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Filters: Tags: {"scheme":"Common geographic areas","name":"wisconsin"} (X) > Types: OGC WFS Layer (X) > Types: OGC WMS Service (X)

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This data set consists of monthly averages of soil and litter properties. Rows are grouped in the following order: year, month, vegetation type, plot ID. Within a single month five plots were sampled within each of the 2 vegetation types (10 plots total). Columns F+ represent individual measurements.
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The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
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Ecosystem metabolism is a measure of energy flow in terrestrial and aquatic environments that quantifies a balance between the rate of biomass production by photosynthesizing plants and the rate of biomass oxidation by respiring plants and animals to maintain and build living biomass. It is therefore a fundamental measure of ecosystem function that quantifies the balance between the rate of production, maintenance, and decay of organic matter. It also provides an understanding of energy flow to higher trophic levels that supports food webs with secondary and tertiary productivity. Furthermore, metabolism helps explain when aquatic ecosystems undergo out-of-balance behaviors such as hypoxia. Recent advances in sensor...
This data release contains input data used in model development and TIF raster files used to predict the probability of low dissolved oxygen (DO) and high dissolved iron (Fe) in groundwater within the glacial aquifer system in the northern continental United States. Input data include measured DO and Fe concentrations at groundwater wells, and associated predictor variable data. The probability of low DO and high Fe was predicted using boosted regression tree methods using the gbm package in R (v. 4.0.0) in RStudio (v. 1.2.5042). The response variables for individual models were the occurrence of: (1) DO ≤0.5 mg/L, (2) DO ≤2 mg/L, and (3) Fe >100 µg/L. Water-quality data were compiled from three sources, as described...
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A Groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). The GW-NDST relies on several support models, including machine-learning models that require numerous GIS input files. This data release contains all GIS files required to run the GW-NDST and its machine-learning support models. The GIS files are packaged into three ZIP files (WI_County.zip, WT-ML.zip, and WI_Buff1km.zip) which are contained in this data release. Before running the GW-NDST, these ZIP...
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A histrogram-based boosted regression tree (HBRT) method was used to predict the depth to the surficial aquifer water table (in feet) throughout the State of Wisconsin. This method used a combination of discrete groundwater levels from the U.S. Geological Survey National Water Information System, continuous groundwater levels from the National Groundwater Monitoring Network, the State of Wisconsin well-construction database, and NHDPlus version 2.1-derived points. The predicted water table depth utilized the HBRT model available through Scikit-learn in Python version 3.10.10. The HBRT model can predict the surficial water table depth for any latitude and longitude for Wisconsin. A total of 48 predictor variables...
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A groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). The GW-NDST relies on an ensemble of calibrated parameters to make nitrate predictions and to estimate the uncertainty of those predictions. This data release contains all of the calibrated parameter files required to run the tool. The files are packaged in a single ZIP file. To run the tool, the ZIP package needs to be downloaded and extracted within the pest/ies_parameter_ensembles/ subdirectory...
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This data release provides computed rainfall (rain total, duration, intensity, erosivity and antecedent rainfall) and flow (flow volume, flow-weighted mean concentrations, total loads, and total yields) metrics from monitored precipitation, discharge, and water quality (nutrients and sediment concentrations) data collected at U.S. Geological Survey edge-of-field (EOF) monitoring sites located in five Great Lakes States (Wisconsin, Michigan, Ohio, Indiana, and New York). EOF monitoring sites are installed at the edge of agricultural fields, either on the field surface or using subsurface tiles, where runoff can be intercepted and channeled through monitoring equipment before it enters the natural stream system. These...
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This dataset represents results from this study attributed to the NHDPlus V2 catchments. Changes in climate occurring throughout the Mississippi River Basin are expected to lead to additional impacts in stream habitats and fish assemblages in multiple ways, including changing changing thermal properties and flow regimes. To manage streams for current impacts and future changes, managers need region-wide information for decision-making and developing proactive management strategies. Our project provides a suite of climate metrics that have been found to be relevant to the distribution and population structure of aquatic organisms in freshwater stream networks. These results provide natural resource managers, decision-makers,...
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Academics & scientific researchers, Alabama, Alabama, Arkansas, Arkansas, All tags...
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Ecosystem metabolism is a measure of energy flow in terrestrial and aquatic environments that quantifies a balance between the rate of biomass production by photosynthesizing plants and the rate of biomass oxidation by respiring plants and animals to maintain and build living biomass. It is therefore a fundamental measure of ecosystem function that quantifies the balance between the rate of production, maintenance, and decay of organic matter. It also provides an understanding of energy flow to higher trophic levels that supports food webs with secondary and tertiary productivity. Furthermore, metabolism helps explain when aquatic ecosystems undergo out-of-balance behaviors such as hypoxia. Recent advances in sensor...
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Residence time distribution (RTD) is a critically important characteristic of groundwater flow systems; however, it cannot be measured directly. RTD can be inferred from tracer data with analytical models (few parameters) or with numerical models (many parameters). The second approach permits more variation in system properties but is used less frequently than the first because large-scale numerical models can be resource intensive. With the data and computer codes in this data release users can (1) reconstruct and run 115 General Simulation Models (GSMs) of groundwater flow, (2) calculate groundwater age metrics at selected GSM cells, (3) train a boosted regression tree model using the provided data, (4) predict...
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The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
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A Groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). Running and using the GW-NDST software involves downloading the software code (version 1.1.0) from the code repository (https://doi.org/10.5066/P13ETB4Q), downloading GIS data for the machine learning support models (child data release "GIS files required to run the Groundwater Nitrate Decision Support Tool for Wisconsin"), downloading the parameter uncertainty file (child data release "Parameter ensemble...
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A multivariate regression model was developed to predict zero-order oxygen reduction rates (mg/L/yr) in aquifers across the State of Wisconsin. The model used a combination of dissolved oxygen concentrations and mean groundwater ages estimated with sampled age tracers from wells in the U.S. Geological Survey National Water Information System and previously published project reports from state agencies and universities. The multivariate regression model was solved using the Microsoft Excel solver, with 461 wells used for training and 46 wells held-out for validation. A total of 31 predictor variables were used for model development (56 were tested), including basic well characteristics, soil properties, aquifer properties,...
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Green and others (2021) developed a gradient boosted regression tree model to predict the mean groundwater age, or travel time, for shallow wells across a portion of the Great Lakes basin in the United States. Their study applied machine learning methods to predict ages in wells using well construction, well chemistry, and landscape characteristics. For a dataset of age tracers in 961 water samples, the mean travel time from the land surface to the sample location (center of saturated open interval) was estimated for each sample using parametric functions. The mean travel times were then modeled using a gradient boosting machine algorithm with cross validation tuning of model hyperparameters. The model contained...
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Ecosystem metabolism is a measure of energy flow in terrestrial and aquatic environments that quantifies a balance between the rate of biomass production by photosynthesizing plants and the rate of biomass oxidation by respiring plants and animals to maintain and build living biomass. It is therefore a fundamental measure of ecosystem function that quantifies the balance between the rate of production, maintenance, and decay of organic matter. It also provides an understanding of energy flow to higher trophic levels that supports food webs with secondary and tertiary productivity. Furthermore, metabolism helps explain when aquatic ecosystems undergo out-of-balance behaviors such as hypoxia. Recent advances in sensor...
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In response to Executive Order 13817 of December 20, 2017, the U.S. Geological Survey (USGS) coordinated with the Bureau of Land Management (BLM) to identify 35 nonfuel minerals or mineral materials considered critical to the economic and national security of the United States (U.S.) (https://pubs.usgs.gov/of/2018/1021/ofr20181021.pdf). Acquiring information on possible domestic sources of these critical minerals is the rationale for the USGS Earth Mapping Resources Initiative (Earth MRI). The program, which partners the USGS with State Geological Surveys, federal agencies, and the private sector, aims to collect new geological, geophysical, and topographic (lidar) data in key areas of the U.S. to stimulate mineral...
Categories: Data, Data Release - Revised; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Alabama, Alaska, Arizona, Arkansas, California, All tags...
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Wind fetch is defined as the unobstructed distance that wind can travel over water in a constant direction. Fetch is an important characteristic of open water because longer fetch can result in larger wind-generated waves. The larger waves, in turn, can increase shoreline erosion and sediment re-suspension. Wind fetches were calculated using the wind fetch model available from (http://www.umesc.usgs.gov/management/dss/wind_fetch_wave_models_2012update.html) for aquatic areas within the Upper Mississippi River System. This toolbox calculates effective wind fetch using the recommended procedure of the Shore Protection Manual (USACE 1984). A baseline conditions assessment of wind fetch was conducted to assist the...
map background search result map search result map Spatial and temporal relationships between the invasive snail Bithynia tentaculata and submersed aquatic vegetation in Pool 8 of the Upper Mississippi River data Effects of Flood Inundation and Invasion by Phalaris arundinacea on Nitrogen Cycling in an Upper Mississippi River Floodplain Forest data Effects of flood inundation, invasion by Phalaris arundinacea, and nitrogen enrichment on extracellular enzyme activity in an Upper Mississippi River floodplain forest: Data Data: Current and future CCCma CGCM3.1 climate data for NHD v2 catchments within the Mississippi River Basin Groundwater data, predictor variables, and rasters used for predicting redox conditions in the glacial aquifer, northern continental United States Data for three-dimensional distribution of groundwater residence time metrics in the glaciated United States using metamodels trained on general numerical simulation models GIS for focus areas of potential domestic resources of 11 critical minerals—aluminum, cobalt, graphite, lithium, niobium, platinum group elements, rare earth elements, tantalum, tin, titanium, and tungsten (version 2.0, August 2020) Mapped differences in weighted wind fetch distances within the Upper Mississippi River System between 1989 and 2000 Nutrient and sediment concentrations, loads, yields, and rainfall characteristics at USGS surface and subsurface-tile edge-of-field agricultural monitoring sites in Great Lakes States (ver. 2.1, September 2023) Data to support a Groundwater Nitrate Decision Support Tool for Wisconsin Python-HBRT model and groundwater levels used for estimating the static, shallow water table depth for the State of Wisconsin UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 13 South UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 13 RiverMET: Workflow and scripts for river metabolism estimation including Illinois River Basin application, 2005 - 2020 (Input data for) RiverMET: Workflow and scripts for river metabolism estimation including Illinois River Basin application, 2005 - 2020 (Output files from) RiverMET: Workflow and scripts for river metabolism estimation including Illinois River Basin application, 2005 - 2020 Multivariate regression model for predicting oxygen reduction rates in groundwater for the State of Wisconsin GIS files required to run the Groundwater Nitrate Decision Support Tool for Wisconsin Parameter ensemble files required to run the Groundwater Nitrate Decision Support Tool for Wisconsin Histogram-based gradient boosted regression tree model of mean ages of shallow well samples in the Great Lakes Basin, USA UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 13 South Spatial and temporal relationships between the invasive snail Bithynia tentaculata and submersed aquatic vegetation in Pool 8 of the Upper Mississippi River data Effects of Flood Inundation and Invasion by Phalaris arundinacea on Nitrogen Cycling in an Upper Mississippi River Floodplain Forest data UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 13 RiverMET: Workflow and scripts for river metabolism estimation including Illinois River Basin application, 2005 - 2020 (Input data for) RiverMET: Workflow and scripts for river metabolism estimation including Illinois River Basin application, 2005 - 2020 (Output files from) RiverMET: Workflow and scripts for river metabolism estimation including Illinois River Basin application, 2005 - 2020 Python-HBRT model and groundwater levels used for estimating the static, shallow water table depth for the State of Wisconsin Data to support a Groundwater Nitrate Decision Support Tool for Wisconsin Multivariate regression model for predicting oxygen reduction rates in groundwater for the State of Wisconsin Parameter ensemble files required to run the Groundwater Nitrate Decision Support Tool for Wisconsin GIS files required to run the Groundwater Nitrate Decision Support Tool for Wisconsin Mapped differences in weighted wind fetch distances within the Upper Mississippi River System between 1989 and 2000 Nutrient and sediment concentrations, loads, yields, and rainfall characteristics at USGS surface and subsurface-tile edge-of-field agricultural monitoring sites in Great Lakes States (ver. 2.1, September 2023) Effects of flood inundation, invasion by Phalaris arundinacea, and nitrogen enrichment on extracellular enzyme activity in an Upper Mississippi River floodplain forest: Data Histogram-based gradient boosted regression tree model of mean ages of shallow well samples in the Great Lakes Basin, USA Data: Current and future CCCma CGCM3.1 climate data for NHD v2 catchments within the Mississippi River Basin Data for three-dimensional distribution of groundwater residence time metrics in the glaciated United States using metamodels trained on general numerical simulation models Groundwater data, predictor variables, and rasters used for predicting redox conditions in the glacial aquifer, northern continental United States GIS for focus areas of potential domestic resources of 11 critical minerals—aluminum, cobalt, graphite, lithium, niobium, platinum group elements, rare earth elements, tantalum, tin, titanium, and tungsten (version 2.0, August 2020)