Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. The medusahead phenology in the Snake River Plain (SRP) and Northern Basin and Range (NBR) based on 30m near seamless Harmonized Landsat and Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) weekly composites between 2016 and 2022 (Dahal et al., 2022) were processed using a 3 step method. We first identified a set of points to derive an HLS NDVI timeseries based on high probability of cheatgrass and medusahead cover. Second, we extracted the phenological metrics used for training the models by applying a decision tree processing technique on the NDVI timeseries. Finally, we utilized automated machine learning techniques to derive phenological models that were used to develop maps for the entire study area per 30-m pixel. The medusahead phenology model produced three metrics (Start of Season Time (SOST), End of Season Time (EOST), and Maximum Time (MAXT)) and calculated five metrics for identifying the sustained growth characteristics of medusahead throughout SRP and NBR ecoregions. The current suites of 30-m spatial resolution phenological metrics are SOST; Start of Season NDVI (SOSN); EOST; End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); and Amplitude (AMP). Datasets 2017 to 2021 were developed using decision tree analysis training data from their respective year, but 2022 was developed from unseen NDVI datasets to test robustness of the phenology model. References: Dahal, D.; Pastick, N.J.; Boyte, S.P.; Parajuli, S.; Oimoen, M.J.; Megard, L.J. Multi-Species Inference of Exotic Annual and Native Perennial Grasses in Rangelands of the Western United States Using Harmonized Landsat and Sentinel-2 Data. Remote Sensing 2022, 14, doi:10.3390/rs14040807.

Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. The cheatgrass phenology in the Snake River Plain (SRP) and Northern Basin and Range (NBR) based on 30m near seamless Harmonized Landsat and Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) weekly composites between 2016 and 2022 (Dahal et al., 2022) were processed using a 3 step method. We first identified a set of points to derive an HLS NDVI timeseries based on high probability of cheatgrass and medusahead cover. Second, we extracted the phenological metrics used for training the models by applying a decision tree processing technique on the NDVI timeseries. Finally, we utilized automated machine learning techniques to derive phenological models that were used to develop maps for the entire study area per 30-m pixel. The cheatgrass phenology model produced three metrics (Start of Season Time (SOST), End of Season Time (EOST), and Maximum Time (MAXT)) and calculated five metrics for identifying the sustained growth characteristics of cheatgrass throughout SRP and NBR ecoregions. The current suites of 30-m spatial resolution phenological metrics are SOST; Start of Season NDVI (SOSN); EOST; End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); and Amplitude (AMP). Datasets 2017 to 2021 were developed using decision tree analysis training data from their respective year, but 2022 was developed from unseen NDVI datasets to test robustness of the phenology model. References: Dahal, D.; Pastick, N.J.; Boyte, S.P.; Parajuli, S.; Oimoen, M.J.; Megard, L.J. Multi-Species Inference of Exotic Annual and Native Perennial Grasses in Rangelands of the Western United States Using Harmonized Landsat and Sentinel-2 Data. Remote Sensing 2022, 14, doi:10.3390/rs14040807.

Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. The cheatgrass phenology in the Snake River Plain (SRP) and Northern Basin and Range (NBR) based on 30m near seamless Harmonized Landsat and Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) weekly composites between 2016 and 2022 (Dahal et al., 2022) were processed using a 3 step method. We first identified a set of points to derive an HLS NDVI timeseries based on high probability of cheatgrass and medusahead cover. Second, we extracted the phenological metrics used for training the models by applying a decision tree processing technique on the NDVI timeseries. Finally, we utilized automated machine learning techniques to derive phenological models that were used to develop maps for the entire study area per 30-m pixel. The cheatgrass phenology model produced three metrics (Start of Season Time (SOST), End of Season Time (EOST), and Maximum Time (MAXT)) and calculated five metrics for identifying the sustained growth characteristics of cheatgrass throughout SRP and NBR ecoregions. The current suites of 30-m spatial resolution phenological metrics are SOST; Start of Season NDVI (SOSN); EOST; End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); and Amplitude (AMP). Datasets 2017 to 2021 were developed using decision tree analysis training data from their respective year, but 2022 was developed from unseen NDVI datasets to test robustness of the phenology model. References: Dahal, D.; Pastick, N.J.; Boyte, S.P.; Parajuli, S.; Oimoen, M.J.; Megard, L.J. Multi-Species Inference of Exotic Annual and Native Perennial Grasses in Rangelands of the Western United States Using Harmonized Landsat and Sentinel-2 Data. Remote Sensing 2022, 14, doi:10.3390/rs14040807.

Phenological dynamics reflect the vegetation response to changes in weather, vegetation composition, plant life stages pertinent to both agricultural and fire management and are thus important to monitor operationally. The Exotic Annual Grass (EAG) phenology in the western U.S. rangeland based on 30-m Harmonized Landsat and Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) weekly composites between 2016 and 2024 (Dahal et al., 2022) were processed using these 3 methods: (1) NDVI threshold-based method, (2) manual phenological metrics, and (3) modeling and mapping. The EAG phenology model produced two metrics (Start of Season Time [SOST] and End of Season Time [EOST]) and calculated six metrics for identifying the sustained growth characteristics of 15 EAG species throughout 190 million hectares of western U.S. rangeland for 2017 to 2024. The current suite of phenological metrics are SOST; Start of Season NDVI (SOSN); EOST; End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); and Amplitude (AMP). Datasets from 2017 to 2021 were developed using manually interpreted training data specific to each year, while datasets from 2022 to 2024 were produced using the same training set supplemented with additional automated datasets. References: Dahal, D.; Pastick, N.J.; Boyte, S.P.; Parajuli, S.; Oimoen, M.J.; Megard, L.J. Multi-Species Inference of Exotic Annual and Native Perennial Grasses in Rangelands of the Western United States Using Harmonized Landsat and Sentinel-2 Data. Remote Sensing 2022, 14, doi:10.3390/rs14040807.

Phenological dynamics reflect the vegetation response to changes in weather, vegetation composition, plant life stages pertinent to both agricultural and fire management and are thus important to monitor operationally. The Exotic Annual Grass (EAG) phenology in the western U.S. rangeland based on 30-m Harmonized Landsat and Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) weekly composites between 2016 and 2024 (Dahal et al., 2022) were processed using these 3 methods: (1) NDVI threshold-based method, (2) manual phenological metrics, and (3) modeling and mapping. The EAG phenology model produced two metrics (Start of Season Time [SOST] and End of Season Time [EOST]) and calculated six metrics for identifying the sustained growth characteristics of 15 EAG species throughout 190 million hectares of western U.S. rangeland for 2017 to 2024. The current suite of phenological metrics are SOST; Start of Season NDVI (SOSN); EOST; End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); and Amplitude (AMP). Datasets from 2017 to 2021 were developed using manually interpreted training data specific to each year, while datasets from 2022 to 2024 were produced using the same training set supplemented with additional automated datasets. References: Dahal, D.; Pastick, N.J.; Boyte, S.P.; Parajuli, S.; Oimoen, M.J.; Megard, L.J. Multi-Species Inference of Exotic Annual and Native Perennial Grasses in Rangelands of the Western United States Using Harmonized Landsat and Sentinel-2 Data. Remote Sensing 2022, 14, doi:10.3390/rs14040807.

Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. The Exotic Annual Grass (EAG) phenology in the western U.S. rangeland based on 30m near seamless Harmonized Landsat and Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) weekly composites between 2016 and 2023 (Dahal et al., 2022) were processed using these 3 methods: (1) NDVI threshold-based method, (2) manual phenological metrics, and (3) modeling and mapping. The EAG phenology model produced two metrics (Start of Season Time (SOST) and End of Season Time (EOST)) and calculated six metrics for identifying the sustained growth characteristics of 16 EAG species throughout level III Commission for Environmental Cooperation ecoregions, which cover over 190 million hectares of western U.S. potential rangeland for 2017 to 2021. The current suites of 30-m spatial resolution phenological metrics are SOST; Start of Season NDVI (SOSN); EOST; End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); and Amplitude (AMP). Datasets 2017 to 2021 were developed using manually interpreted training data from their respective year, but 2022 and 2023 was developed from unseen NDVI datasets to test robustness of the phenology model. References: Dahal, D.; Pastick, N.J.; Boyte, S.P.; Parajuli, S.; Oimoen, M.J.; Megard, L.J. Multi-Species Inference of Exotic Annual and Native Perennial Grasses in Rangelands of the Western United States Using Harmonized Landsat and Sentinel-2 Data. Remote Sensing 2022, 14, doi:10.3390/rs14040807.

This data set represents basin characteristics, compiled for every catchment in NHDPlus for the conterminous United States. These characteristics are basin shape index, stream density, sinuosity, mean elevation, mean slope, and number of road-stream crossings. The source data sets are the U.S. Environmental Protection Agency's NHDPlus and the U.S. Census Bureau's TIGER/Line Files. The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. The Exotic Annual Grass (EAG) phenology in the western U.S. rangeland based on 30m near seamless Harmonized Landsat and Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) weekly composites between 2016 and 2021 (Dahal et al., 2022) were processed using these 3 methods: (1) NDVI threshold-based method, (2) manual phenological metrics, and (3) modeling and mapping. The EAG phenology model produced eight metrics identifying the sustainable growth characteristics of 16 EAG species throughout level III Commission for Environmental Cooperation ecoregions, which cover over 190 million hectares of western U.S. potential rangeland for 2017 to 2021. The current suites of 30-m spatial resolution phenological metrics are Start of Season Time (SOST); Start of Season NDVI (SOSN); End of Season Time (EOST); End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); and Amplitude (AMP). Datasets 2017 to 2020 were developed using manually interpreted training data from their respective year, but 2021 was developed from unseen NDVI datasets to test robustness of the phenology model. References: Dahal, D.; Pastick, N.J.; Boyte, S.P.; Parajuli, S.; Oimoen, M.J.; Megard, L.J. Multi-Species Inference of Exotic Annual and Native Perennial Grasses in Rangelands of the Western United States Using Harmonized Landsat and Sentinel-2 Data. Remote Sensing 2022, 14, doi:10.3390/rs14040807.

Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. The Exotic Annual Grass (EAG) phenology in the western U.S. rangeland based on 30m near seamless Harmonized Landsat and Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) weekly composites between 2016 and 2021 (Dahal et al., 2022) were processed using these 3 methods: (1) NDVI threshold-based method, (2) manual phenological metrics, and (3) modeling and mapping. The EAG phenology model produced eight metrics identifying the sustainable growth characteristics of 16 EAG species throughout level III Commission for Environmental Cooperation ecoregions, which cover over 190 million hectares of western U.S. potential rangeland for 2017 to 2021. The current suites of 30-m spatial resolution phenological metrics are Start of Season Time (SOST); Start of Season NDVI (SOSN); End of Season Time (EOST); End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); and Amplitude (AMP). Datasets 2017 to 2020 were developed using manually interpreted training data from their respective year, but 2021 was developed from unseen NDVI datasets to test robustness of the phenology model. References: Dahal, D.; Pastick, N.J.; Boyte, S.P.; Parajuli, S.; Oimoen, M.J.; Megard, L.J. Multi-Species Inference of Exotic Annual and Native Perennial Grasses in Rangelands of the Western United States Using Harmonized Landsat and Sentinel-2 Data. Remote Sensing 2022, 14, doi:10.3390/rs14040807.

A three-dimensional groundwater flow model, MODFLOW-NWT, was developed to simulate saturated groundwater hydrology, streamflow, and groundwater/surface-water interaction within the Colorado Plateau principal aquifer system. The model was used to evaluate and compare the hydrologic responses of groundwater and streamflow to natural and anthropogenic drivers of change between a recent wet period (1982-1999) and drought period (2000-2022) for four headwater subregions in the Upper Colorado River Basin. This child item contains all of the MODFLOW-NWT input and output files for the simulations described in the associated journal article (https://doi.org/10.1016/j.ejrh.2025.102554).