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Inputs and Selected Predictions of the CBTN v5 and CBTP v5 SPARROW Models for the Chesapeake Bay Watershed
The CBTN_v5 and CBTP_v5 SPARROW models were developed to support inferences about causes of observed changes in nitrogen and phosphorus (respectively) fluxes in Chesapeake Bay tributaries between 1992 and 2012. Model inputs and outputs are included in three files, which are described below. Detailed documentation of the SPARROW modeling technique is available at https://pubs.er.usgs.gov/publication/tm6B3.
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SPARROW model input datasets and predictions of nitrogen loads in streams of the Chesapeake Bay watershed
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This data release contains mean-annual total nitrogen (TN) loads predicted by a SPARROW model for individual stream and shoreline reaches in the Chesapeake watershed as defined by NHDPlus, a 1:100,000 scale representation of stream hydrography built upon the National Hydrography Dataset (NHD) (Horizon Systems, 2010). Also included are the input variables required to execute the model, including landscape characteristics, nutrient inputs to land, and calibration data from water quality monitoring stations. Further details on model construction and results are described in Ator (2011, https://doi.org/10.3133/sir20115167).
SPARROW model input datasets and predictions of nitrogen loads in streams of the Chesapeake Bay watershed
공공데이터포털
This data release contains mean-annual total nitrogen (TN) loads predicted by a SPARROW model for individual stream and shoreline reaches in the Chesapeake watershed as defined by NHDPlus, a 1:100,000 scale representation of stream hydrography built upon the National Hydrography Dataset (NHD) (Horizon Systems, 2010). Also included are the input variables required to execute the model, including landscape characteristics, nutrient inputs to land, and calibration data from water quality monitoring stations. Further details on model construction and results are described in Ator (2011, https://doi.org/10.3133/sir20115167).
SPARROW model input datasets and predictions for predicting near-term effects of climate change on nitrogen transport to Chesapeake Bay
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This data release includes 5 files containing model inputs and resulting model predictions. A previously-calibrated spatially referenced regression (SPARROW) model was used to estimate effects of climate change on in-stream nitrogen (TN) loads in the Chesapeake Bay watershed between 1995 and 2025. Model scenarios were run using data for nitrogen sources and landscape characteristics from 2012, changing only temperature and runoff using climate change predictions to evaluate the change in climate on TN loads. Confidence intervals for model output predictions are also included.
SPARROW model input datasets and predictions for predicting near-term effects of climate change on nitrogen transport to Chesapeake Bay
공공데이터포털
This data release includes 5 files containing model inputs and resulting model predictions. A previously-calibrated spatially referenced regression (SPARROW) model was used to estimate effects of climate change on in-stream nitrogen (TN) loads in the Chesapeake Bay watershed between 1995 and 2025. Model scenarios were run using data for nitrogen sources and landscape characteristics from 2012, changing only temperature and runoff using climate change predictions to evaluate the change in climate on TN loads. Confidence intervals for model output predictions are also included.
Inputs and Selected Predictions of a Differential Spatially Referenced Regression Model for 20-year Changes in Total Nitrogen in the Chesapeake Bay Watershed
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The core equations of the SPARROW model (Schwarz and others, 2006) were implemented in differential form using the R programming language (R Core Team, 2017), as the basis of a tool for empirically relating a regional pattern of changes in constituent flux, over a multi-year period, to spatially referenced changes in explanatory variables over the same period. A pilot implementation was developed to explore factors influencing changes in flow-normalized flux of total nitrogen (TN) over the period 1990-2010 at 43 sites in the non-tidal Chesapeake Bay watershed. Model inputs, outputs, and code are included in this data release, and are described below.
Inputs and Selected Predictions of a Differential Spatially Referenced Regression Model for 20-year Changes in Total Nitrogen in the Chesapeake Bay Watershed
공공데이터포털
The core equations of the SPARROW model (Schwarz and others, 2006) were implemented in differential form using the R programming language (R Core Team, 2017), as the basis of a tool for empirically relating a regional pattern of changes in constituent flux, over a multi-year period, to spatially referenced changes in explanatory variables over the same period. A pilot implementation was developed to explore factors influencing changes in flow-normalized flux of total nitrogen (TN) over the period 1990-2010 at 43 sites in the non-tidal Chesapeake Bay watershed. Model inputs, outputs, and code are included in this data release, and are described below.
Input and results from a boosted regression tree (BRT) model relating base flow nitrate concentrations in the Chesapeake Bay watershed to catchment characteristics (1970-2013)
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This data release contains a boosted regression tree (BRT) model (written in the R programming language), and the input and output data from that model that were used to relate base flow nitrate concentrations in the Chesapeake Bay watershed to catchment characteristics. The input data consists of two types of information: 1) surface water nitrate concentrations collected by the USGS and partnering agencies in the Chesapeake Bay watershed between 1970 and 2013 and 2) potential predictor variables that included nitrogen sources, catchment characteristics, soil and groundwater chemistry, soil drainage and composition, and aquifer geology. The results from the BRT model were used to identify ten significant predictors of base flow nitrate concentrations in streams in the Chesapeake Bay watershed.
Input and results from a boosted regression tree (BRT) model relating base flow nitrate concentrations in the Chesapeake Bay watershed to catchment characteristics (1970-2013)
공공데이터포털
This data release contains a boosted regression tree (BRT) model (written in the R programming language), and the input and output data from that model that were used to relate base flow nitrate concentrations in the Chesapeake Bay watershed to catchment characteristics. The input data consists of two types of information: 1) surface water nitrate concentrations collected by the USGS and partnering agencies in the Chesapeake Bay watershed between 1970 and 2013 and 2) potential predictor variables that included nitrogen sources, catchment characteristics, soil and groundwater chemistry, soil drainage and composition, and aquifer geology. The results from the BRT model were used to identify ten significant predictors of base flow nitrate concentrations in streams in the Chesapeake Bay watershed.
Input and predictions from a suspended-sediment SPARROW model CBSS V2 in the Chesapeake Bay watershed. U.S. Geological Survey data release
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These data represent both inputs for and estimates from a medium-resolution (1:100,000 scale) NHDPlus SPAtially Referenced Regression on Watershed attributes (SPARROW) model for the Chesapeake Bay watershed (CBSS_v2). The model spatially correlates long-term mean annual suspended-sediment flux in 113 non-tidal streams to likely upland and stream-corridor sources, landscape factors affecting upland sediment transport and delivery to stream corridors, and fluvial and reservoir retention representing the early 2000 time period. The item COMID is a common related field between the data file and the spatial component (catchments) in NHDPlus version 1.0.
Input and predictions from a suspended-sediment SPARROW model CBSS V2 in the Chesapeake Bay watershed. U.S. Geological Survey data release
공공데이터포털
These data represent both inputs for and estimates from a medium-resolution (1:100,000 scale) NHDPlus SPAtially Referenced Regression on Watershed attributes (SPARROW) model for the Chesapeake Bay watershed (CBSS_v2). The model spatially correlates long-term mean annual suspended-sediment flux in 113 non-tidal streams to likely upland and stream-corridor sources, landscape factors affecting upland sediment transport and delivery to stream corridors, and fluvial and reservoir retention representing the early 2000 time period. The item COMID is a common related field between the data file and the spatial component (catchments) in NHDPlus version 1.0.
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