of the RBMapper tool, includes instructions on how to obtain the RBMapper tool and tutorial datasets, and contains a summary evaluation of the tool

Open-File Report↗

USGS1997

Land cover characterization and land surface parameterization research

The understanding of land surface processes and their parameterization in atmospheric, hydrologic, and ecosystem models has been a dominant research theme over the past decade. For example, many studies have demonstrated the key role of land cover characteristics as controlling factors in determining land surface processes, such as the exchange of water, energy, carbon, and trace gases between the land surface and the lower atmosphere. The requirements for multiresolution land cover characteristics data to support coupled-systems modeling have also been well documented, including the need for data on land cover type, land use, and many seasonally variable land cover characteristics, such as albedo, leaf area index, canopy conductance, surface roughness, and net primary productivity. Recently, the developers of land data have worked more closely with the land surface process modelers in these efforts.

Ecological Applications↗

USGS1997

Environmental setting and implications for water quality in the Western Lake Michigan Drainages

In 1991, the U.S. Geological Survey began to implement its National Water-Quality Assessment (NAWQA) program. The Western Lake Michigan Drainages was one of 20 study units selected for investigation to begin in 1991. The study-unit investigation will include an assessment of surface- and ground-water quality. The quality of water in a study unit is intrinsically related to the natural and anthropogenic features of the study unit. The natural features include geology, weather and climate, vegetation, and hydrology. The anthropogenic features of the basin include population distribution, land use and land cover, agricultural practices, and water use. This report describes the natural and anthropogenic features that constitute the environmental setting of the Western Lake Michigan Drainages as well as the implications of those features on the water quality.

Wisconsin↗

USGS2006

Quantifying the Components of Impervious Surfaces

This study's objectives were to (1) determine the relative contribution of impervious surface individual components by collecting digital information from high-resolution imagery, 1-meter or better; and to (2) determine which of the more advanced techniques, such as spectral unmixing or the application of coefficients to land use or land cover data, was the most suitable method that could be used by State and local governments as well as Federal agencies to efficiently measure the imperviousness in any given watershed or area of interest. The components of impervious surfaces, combined from all the watersheds and time periods from objective one were the following: buildings 29.2-percent, roads 28.3-percent, parking lots 24.6-percent; with the remaining three totaling 14-percent - driveways, sidewalks, and other, where other were any other features that were not contained within the first five. Results from objective two were spectral unmixing techniques will ultimately be the most efficient method of determining imperviousness, but are not yet accurate enough as it is critical to achieve accuracy better than 10-percent of the truth, of which the method is not consistently accomplishing as observed in this study. Of the three techniques in coefficient application tested, land use coefficient application was not practical, while if the last two methods, coefficients applied to land cover data, were merged, their end results could be to within 5-percent or better, of the truth. Until the spectral unmixing technique has been further refined, land cover coefficients should be used, which offer quick results, but not current as they were developed for the 1992 National Land Characteristics Data.

Open-File Report↗

USGS2012

Modeling habitat dynamics accounting for possible misclassification

Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.

Landscape Ecology↗

USGS2007

Factors affecting herbicide yields in the Chesapeake Bay watershed, June 1994

Median concentrations and instantaneous yields of alachlor, metolachlor, atrazine, cyanazine, and simazine were generally highest at sites in the Lower Susquehanna River Basin and in agricultural subbasins. Instantaneous herbicide yields are related to land use, hydrogeologic setting, streamflow yield, and agricultural row cropping practices. The significance of these relations may be affected by the interdependence of the factors. The percentage of basin area planted in corn is the most influential factor in the prediction of herbicide yield. Instantaneous yields of all five herbicides measured in June 1994 related poorly to averaged 199094 herbicide use. Annually averaged herbicide-use data are too general to use as a predictor for short-term herbicide yields. An evaluation of factors affecting herbicide yields could be refined with more-current land use and land cover information and a more accurate estimate of the percentage of basin area planted in corn. Factors related to herbicide yields can be used to predict herbicide yields in other basins within the Chesapeake Bay watershed and to develop an estimate of herbicide loads to Chesapeake Bay.Median concentrations and instantaneous yields of alachlor, metolachlor, atrazine, cyanazine, and simazine were generally highest at sites in the Lower Susquehanna River Basin and in agricultural subbasins. Instantaneous herbicide yields are related to land use, hydrogeologic setting, streamflow yield, and agricultural row cropping practices. The significance of these relations may be affected by the interdependence of the factors. The percentage of basin area planted in corn is the most influential factor in the prediction of herbicide yield. Instantaneous yields of all five herbicides measured in June 1994 related poorly to averaged 1990-94 herbicide use. Annually averaged herbicide-use data are too general to use as a predictor for short-term herbicide yields. An evaluation of factors affecting herbicide yields could be refined with more-current land use and land cover information and a more accurate estimate of the percentage of basin area planted in corn. Factors related to herbicide yields can be used to predict herbicide yields in other basins within the Chesapeake Bay watershed and to develop an estimate of herbicide loads to Chesapeake Bay.

Water Resources Bulletin↗

USGS1997

Classification and Mapping of Agricultural Land for National Water-Quality Assessment

Agricultural land use is one of the most important influences on water quality at national and regional scales. Although there is great diversity in the character of agricultural land, variations follow regional patterns that are influenced by environmental setting and economics. These regional patterns can be characterized by the distribution of crops. A new approach to classifying and mapping agricultural land use for national water-quality assessment was developed by combining information on general land-use distribution with information on crop patterns from agricultural census data. Separate classification systems were developed for row crops and for orchards, vineyards, and nurseries. These two general categories of agricultural land are distinguished from each other in the land-use classification system used in the U.S. Geological Survey national Land Use and Land Cover database. Classification of cropland was based on the areal extent of crops harvested. The acreage of each crop in each county was divided by total row-crop area or total orchard, vineyard, and nursery area, as appropriate, thus normalizing the crop data and making the classification independent of total cropland area. The classification system was developed using simple percentage criteria to define combinations of 1 to 3 crops that account for 50 percent or more or harvested acreage in a county. The classification system consists of 21 level I categories and 46 level II subcategories for row crops, and 26 level I categories and 19 level II subcategories for orchards, vineyards, and nurseries. All counties in the United States with reported harvested acreage are classified in these categories. The distribution of agricultural land within each county, however, must be evaluated on the basis of general land-use data. This can be done at the national scale using 'Major Land Uses of the United States,' at the regional scale using data from the national Land Use and Land Cover database, or at smaller scales using locally available data.

Circular↗