Derived climatic variables based on the historical and future simulations of ten Global Climate Models.

Projected wetland densities under 10 different climate models and 3 land use and land cover scenarios. This file contains projected wetland densities under each combination of land use and climate.

Projected wetland densities under 10 different climate models and 3 land use and land cover scenarios. This file contains projected wetland densities under each combination of land use and climate.

This data release presents input data for plot- and landscape-scale models of Prairie Pothole Region wetland methane emissions as a function of explanatory variables and remotely sensed predictors. Field data for the plot- and landscape-scale models span the years 2003-2016 and 2005-2016, respectively. The data release also includes R programming code to run the generalized additive model (GAM; plot scale) and random forest (RF; landscape scale) model of methane flux rates. Input data were extracted and modified from existing sources, and combined to facilitate model development, as well as six scenario-based model runs (two historical, four future). Briefly, a bottom-up approach was used to develop a spatially explicit, temporally dynamic model of methane emissions from Prairie Pothole Region (PPR) wetlands. A dataset of greater than 18,000 static-chamber flux measurements along with environmental covariates was used to develop a chamber-based (plot) model of methane flux, which was then used to inform a landscape-model using remotely sensed predictors. Covariates for the chamber-based model included soil water-filled pore space, soil temperature, wetland size, hydroperiod, land cover, growing season interval, and normalized difference vegetation index (NDVI). Predictors for upscaling included the Dynamic Surface Water Extent based on Landsat 4, 5, 7, and 8 for the presence, permanence, and extent of surface water, ClimateNA for historical and future temperatures, and the North American Land Change Monitoring System for land cover. Model runs included historical dry (1991) and wet (2011) years, as well as future Socioeconomic Pathways emissions scenarios (SSP2-4.5, SSP5-8.5).

Data used to estimate models relating climate and land cover to wetland densities. Data derived from historical climate data, estimates of hydrological processed based on the Variable Infiltration Capacity model, National Wetlands Inventory, and National Land Cover Database (2006 version). Wetland densities based on observations from the Waterfowl Breeding Population and Habitat Survey.

Data used to estimate models relating climate and land cover to wetland densities. Data derived from historical climate data, estimates of hydrological processed based on the Variable Infiltration Capacity model, National Wetlands Inventory, and National Land Cover Database (2006 version). Wetland densities based on observations from the Waterfowl Breeding Population and Habitat Survey.

The impact of climate change on land conversion was assessed by projecting the land-use model under GCM hindcast and forecast climatic conditions. For each GCM, we projected future row crop proportions under 40 years of average hindcast conditions (i.e., assuming historical climate prevails into the future), and under 20 year of average hindcast conditions followed by 20 years of average forecast conditions. We used twenty years of forecast conditions to avoid assuming that climate changes projected for mid-century would have occurred immediately. The 20-20 assumption approximates a linear transition from the historic to future climate and is not limiting since the probabilities will converge given sufficient years under a given climate regime. Projected climate change impacts differed in direction and spatial pattern between GCMs (Fig. S3). Projected changes in the proportion of the landscape planted in row crops were generally small (mean change = 0.01), but included increases of over 0.25 of the landscape and declines of over 0.3 of the landscape (Fig. S3). Conversion probabilities responded to precipitation as expected, with an increase in precipitation associated with higher probabilities that grass converts to crops and lower probabilities that crops convert to grass.

The USGS’s FORE-SCE model was used to produce unprecedented landscape projections for the Prairie Potholes region of the northern Great Plains of the United States. The projections are characterized by 1) high spatial resolution (30-meter cells), 2) high thematic resolution (29 land use and land cover classes), 3) broad spatial extent (covering much of the Great Plains), 4) use of real land ownership boundaries to ensure realistic representation of landscape patterns, and 5) representation of both anthropogenic land use and natural vegetation change. A variety of scenarios were modeled from 2014 to 2100, with decadal timesteps (i.e., 2014, 2020, 2030, etc.). Modeled land use and natural vegetation classes were responsive to projected future changes in environmental conditions, including changes in groundwater and water access. Eleven primary land-use scenarios were modeled, from four different scenario families. The land-use scenarios focused on socioeconomic impacts on anthropogenic land use (demographics, energy use, agricultural economics, and other socioeconomic considerations). The following provides a brief summary of the 11 major land-use scenarios. 1) Business-as-usual - Based on an extrapolation of recent land-cover trends as derived from remote-sensing data. Overall trends were provided by 2001 to 2011 change in the National Land Cover Database, while change in crop types were extrapolated from 2008 to 2014 change in the Cropland Data Layer. Overall the scenario is marked by expansion of high-value traditional crops (corn, soybeans, cotton), with a concurrent decline in dryland wheat and some other lower-value crops. 2) Billion Ton Update scenario ($40 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update (BTU). The $40 scenario represents likely agricultural conditions under an assumed farmgate price of $40 per dry ton of biomass (for the production of biofuel). This is the least aggressive BTU scenario for placing "perennial grass" (for biofuel feedstock) on the landscape. 3) Billion Ton Update scenario ($60 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $60 scenario represents likely agricultural conditions under an assumed farmgate price of $60 per dry ton of biomass (for the production of biofuel). At the higher farmgate price, the perennial grass class expands dramatically. 4) Billion Ton Update scenario ($80 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $80 scenario represents likely agricultural conditions under an assumed farmgate price of $80 per dry ton of biomass (for the production of biofuel). With the high farmgate price, this scenario shows the highest expansion of perennial grass among the 11 modeled scenarios. 5) GCAM Reference scenario - Based on global-scale scenarios from the GCAM model, the "reference" scenario provides a likely landscape under a world without specific carbon or climate mitigation efforts. As such, it's another form of a "business-as-usual" scenario. 6) GCAM 4.5 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 4.5 model represents a mid-level mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of ~4.5 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland (including perennial grass used as feedstock for cellulosic biofuel production). 7) GCAM 2.6 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 2.6 model represents a very aggressive mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of only ~2.6 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland

The USGS’s FORE-SCE model was used to produce unprecedented landscape projections for the Prairie Potholes region of the northern Great Plains of the United States. The projections are characterized by 1) high spatial resolution (30-meter cells), 2) high thematic resolution (29 land use and land cover classes), 3) broad spatial extent (covering much of the Great Plains), 4) use of real land ownership boundaries to ensure realistic representation of landscape patterns, and 5) representation of both anthropogenic land use and natural vegetation change. A variety of scenarios were modeled from 2014 to 2100, with decadal timesteps (i.e., 2014, 2020, 2030, etc.). Modeled land use and natural vegetation classes were responsive to projected future changes in environmental conditions, including changes in groundwater and water access. Eleven primary land-use scenarios were modeled, from four different scenario families. The land-use scenarios focused on socioeconomic impacts on anthropogenic land use (demographics, energy use, agricultural economics, and other socioeconomic considerations). The following provides a brief summary of the 11 major land-use scenarios. 1) Business-as-usual - Based on an extrapolation of recent land-cover trends as derived from remote-sensing data. Overall trends were provided by 2001 to 2011 change in the National Land Cover Database, while change in crop types were extrapolated from 2008 to 2014 change in the Cropland Data Layer. Overall the scenario is marked by expansion of high-value traditional crops (corn, soybeans, cotton), with a concurrent decline in dryland wheat and some other lower-value crops. 2) Billion Ton Update scenario ($40 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update (BTU). The $40 scenario represents likely agricultural conditions under an assumed farmgate price of $40 per dry ton of biomass (for the production of biofuel). This is the least aggressive BTU scenario for placing "perennial grass" (for biofuel feedstock) on the landscape. 3) Billion Ton Update scenario ($60 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $60 scenario represents likely agricultural conditions under an assumed farmgate price of $60 per dry ton of biomass (for the production of biofuel). At the higher farmgate price, the perennial grass class expands dramatically. 4) Billion Ton Update scenario ($80 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $80 scenario represents likely agricultural conditions under an assumed farmgate price of $80 per dry ton of biomass (for the production of biofuel). With the high farmgate price, this scenario shows the highest expansion of perennial grass among the 11 modeled scenarios. 5) GCAM Reference scenario - Based on global-scale scenarios from the GCAM model, the "reference" scenario provides a likely landscape under a world without specific carbon or climate mitigation efforts. As such, it's another form of a "business-as-usual" scenario. 6) GCAM 4.5 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 4.5 model represents a mid-level mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of ~4.5 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland (including perennial grass used as feedstock for cellulosic biofuel production). 7) GCAM 2.6 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 2.6 model represents a very aggressive mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of only ~2.6 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland

This data release provides a set of Hydrological Simulation Program--Fortran (HSPF) model files representing 5 EPA-selected future climate change scenarios for each of three river basins: Blackstone in Massachusetts and Rhode Island, Pawcatuck in Rhode Island, and Ispwich in Massachusetts. Output from these models are intended for use as input to EPA Watershed Management Optimization Support Tool (WMOST) modeling. Climate scenarios, based on 2036-2065 change from 1975-2004 Representative Concentration Pathways (RCP) 4.5 and 8.5, model effects of air temperature and precipitation changes (in degrees F for air temperature, in percent for precipitation) made to the input historical meteorological time series 1975-2004. Blackstone meteorological data are from T.F. Green Airport (Providence) and Worcester Regional Airport (Worcester), Pawcatuck meteorological data are from T.F. Green Airport (Providence), and Ipswich meteorological data are from 30 local National Weather Service Stations (1975-1995) and Boston Logan Airport (1996-2004). Each set of climate scenario model files are derived from the original calibrated model files developed to support WMOST modeling (refer to Source Input fields in this metadata file).