Found 73 datasets matching "predictor variable".
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This data release includes three types of data used in habitat modeling, and predictions from the habitat models. (1) Predictor rasters for proportion urban development within 1-km radius,...
Search relevance: 85.26 | Views last month: 0 -
Please review Zhang et al. (2021) for details on study design and datasets (https://doi.org/10.1016/j.watres.2022.118443). In summary, predictor and response variable data was acquired from the...
Search relevance: 63.72 | Views last month: 0 -
This data release contains: (1) ASCII grids of predicted probability of elevated arsenic in groundwater for the Northwest and Central Minnesota regions, (2) input arsenic and predictive variable...
Search relevance: 53.07 | Views last month: 0 -
* This research used public drinking water nitrate violations data from across the conterminous United States as response variables, and various predictor variables from EPA's StreamCat dataset...
Search relevance: 51.44 | Views last month: 2 -
This data release contains data used to develop models and maps that estimate the occurrence of lithium in groundwater used as drinking water throughout the conterminous United States. An extreme...
Search relevance: 51.11 | Views last month: 9 -
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...
Search relevance: 47.65 | Views last month: 1 -
A three-dimensional extreme gradient boosting (XGB) machine learning model was developed to predict the distribution of nitrate in groundwater across the conterminous United States (CONUS)....
Search relevance: 47.65 | Views last month: 0 -
Data represent predicted cheatgrass (Bromus tectorum) cover from a quantile regression model. We used quantile regression to model cheatgrass abundance as a function of climate, weather, and...
Search relevance: 45.93 | Views last month: 1 -
This data release contains data used to develop models and maps that estimate probabilities of exceeding various thresholds of arsenic concentrations in private domestic wells throughout the...
Search relevance: 45.15 | Views last month: 0 -
This data release contains input data used in model development and TIF raster files used to predict the probability of high arsenic (As) and high manganese (Mn) in groundwater within the glacial...
Search relevance: 44.98 | Views last month: 0 -
This dataset contains the daily average base flow, as determined by hydrograph separation, for 14 watersheds in Gwinnett County, Georgia for October 2001 through September 2020. Hydrograph...
Search relevance: 44.78 | Views last month: 0 -
This data release consists of statistical predictions of daily salinity time series generated from the makESTUSAL software repository described by Asquith and others (2023b). The statistical...
Search relevance: 44.29 | Views last month: 0 -
The ascii grids associated with this data release are predicted distributions of continuous pH at the drinking water depth zones in the groundwater of Central Valley, California. The two...
Search relevance: 43.59 | Views last month: 2 -
Widespread nitrate contamination of groundwater in agricultural areas poses a major challenge to sustainable water resources. Efficient analysis of nitrate fluxes across large regions also remains...
Search relevance: 43.47 | Views last month: 0 -
We created a probabilistic classification model using the nonparametric machine learning technique 'Random Forests' for oil and gas development potential from low (0) to high (1) across the...
Search relevance: 43.42 | Views last month: 2 -
Although the TIMI (Thrombolysis In Myocardial Infarction) flow grade classification scheme is widely used to assess angiographic outcomes, it is limited by poor reproducibility and its categoric...
Search relevance: 43.01 | Views last month: 0 -
This data release contains model inputs, R code, and model outputs for predicting depth to bedrock in the Delaware River Basin at a 1km gridded resolution with a random forest model. Model inputs...
Search relevance: 42.32 | Views last month: 2 -
Species distribution models (SDMs) can be an important tool in rare species conservation. Specifically, SDMs have been used to location previously unknown populations and identify sites for...
Search relevance: 42.26 | Views last month: 0 -
The Mental Health Surveillance Study (MHSS) clinical follow-up was conducted as part of the National Survey on Drug Use and Health (NSDUH) from 2008 to 2012 for the primary purpose of developing...
Search relevance: 42.14 | Views last month: 0 -
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...
Search relevance: 41.80 | Views last month: 0
