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Enhanced Historical Land-Use and Land-Cover Data Sets of the U.S. Geological Survey

Historical land-use and land-cover data, available from the U.S. Geological Survey (USGS) for the conterminous United States and Hawaii, have been enhanced for use in geographic information systems (GIS) applications. The original digital data sets were created by the USGS in the late 1970s and early 1980s and were later converted by USGS and the U.S. Environmental Protection Agency (USEPA) to a geographic information system (GIS) format in the early 1990s. These data were made available on USEPA's Web site since the early 1990s and have been used for many national applications, despite minor coding and topological errors. During the 1990s, a group of USGS researchers made modifications to the data set for use in the National Water-Quality Assessment Program. These edited files have been further modified to create a more accurate, topologically clean, and seamless national data set. Several different methods, including custom editing software and several batch processes, were applied to create this enhanced version of the national data set. The data sets are included in this report in the commonly used shapefile and Tagged Image Format File (TIFF) formats. In addition, this report includes two polygon data sets (in shapefile format) representing (1) land-use and land-cover source documentation extracted from the previously published USGS data files, and (2) the extent of each polygon data file.

Data Series↗

Mapping karst groundwater flow paths and delineating recharge areas for Fern Cave, Alabama, through the use of dye tracing

Fern Cave in Jackson County, Alabama, is a 15.6-mile-long (25.1-kilometer) cave system, managed by the U.S. Fish and Wildlife Service and Southeastern Cave Conservancy, that has the second highest biodiversity of any cave in the southeastern United States. Groundwater in karst ecosystems is known to be susceptible to impacts from human-induced land-use activities in watersheds that contribute recharge to the groundwater system. To provide the U.S. Fish and Wildlife Service with necessary baseline information on the groundwater flow system in Fern Cave, the U.S. Geological Survey and the Kentucky Geological Survey conducted a series of dye traces during 2019–21 to delineate the watershed recharging the cave system. The dye traces identified two separate streams that flow through the cave and a recharge area of 1.73 square miles (4.48 square kilometers) draining to the cave system. Current land use within the recharge area is dominated by deciduous forest with minimal additional land use types, indicating a low potential for undesirable effects to the cave by anthropogenic sources.

Alabama↗

Developing a temporal database of urban development for the Baltimore/Washington region

The U.S. Geological Survey (USGS), the University of Maryland Baltimore County (UMBC), and the U.S. Bureau of the Census are working together as a multiagency, multidisciplinary team in developing a temporal database that documents the growth of the Baltimore-Washington metropolitan region. This database consists of urban development, principal transportation, shoreline, and population density change. The urban development theme, considered a primary data layer in the study of urban land transformation resulting from human impact on the land, is the focus of this paper. The Baltimore-Washington Spatial Dynamics and Human Impacts Study builds on earlier research efforts that mapped urban land use change for the San Francisco Bay area (Acevedo and Bell, 1994; Bell and others, 1995; Kirtland and others, 1994). In developing a temporal database (Acevedo and others, in press), the team participants hope to provide data that can be used to study patterns of urban growth; assess ecological, environmental, and climatic impacts of urban change; and model and predict future urbanization patterns and impacts (Clarke and others, 1996). Both the San Francisco and Baltimore-Washington regions were selected because of the rapid urban growth and resulting impacts on their ecosystems. The Chesapeake Bay region in particular has undergone extensive environmental agitation due to the hydrologic problems that have arisen from the increase in impermeable surfaces and structures, that is buildings and pavement that physically cover the soil. Because of the inability of water to percolate into the ground, little purification occurs by filtration. Water runs over paved surfaces and quickly washes high levels of toxins directly into the water system. Toxins like gasoline, oil, and fertilizer have dramatically affected the local streams, rivers, and the bay. ABSTRACT The U.S. Geological Survey, the University of Maryland Baltimore County, and the U.S. Bureau of the Census are developing a temporal database to study urban development in the Baltimore-Washington region. The primary data layer, the extent of urban or built-up areas, was compiled using a geographic information system and historical maps, remotely sensed data, digital land use data, and census information from a variety of sources. Urban land use change has been documented by the Baltimore-Washington Spatial Dynamics & Human Impact Study Team for the last 200 years. The methods, definitions, and collection criteria used to define urban or built-up areas were developed by a multi-disciplinary team that also ensures consistency in collection techniques and documentation methods for subsequent application in other regions. Animation techniques were used to visualize the database and to document the evolution of the region's urban landscape. The database is an important tool to urban and regional planners, ecologists, and global change researchers for measuring trends in urban sprawl, analyzing patterns of water pollution, understanding the impacts of development on ecosystems, and developing predictive modeling techniques to better forecast areas of urban growth. This paper describes the techniques used to map the extent of urban areas for Phase I and does not discuss Phase II in detail because the work is still in progress. In this study, urban development is defined as areas of intensive use, with much of the land covered by structures. The built-up areas are characterized by the existence of a systematic street pattern, and the relative concentration of buildings and associated intensive use areas, such as parking lots. Using this definition, urban development does not refer to political boundaries and may include incorporated or unincorporated areas as well as military reservations. ABSTRACT The U.S. Geological Survey, the University of Maryland Baltimore County, and the U.S. Bureau of the Census are developing a temporal database to study urban development in the Baltimore-Washington region. The primary data layer, the extent of urban or built-up areas, was compiled using a geographic information system and historical maps, remotely sensed data, digital land use data, and census information from a variety of sources. Urban land use change has been documented by the Baltimore-Washington Spatial Dynamics & Human Impact Study Team for the last 200 years. The methods, definitions, and collection criteria used to define urban or built-up areas were developed by a multi-disciplinary team that also ensures consistency in collection techniques and documentation methods for subsequent application in other regions. Animation techniques were used to visualize the database and to document the evolution of the region's urban landscape. The database is an important tool to urban and regional planners, ecologists, and global change researchers for measuring trends in urban sprawl, analyzing patterns of water pollution, understanding the impacts of development on ecosystems, and developing predictive modeling techniques to better forecast areas of urban growth. To build the urban component of the temporal database, a multidisciplinary team was assembled and a phased approach initiated. Expanding on procedures developed for the San Francisco Regional Study (Bell and others, 1995), the team developed data definitions, a classification scheme, compilation criteria, mapping specifications, guidelines for source materials, and metadata specifications to support development of a logically consistent dataset. Extensive documentation procedures were established to ensure consistency in data collection, and for subsequent application to other regions. Phase II was the implementation of the regional mapping effort. ABSTRACT The U.S. Geological Survey, the University of Maryland Baltimore County, and the U.S. Bureau of the Census are developing a temporal database to study urban development in the Baltimore-Washington region. The primary data layer, the extent of urban or built-up areas, was compiled using a geographic information system and historical maps, remotely sensed data, digital land use data, and census information from a variety of sources. Urban land use change has been documented by the Baltimore-Washington Spatial Dynamics & Human Impact Study Team for the last 200 years. The methods, definitions, and collection criteria used to define urban or built-up areas were developed by a multi-disciplinary team that also ensures consistency in collection techniques and documentation methods for subsequent application in other regions. Animation techniques were used to visualize the database and to document the evolution of the region's urban landscape. The database is an important tool to urban and regional planners, ecologists, and global change researchers for measuring trends in urban sprawl, analyzing patterns of water pollution, understanding the impacts of development on ecosystems, and developing predictive modeling techniques to better forecast areas of urban growth. The study area for Phase I consisted of an approximate area of 15- by 15-minute segment centered around the city of Baltimore (fig. 1). Phase I was used as a prototype for the technique development and integration that the multiagency collaborative effort would require. The regional study, Phase II, encompassed a 2-degree square centered on Washington, D.C. With more than 7 million people spread across 39 counties, the Baltimore-Washington region is one the Nation's fastest growing metropolitan areas. The two cities are rapidly merging into one.

Maryland↗

Digital mapping of ecological land units using a nationally scalable modeling framework

Ecological site descriptions (ESDs) and associated state-and-transition models (STMs) provide a nationally consistent classification and information system for defining ecological land units for management applications in the United States. Current spatial representations of ESDs, however, occur via soil mapping and are therefore confined to the spatial resolution used to map soils within a survey area. Land management decisions occur across a range of spatial scales and therefore require ecological information that spans similar scales. Digital mapping provides an approach for optimizing the spatial scale of modeling products to best serve decision makers and have the greatest impact in addressing land management concerns. Here, we present a spatial modeling framework for mapping ecological sites using machine learning algorithms, soil survey field observations, soil survey geographic databases, ecological site data, and a suite of remote sensing-based spatial covariates (e.g., hyper-temporal remote sensing, terrain attributes, climate data, land-cover, lithology). Based on the theoretical association between ecological sites and landscape biophysical properties, we hypothesized that the spatial distribution of ecological sites could be predicted using readily available geospatial data. This modeling approach was tested at two study areas within the western United States, representing 6.1 million ha on the Colorado Plateau and 7.5 million ha within the Chihuahuan Desert. Results show our approach was effective in mapping grouped ecological site classes (ESGs), with 10-fold cross-validation accuracies of 70% in the Colorado Plateau based on 1405 point observations across eight expertly-defined ESG classes and 79% in the Chihuahuan Desert based on 2589 point observations across nine expertly-defined ESG classes. Model accuracies were also evaluated using external-validation datasets; resulting in 56 and 44% correct classification for the Colorado Plateau and Chihuahuan Desert, respectively. National coverage of the training and covariate data used in this study provides opportunities for a consistent national-scale mapping effort of ecological sites.

Chihuahuan Desert, Colorado Plateau↗

Evaluation of the ground-water resources of coastal Georgia: preliminary report of the data available as of July 1983

A compilation of ground-water data that have been collected for nearly 100 years in the coastal area of Georgia is presented in this report. The compilation of pertinent data indicates what information is available for use in the evaluation of the ground-water resources of the 13 counties of coastal Georgia. Also included in this report is a fairly complete discussion of previous and ongoing investigations and monitoring networks, and an extensive list of references. Maps at 1:24,000 and 1:1,000,000 scales contain well locations and identifiers for all wells in the Ground Water Site Inventory (GWSI) data base of the National Water Data Storage and retrieval System (WATSTORE). Tabular summaries of selected site information from GWSI, including well identifiers and names, latitude-longitude location, depth of well, altitude of land surface, and use of water are presented. Water-use data from the National Water Use Data System, and water use for irrigation from the University of Georgia, Department of Agriculture survey, also are tabulated. Also included are pertinent information on geophysical surveys and data obtained, and proposed project activities, particularly test-monitor well drilling. The data in this report were collected and compiled as part of the cooperative activities between the U.S. Geological Survey and other agencies.

Georgia↗

Training data selection for annual land cover classification for the LCMAP initiative

The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative characterizes changes in land cover, use, and condition with the goal of producing land change information that improves understanding of the earth system and provides insight into the impacts of land change on society. For LCMAP, all available high-quality data from the Landsat archive is used in a time series approach to detect land surface change. Annual thematic land cover maps are produced by classifying time series models. In this paper, we describe optimization of the classification method used to derive the thematic land cover product. We investigated the influences of auxiliary data, sample size, and training from different sources such as the U.S. Geological Survey’s Land Cover Trends project and National Land Cover Database (NLCD 2001 and NLCD 2011). Results were evaluated and validated based on independent data from the training dataset. We found that refining auxiliary data effectively reduced artifacts in the thematic land cover map that are related to data availability (i.e., SLC-off). The classification accuracy and stability were improved considerably by using a total of 20 million training pixels with a minimum of 600,000 and a maximum of 8 million training pixels per class. Finally, the NLCD 2001 training data delivered the best classification accuracy. Comparing to the original LCMAP classification strategy (Trends training data, 20,000 samples), the optimized classification strategy considerably improved the annual land cover map accuracy.

Remote Sensing↗

Climate change and maple syrup: Producer observations, perceptions, knowledge, and adaptation strategies

Introduction: Climate change is impacting forest-based agricultural systems with implications for producer decision-making and livelihoods. This article presents a case study on the observations, perceptions, knowledge, and adaptation strategies of maple syrup producers in the United States to climate change. Methods: We carried out two semi-structured surveys with maple producers on: (1) climate change and its impacts on the maple system ( n = 106 participants); and (2) responses to climate adaptation scenarios ( n = 98 participants). Additionally, we carried out two focus groups and key informant interviews ( n = 70+) to understand barriers and opportunities for climate adaptation. One of these focus groups and follow up key informant interviews was with tribally affiliated community members with the intention to acknowledge Indigenous Peoples’ voices, history, and relationships to the land. Results: Findings highlight that most of the surveyed producers (89%) have experienced the negative impacts of climate on maple syrup production. While 40% of participants feel concerned regarding the future of the maple system, 39% feel hopeful, with significant differences based on the age of the surveyed producers. The majority of producers have adapted their harvesting practices to climate effects. Producers shared knowledge of multiple adaptation strategies in response to climate scenarios comprised of: (1) stand management practices such as diversification of sap species tapped; (2) harvesting practices such as changing the type and number of taps; (3) sap processing practices focused on the integration of technology such as the use of an evaporator and reverse osmosis; and (4) marketing practices such as innovation of products and marketing different maple syrup characteristics. Responses shared by tribally affiliated producers highlight knowledge of multiple adaptation strategies that focus on long-term ecological management of forests rather than technological solutions. Discussion: Overall, findings emphasize the importance of cooperation and diversification at every level and dimension of the maple system for its long-term resilience.

Frontiers in Forests and Global Change↗

Environmental Characteristics and Geographic Information System Applications for the Development of Nutrient Thresholds in Oklahoma Streams

The U.S.Environmental Protection Agency has developed nutrient criteria using ecoregions to manage and protect rivers and streams in the United States. Individual states and tribes are encouraged by the U.S. Environmental Protection Agency to modify or improve upon the ecoregion approach. The Oklahoma Water Resources Board uses a dichotomous process that stratifies streams using environmental characteristics such as stream order and stream slope. This process is called the Use Support Assessment Protocols, subchapter15. The Use Support Assessment Protocols can be used to identify streams threatened by excessive amounts of nutrients, dependant upon a beneficial use designation for each stream. The Use Support Assessment Protocols, subchapter 15 uses nutrient and environmental characteristic thresholds developed from a study conducted in the Netherlands, but the Oklahoma Water Resources Board wants to modify the thresholds to reflect hydrologic and ecological conditions relevant to Oklahoma streams and rivers. Environmental characteristics thought to affect impairment from nutrient concentrations in Oklahoma streams and rivers were determined for 798 water-quality sites in Oklahoma. Nutrient, chlorophyll, water-properties, and location data were retrieved from the U.S. Environmental Protection Agency STORET database including data from the U.S. Geological Survey, Oklahoma Conservation Commission, and Oklahoma Water Resources Board. Drainage-basin area, stream order, stream slope, and land-use proportions were determined for each site using a Geographic Information System. The methods, procedures, and data sets used to determine the environmental characteristics are described.

Water-Resources Investigations Report↗

Global land information system (GLIS) access to worldwide Landsat data

The Landsat Technical Working Group (LTWG) and the Landsat Ground Station Operations Working Group (LGSOWG) have encouraged Landsat receiving stations around the world to share information about their data holdings through the exchange of metadata records. Receiving stations forward their metadata records to the U.S. Geological Survey's EROS Data Center (EDC) on a quarterly basis. The EDC maintains the records for each station, coordinates changes to the database, and provides metadata to the stations as requested. The result is a comprehensive international database listing most of the world's Landsat data acquisitions This exchange of information began in the early 1980's with the inclusion in the EDC database os scenes acquired by a receiving station in Italy. Through the years other stations have agreed to participate; currently ten of the seventeen stations actively share their metadata records. Coverage maps have been generated to depict the status of the database. The Worldwide Landsat database is also available though the Global Land Information System (GLIS).

Pecora 12 Symposium↗

Water quality and landscape processes of four watersheds in eastern Puerto Rico

Humid tropical regions occupy about a quarter of Earth's land surface, yet they contribute a substantially higher fraction of the water, solutes, and sediment discharged to the world's oceans. Nearly half of Earth's population lives in the tropics, and development stresses can potentially harm soil resources, water quality, and water supply and in addition increase landslide and flood hazards. Owing to Puerto Rico's steep topography, low water storage capacity, and dependence on trade-wind precipitation, the island's people, ecosystems, and water supply are vulnerable to extreme weather such as hurricanes, floods, and droughts. Eastern Puerto Rico offers a natural laboratory for separating geologic and land-cover influences from regional- and global-scale influences because of its various bedrock types and the changing land cover surrounding intact, mature forest of the Luquillo Experimental Forest. Accordingly, a multiyear assessment of hydrological and biogeochemical processes was designed to develop an understanding of the effects of these differences on local climate, streamflow, water quality, and ecosystems, and to form the basis for a long-term and event-based program of climate and hydrologic monitoring. Because infrequent, large storms play a major role in this landscape, we focused on high-runoff events, sampling 263 storms, including all major hurricanes from 1991 through 2005. The largest storms have profound geomorphic consequences, such as landslides, debris flows, deep gullying on deforested lands, excavation and suspension of sediment in stream channels, and delivery of a substantial fraction of annual stream sediment load. Large storms sometimes entrain ocean foam and spray causing high concentrations of seasalt-derived constituents in stream waters during the storm. Past deforestation and agricultural activities in the Cayaguás and Canóvanas watersheds accelerated erosion and soil loss, and this material continues to be remobilized during large storms. Nearly 5,000 routine and event samples were analyzed for parameters that allow determination of denudation rates based on suspended and dissolved loads; 860 of these samples were analyzed for a comprehensive suite of chemical constituents. The rivers studied are generally similar in water-quality characteristics, and windward or leeward aspect appears to exert a stronger influence on water quality than geology or land cover. Of samples analyzed for comprehensive chemistry and for sediment, 543 were collected at runoff rates greater than 1 millimeter per hour, 256 at rates exceeding 10 millimeters per hour, and 3 at rates exceeding 90 millimeters per hour. Streams have rarely been sampled during events with such high runoff rates. Rates of physical and chemical weathering are especially high, and physical denudation rates, forested watersheds included, are considerably greater than is expected for a steady-state system. The elevated physical erosion drives an increased particulate organic carbon flux, one that is large, important to the carbon cycle, and sustainable, because soil-carbon regeneration is rapid. The 15-year Water, Energy, and Biogeochemical Budget dataset, which includes discharge, field parameters, suspended sediment, major cations and anions, and nutrients, is available from the U.S. Geological Survey's National Water Information System (http://waterdata.usgs.gov/nwis). The dataset provides a baseline for characterizing future environmental change and will improve our understanding of the interdependencies of land, water, and biological resources and their responses to changes in climate and land use. Because eastern Puerto Rico resembles many tropical regions in terms of geology and patterns of development, implications from this study are transferable to other tropical regions facing deforestation, rapid land-use change, and climate change.

Puerto Rico↗

Effects of urbanization on stream ecosystems along an agriculture-to-urban land-use gradient, Milwaukee to Green Bay, Wisconsin, 2003-2004

In 2003 and 2004, 30 streams near Milwaukee and Green Bay, Wisconsin, were part of a national study by the U.S. Geological Survey to assess urbanization effects on physical, chemical, and biological characteristics along an agriculture-to-urban land-use gradient. A geographic information system was used to characterize natural landscape features that define the environmental setting and the degree of urbanization within each stream watershed. A combination of land cover, socioeconomic, and infrastructure variables were integrated into a multi-metric urban intensity index, scaled from 0 to 100, and assigned to each stream site to identify a gradient of urbanization within relatively homogeneous environmental settings. The 35 variables used to develop the final urban intensity index characterized the degree of urbanization and included road infrastructure (road area and road traffic index), 100-meter riparian land cover (percentage of impervious surface, shrubland, and agriculture), watershed land cover (percentage of impervious surface, developed/urban land, shrubland, and agriculture), and 26 socioeconomic variables (U.S. Census Bureau, 2001). Characteristics examined as part of this study included: habitat, hydrology, stream temperature, water chemistry (chloride, sulfate, nutrients, dissolved and particulate organic and inorganic carbon, pesticides, and suspended sediment), benthic algae, benthic invertebrates, and fish. Semipermeable membrane devices (SPMDs) were used to assess the potential for bioconcentration of hydrophobic organic contaminants (specifically polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and organochlorine and pyrethroid insecticides) in biological membranes, such as the gills of fish. Physical habitat measurements reflective of channel enlargement, including bankfull channel size and bank erosion, increased with increasing urbanization within the watershed. In this study, percentage of riffles and streambed substrate size were more strongly related to local geologic setting, slope, watershed topography, and river-engineering practices than to urbanization. Historical local river-engineering features such as channelization, bank stabilization, and grade controls may have confounded relations among habitat characteristics and urbanization. A number of hydrologic-condition metrics (including flashiness and duration of high flow during pre- or post-ice periods) showed strong relations to the urban intensity index. Hydrologic-condition metrics cannot be used alone to predict habitat or geomorphic change. Chloride and SPMD measures of potential toxicity and polycyclic aromatic hydrocarbon concentrations showed the strongest positive correlations to urbanization including increases in road infrastructure, percentage of impervious surface in the watershed, urban land cover, and land-distribution related to urban land cover. This suggests that automobiles and the infrastructure required to support automobiles are a significant source of these compounds in this study area. Chloride in spring and summer showed a significant positive correlation with the urban intensity index; concentrations increased with increasing road infrastructure, urban land cover, and a number of landscape variables related to urbanization. Spring concentrations of sulfate, prometon, and diazinon correlated to fewer urban characteristics than chloride, including increases in road infrastructure, percentage of impervious surface, and urban land cover. Changes in biological communities correlated to the urban intensity index or individual urban-associated variables. Decreased percentages of pollution-sensitive diatoms and diatoms requiring high dissolved-oxygen saturation correlated to increases in the percentage of developed urban land, total impervious surface, stream flashiness, population density, road-area density, and decreases in the percentage of wetland in the watershed. Invertebrate taxa richness and Coleop

Scientific Investigations Report↗

U.S. Geological Survey 2024 Rocky Mountain Region Science Exchange—Showcasing cutting-edge science to adapt to extreme weather events and stakeholder needs

Introduction The Rocky Mountains and the Colorado River Basin in the Western United States are complex, interconnected systems that sustain a large variety of species, including tens of millions of humans. These regions face risks from drought, wildfires, invasive plant and animal species, and habitat reduction. Working with many stakeholders, scientists can help to characterize these risks by providing data and analytical tools to inform land and water resource management decisions. The U.S. Geological Survey 2024 Rocky Mountain Region (Region 7) Science Exchange Workshop, held in April 2024, focused on cutting-edge science techniques, evaluating complex interconnected risks, and coproducing science with science partners and stakeholders. These science topics and communication strategies can be used for developing data, interpretations, and decision support tools needed to provide science that resource managers and other stakeholders can use to better understand complex, dynamic natural systems and develop management strategies to plan for and adapt to risks that threaten human communities and natural ecosystems.

Fact Sheet↗

Historical land cover changes in the Great Lakes Region

Two different methods of reconstructing historical vegetation change, drawing on General Land Office (GLO) surveys and fossil pollen deposits, are demonstrated by using data from the Great Lakes region. Both types of data are incorporated into landscape-scale analyses and presented through geographic information systems. Results from the two methods reinforce each other and allow reconstructions of past landscapes at different time scales. Changes to forests of the Great Lakes region during the last 150 years were far greater than the changes recorded over the preceding 1,000 years. Over the last 150 years, the total amount of forested land in the Great Lakes region declined by over 40%, and much of the remaining forest was converted to early successional forest types as a result of extensive logging. These results demonstrate the utility of using GLO survey data in conjunction with other data sources to reconstruct a generalized 'presettlement' condition and assess changes in landcover.

Biological Science Report↗

Automated lidar-derived canopy height estimates for the Upper Mississippi River System

Land cover/land use (LCU) classifications serve as important decision support products for researchers and land managers. The LCU classifications produced by the U.S. Geological Survey’s Upper Midwest Environmental Sciences Center (UMESC) include canopy height estimates that are assigned through manual aerial photography interpretation techniques. In an effort to improve upon these techniques, this project investigated the use of high-density lidar data for the Upper Mississippi River System to determine canopy height. An ArcGIS tool was developed to automatically derive height modifier information based on the extent of land cover features for forest classes. The measurement of canopy height included a calculation of the average height from lidar point cloud data as well as the inclusion of a local maximum filter to identify individual tree canopies. Results were compared to original manually interpreted height modifiers and to field survey data from U.S. Forest Service Forest Inventory and Analysis plots. This project demonstrated the effectiveness of utilizing lidar data to more efficiently assign height modifier attributes to LCU classifications produced by the UMESC.

Minnesota, Wisconsin↗

EarthExplorer

The EarthExplorer trifold provides basic information for on-line access to remotely-sensed data from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center archive. The EarthExplorer (http://earthexplorer.usgs.gov/) client/server interface allows users to search and download aerial photography, satellite data, elevation data, land-cover products, and digitized maps. Minimum computer system requirements and customer service contact information also are included in the brochure.

General Information Product↗

Drain tiles and groundwater resources: Understanding the relations

Executive Summary Drainage for agricultural production over the past 150 years has been an integral component of human-driven change to Minnesota’s rural landscapes. Benefits of drainage Historically, poorly drained soils across much of the State would often remain saturated or flooded after spring snowmelt, preventing timely farm operations such as tilling and planting crops (Arneman, 1963). Installation of agricultural drainage, both surface ditches and subsurface drainage, accelerated transport of water off farm fields and imparted producers higher crop yields (Beauchamp, 1987; Stoner and others, 1993). Agricultural drainage offered many other benefits such as preventing crop drown out, aerating the soil profile for improved plant growth, limiting surface runoff and soil erosion, and allowing farmers better access to croplands (Fausey and others, 1987). Without agricultural drainage on much of Minnesota’s croplands, it would have been difficult to realize high enough crop yields to remain economically viable. Environmental concerns While drainage of Minnesota croplands provided the benefits mentioned above, several environmental concerns result. These include wetland loss, degradation of downstream water quality, and reduced [potential for] recharge. Early agricultural drainage efforts (pre-20th century) led to the disappearance of much of Minnesota’s natural wetlands. Increased focus on preventing or mitigating wetland loss over the last 50 years has helped curtail further losses, even as agricultural drainage proceeds. Prior to establishment of Minnesota statehood, wetlands accounted for more than 10 million acres in Minnesota, including prairie wetlands, peatlands, and forest wetlands that comprised approximately 19 percent of the total land area (Palmer, 1915; King, 1980). In 2018, only half of Minnesota’s pre-settlement wetlands remain, mostly in parts of the State that have not experienced widespread drainage, such as northern Minnesota. Water-quality monitoring has shown that agricultural drainage, in particular the practice of subsurface drainage, provides a direct flow path for nutrient (nitrogen and soluble phosphorus) losses to surface water resources. The negative consequences of agricultural drainage on surface water quality are well documented (for example, Dinnes and others, 2002; Kladivko and others, 2004; Richards and others, 2008; Rozemeijer and others, 2010; Schottler and others, 2013). Agricultural basins with a high percentage of agricultural drainage have been implicated as part of the cause of the Gulf of Mexico hypoxia zone due to excessive nitrogen export (Goolsby and Battaglin, 2001; Randall and Mulla, 2001). The connection of hydrological effects of agricultural subsurface drainage on groundwater recharge and aquifers, on the other hand, has not been well-established. Agricultural subsurface drainage intercepts infiltrating water below croplands and directly discharges the water to nearby surface waters. However, the size of the water balance shift from drained water that would have evapotranspired or run off the land to drained water that would recharge underlying aquifers has been poorly characterized (Schuh, 2008). Drain Tiles and Groundwater Given the poor accounting of subsurface drainage effects on groundwater resources, the Minnesota Ground Water Association (MGWA) deemed it imperative that we document these effects so that groundwater resources in agricultural regions with substantial drainage can be effectively managed. This white paper documents the relations of drain tiles and groundwater resources and discusses the historical significance of agricultural drainage practices, the recognized positive benefits and potential negative consequences of agricultural drainage practices, and the gaps in understanding of the connections between agricultural drainage and groundwater resources. The major messages emerged from the findings of this white paper are: Complex history. Minnesota has a long history of agricultural drainage, spanning over 150 years. Agricultural drainage, and the eventual widespread usage of subsurface drainage, can be separated into at least four distinct periods of time: (a) early drainage to get water off the land, pre-20th century; (b) the boom and bust era (1900-1945); (c) postwar resurgence of subsurface drainage and early conservation efforts (1945-1960); and, (d) emergence of the environmental movement (1960 to present). The State’s regulatory framework that both allowed for drainage and controlled its usage during these periods is complicated and has been governed by a patchwork of both State and Federal statutes. Drainage Provinces. This white paper advances the concept of tile drainage provinces to aid in the discussion of regional differences in subsurface drainage and its overall effect on groundwater resources. Built upon the concept of groundwater provinces (Minnesota Department of Natural Resources, 2001), three distinct tile drainage provinces were conceptualized: (1) the Southeastern Province; (2) the SouthCentral Province; and, (3) the Western Province. The distinct geology and the soils that developed in these regions have implications for each region’s subsurface drainage density and the potential implications for groundwater. Knowledge gaps. Several critical knowledge gaps are identified in this paper, creating opportunities for further research to improve our understanding for better managed water resources: Extent of drainage is unknown. Direct estimates of the extent of subsurface drainage do not exist in Minnesota. However, several indirect methods have been utilized to estimate subsurface drainage, from the field-scale to countylevel through the use of geographic information system (GIS) analysis and aerial photography. Based on a 2012 U.S. Geological Survey estimate of subsurface drainage extent (Nakagaki and Wieczorek, 2016), about 21% of the land area in Minnesota has some density of subsurface drainage. Effect of drainage on underlying aquifers is unknown. A basic understanding of unconfined and confined aquifers and their recharge is necessary to connect any hydrological effects from agricultural drainage to groundwater. The basic goal of subsurface drainage to efficiently drain saturated soils clearly alters the water balance in croplands. However, its overall effect on groundwater resources has been poorly characterized, and is in large part determined by the geology below drained areas and the arrangement of underlying aquifers. Water balance shifts. An improved understanding of historical water balance shifts from pre- to post-drainage periods is necessary to understand long-term implications on net groundwater recharge. Also, more direct field-scale studies and indirect modeling studies are needed to characterize water budgets for fields with subsurface drainage.

Minnesota↗

Map showing location of observation wells in Massachusetts and Rhode Island

This map shows the locations of the 136 observation wells from the observation-well network maintained by the U.S. Geological Survey in Massachusetts and Rhode Island. The wells are identified by town name and well number. The map shows the location of the 10 observation wells that have digital recorders and the 126 observation wells that are measured by local observers. The aquifer material (sand, till, or bedrock) in which a well is located is noted. County and town boundaries are shown on the map. These features are presented at a scale of 1:400,000 (map size is about 38 by 30 inches). The map includes textual information describing the uses of observation-well data. The information is organized by construction, water supply, water quality, and statistical analysis. The map also presents observation well information, which was obtained from the annual data report of the Massachusetts--Rhode Island District. This infor- mation is presented in tabular form and includes town name, well number, aquifer material in which the well is located, and well depth below the land surface. The map was produced from a digital data base using a Geographic Information System. State boundaries were generated from digital line graphs maintained by the U.S. Geological Survey. Town and county boundaries were digitized from stable-base materials maintained by State agencies. The map was prepared in cooperation with State agencies of Massachusetts and Rhode Island.

Massachusetts, Rhode Island↗

Median nitrate concentrations in groundwater in the New Jersey Highlands Region estimated using regression models and land-surface characteristics

Nitrate-concentration data are used in conjunction with land-use and land-cover data to estimate median nitrate concentrations in groundwater underlying the New Jersey (NJ) Highlands Region. Sources of data on nitrate in 19,670 groundwater samples are from the U.S. Geological Survey (USGS) National Water Information System (NWIS) and the NJ Private Well Testing Act (PWTA). In a study conducted by the USGS, in cooperation with the New Jersey Department of Environmental Protection, logistic regression was used to relate measured nitrate concentrations to five explanatory variables (percent urban and agricultural land use, septic-system density, total length of streams, and number of known contaminated sites) quantified in 610-meter-square grid cells. A method for calculating the median concentrations of nitrate from a series of logistic regression models was developed. Two calibration and two validation procedures showed that the logistic-regression-based method can estimate groundwater-nitrate concentrations in the Highlands Region accurately to within 0.1 milligram per liter as nitrogen (mg/L as N). Limitations of the logistic-regression-based method include the inability to select a logistic model with exactly 0.5 probability of exceeding the threshold value and lack of an algorithm to directly calculate the median value. Quantile regression was evaluated as a suitable alternative and was slightly less accurate than the logistic-regression method in estimating median groundwater nitrate concentrations in the Highlands Region. Multiple-linear regression with log-transformed nitrate-concentration data and the same five explanatory values was less accurate than either logistic or quantile regression in estimating median nitrate concentrations. On the basis of 4,516 2000 x 2000 foot grid cells that contain wells with data stored in NWIS and the PWTA database, the estimated median nitrate concentration for the entire Highlands Region is about 1.25 mg/L as N, and estimated median concentrations range from about 1.05 to 1.78 mg/L as N among 11 smaller administratively defined areas within the Highlands Region that vary in percentages of urban land use, agricultural land use, and septic-system density. The Kaplan-Meier method of estimating summary statistics from left-censored data was applied in order to include nondetects (left-censored data) in median nitrate-concentration calculations. Median concentrations also were determined using three alternative methods of handling nondetects. Treatment of the 23 percent of samples that were nondetects had little effect on estimated median nitrate concentrations because method detection limits were mostly less than median values.

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