Inundation observations and inundation model predictions for vernal pools of the northeastern United States
Dates
Publication Date
2020-04-28
Start Date
2004-05-01
End Date
2016-07-20
Citation
Cartwright, J., Morelli, T., and Grant, E., 2020, Inundation observations and inundation model predictions for vernal pools of the northeastern United States: U.S. Geological Survey data release, https://doi.org/10.5066/P9CP2NUD.
Summary
This data release includes data-processing scripts, data products, and associated metadata for a study to model the hydrology of several hundred vernal pools (i.e., seasonal pools or ephemeral wetlands) across the northeastern United States. More information on this study is available from the project website. This data release consists of several components: (1) an input dataset and associated metadata document ("pool_inundation_observations_and_climate_and_landscape_data"); (2) an annotated R script which processes the input dataset, performs inundation modeling, and generates model predictions ("annotated_R_script_for_pool_inundation_modeling.R"); and (3) a model prediction dataset and associated metadata document ("pool_inundation_predictions") [...]
Summary
This data release includes data-processing scripts, data products, and associated metadata for a study to model the hydrology of several hundred vernal pools (i.e., seasonal pools or ephemeral wetlands) across the northeastern United States. More information on this study is available from the project website. This data release consists of several components: (1) an input dataset and associated metadata document ("pool_inundation_observations_and_climate_and_landscape_data"); (2) an annotated R script which processes the input dataset, performs inundation modeling, and generates model predictions ("annotated_R_script_for_pool_inundation_modeling.R"); and (3) a model prediction dataset and associated metadata document ("pool_inundation_predictions") for the model predictions generated by the annotated R script. The inundation modeling procedures are explained in detail in the metadata documents and annotated R script and are described briefly here. The input dataset includes approximately 3,000 field observations of inundation from approximately 450 vernal pools located across the northeastern United States. Observations of inundated depth, length, and width for pools were collected between May and July, from 2004 through 2016. From these observations, four binary inundation metrics were constructed. The H1 metric classified pools as inundated if any amount of water was observed, i.e. inundated depth and area > 0. The H2, H3, and H4 metrics classified pools as inundated if they had inundated depth ≥ 5cm and area ≥ 5m2, depth ≥ 10cm and area ≥ 15m2, and depth ≥ 15cm and area ≥ 25m2, respectively. For each inundation metric (H1 through H4), boosted regression tree models were constructed using the inundation metric as the response variable and pool attributes, weather and climate variables, and landscape characteristics as explanatory variables. These models were then used to generate inundation predictions for the H1 through H4 metrics at several seasonal time points and under a variety of weather and climate scenarios.
This data release provides documentation of the data inputs, modeling procedures, and model predictions outputs of a study to model the hydrology of several hundred vernal pools across the northeastern United States.
Rights
Although these data have been used by the U.S. Geological Survey, U.S. Department of the Interior, no warranty expressed or implied is made by the U.S. Geological Survey as to the accuracy of the data and related materials. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the U.S. Geological Survey in the use of this data, software, or related materials. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
