Effective monitoring and prediction of flood and drought events requires an improved understanding of how and why surface-water expansion and contraction in response to climate varies across space. This paper sought to (1) quantify how interannual patterns of surface-water expansion and contraction vary spatially across the Prairie Pothole Region (PPR) and adjacent Northern Prairie (NP) in the United States, and (2) explore how landscape characteristics influence the relationship between climate inputs and surface-water dynamics. Due to differences in glacial history, the PPR and NP show distinct patterns in regards to drainage development and wetland density, together providing a diversity of conditions to examine surface-water dynamics. We used Landsat imagery to characterize variability in surface-water extent across 11 Landsat path/rows representing the PPR and NP (images spanned 1985-2015). The PPR not only experienced a 2.6-fold greater surface-water extent under median conditions relative to the NP, but also showed a 3.4-fold greater change in surface-water extent between drought and deluge conditions. The relationship between surface-water extent and accumulated water availability (precipitation minus potential evapotranspiration) was quantified per watershed and statistically related to variables representing hydrology-related landscape characteristics (e.g., infiltration capacity, surface storage capacity, stream density). To investigate the influence stream connectivity has on the rate at which surface water leaves a given location, we modeled stream-connected and stream-disconnected surface water separately. Stream-connected surface water showed a greater expansion with wetter climatic conditions in landscapes with greater total wetland area, but lower total wetland density. Disconnected surface water showed a greater expansion with wetter climatic conditions in landscapes with higher wetland density, lower infiltration and less anthropogenic drainage. From these findings, we can expect that shifts in precipitation and evaporative demand will have uneven effects on surface-water quantity. Accurate predictions regarding the effect of climate change on surface-water quantity will require consideration of hydrology-related landscape characteristics including wetland storage and arrangement.

Effective monitoring and prediction of flood and drought events requires an improved understanding of how and why surface-water expansion and contraction in response to climate varies across space. This paper sought to (1) quantify how interannual patterns of surface-water expansion and contraction vary spatially across the Prairie Pothole Region (PPR) and adjacent Northern Prairie (NP) in the United States, and (2) explore how landscape characteristics influence the relationship between climate inputs and surface-water dynamics. Due to differences in glacial history, the PPR and NP show distinct patterns in regards to drainage development and wetland density, together providing a diversity of conditions to examine surface-water dynamics. We used Landsat imagery to characterize variability in surface-water extent across 11 Landsat path/rows representing the PPR and NP (images spanned 1985-2015). The PPR not only experienced a 2.6-fold greater surface-water extent under median conditions relative to the NP, but also showed a 3.4-fold greater change in surface-water extent between drought and deluge conditions. The relationship between surface-water extent and accumulated water availability (precipitation minus potential evapotranspiration) was quantified per watershed and statistically related to variables representing hydrology-related landscape characteristics (e.g., infiltration capacity, surface storage capacity, stream density). To investigate the influence stream connectivity has on the rate at which surface water leaves a given location, we modeled stream-connected and stream-disconnected surface water separately. Stream-connected surface water showed a greater expansion with wetter climatic conditions in landscapes with greater total wetland area, but lower total wetland density. Disconnected surface water showed a greater expansion with wetter climatic conditions in landscapes with higher wetland density, lower infiltration and less anthropogenic drainage. From these findings, we can expect that shifts in precipitation and evaporative demand will have uneven effects on surface-water quantity. Accurate predictions regarding the effect of climate change on surface-water quantity will require consideration of hydrology-related landscape characteristics including wetland storage and arrangement.

surface water data and projections produced for 32 sites in the central US. Surface water data consists of open and vegetated surface water 2 week averages from 2017-2021. This dataset is associated with the following publication: Vanderhoof, M., J. Christensen, L. Alexander, C. Lane, and H. Golden. Climate Change Will Impact Surface Water Extents and Dynamics Across the Central United States. Earth�s Future. John Wiley & Sons, Inc., Hoboken, NJ, USA, 12(2): e2023EF004106, (2024).

This data release contains grids, in geographic tagged imaged file (.tif) format, summarizing inundation frequency of the U. S. Geological Survey (USGS) Dynamic Surface Water Extent (DSWE) Landsat Science Product at 114 National Wildlife Refuges throughout the U.S. Fish and Wildlife Service (USFWS) Mountain-Prairie Region (Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, and Wyoming). The DSWE product provides long-term (1982 to present), high temporal resolution data (30-meter) on surface water inundation patterns that can help identify locations of past or current drought conditions. For each refuge, three files were produced using data from different periods: the baseline period (1982-2000), the evaluation period (2001–20), and the period of record (1982-2020). Inundation frequencies for each pixel were derived by dividing the total number of observations classified as any one of the DSWE water classes by the total number of observations of water extent or presence.

Variability in river discharge, particularly very high flow and low flow conditions, has far-reaching environmental and economic consequences. The retention of water in surface storage, concentrated in lakes, ponds, wetlands, floodplains, and temporary water in flood prone areas, can potentially contribute to flow generation and flood regulation. However, the impact of surface water storage on river discharge can be challenging to isolate and quantify. A suite of hydrologic signatures were generated for 72 gages across the conterminous United States. The hydrologic signatures were selected to characterize all flows as well as isolating high and low flows, and machine learning models were developed to explain watershed variability in signature values. Wetland related variables, including multi-sensor-based surface water extent and hydroperiod, were compared with other drivers, including climate, topography, and land cover. An improved understanding of how surface water dynamics influence river discharge can be used to improve the resilience of river systems to climate extremes.

Variability in river discharge, particularly very high flow and low flow conditions, has far-reaching environmental and economic consequences. The retention of water in surface storage, concentrated in lakes, ponds, wetlands, floodplains, and temporary water in flood prone areas, can potentially contribute to flow generation and flood regulation. However, the impact of surface water storage on river discharge can be challenging to isolate and quantify. A suite of hydrologic signatures were generated for 72 gages across the conterminous United States. The hydrologic signatures were selected to characterize all flows as well as isolating high and low flows, and machine learning models were developed to explain watershed variability in signature values. Wetland related variables, including multi-sensor-based surface water extent and hydroperiod, were compared with other drivers, including climate, topography, and land cover. An improved understanding of how surface water dynamics influence river discharge can be used to improve the resilience of river systems to climate extremes.

Within large-river ecosystems, floodplains serve a variety of important ecological functions. A recent survey of 80 managers of floodplain conservation lands along the Upper and Middle Mississippi and Lower Missouri Rivers in the central United States found that the most critical information needed to improve floodplain management centered on metrics for characterizing depth, extent, frequency, duration, and timing of inundation. These metrics can be delivered to managers efficiently through cloud-based interactive maps. To calculate these metrics, we interpolated an existing one-dimensional HEC-RAS hydraulic model for the Lower Missouri River, which simulated water surface elevations at cross sections spaced (<1 kilometer) to sufficiently characterize water surface profiles along an approximately 800 kilometer stretch upstream from the confluence with the Mississippi River over an 80-year record at a daily time step. To translate these water surface elevations to inundation depths, we subtracted a merged terrain model consisting of floodplain LIDAR and bathymetric surveys of the river channel. We completed these calculations for an 800 kilometer stretch of the Missouri River, spanning from Rulo, Nebraska to the river's confluence with the Mississippi River. This approach resulted in a 29,000+ day time series of inundation depths across the floodplain using grid cells with 30 meter spatial resolution. This dataset presents 17 metrics for each of two scenarios, one using a baseline timeseries of stages from the HEC-RAS simulation and one using a timeseries of stages adjusted to account for changes in discharge under one possible climate change scenario. These metrics are calculated on a per pixel basis and encompass a variety of temporal criteria generally relevant to flora and fauna of interest to floodplain managers, including, for example, the average number of days inundated per year within a growing season. We also include a series of maps of water depths across the floodplain by return interval for each scenario, and the minimum return interval at which each pixel is inundated. Lastly, we include the base elevation layer that we generated to calculate depth of inundation from interpolated water-surface elevations.

Within large-river ecosystems, floodplains serve a variety of important ecological functions. A recent survey of 80 managers of floodplain conservation lands along the Upper and Middle Mississippi and Lower Missouri Rivers in the central United States found that the most critical information needed to improve floodplain management centered on metrics for characterizing depth, extent, frequency, duration, and timing of inundation. These metrics can be delivered to managers efficiently through cloud-based interactive maps. To calculate these metrics, we interpolated an existing one-dimensional HEC-RAS hydraulic model for the Lower Missouri River, which simulated water surface elevations at cross sections spaced (<1 kilometer) to sufficiently characterize water surface profiles along an approximately 800 kilometer stretch upstream from the confluence with the Mississippi River over an 80-year record at a daily time step. To translate these water surface elevations to inundation depths, we subtracted a merged terrain model consisting of floodplain LIDAR and bathymetric surveys of the river channel. We completed these calculations for an 800 kilometer stretch of the Missouri River, spanning from Rulo, Nebraska to the river's confluence with the Mississippi River. This approach resulted in a 29,000+ day time series of inundation depths across the floodplain using grid cells with 30 meter spatial resolution. This dataset presents 17 metrics for each of two scenarios, one using a baseline timeseries of stages from the HEC-RAS simulation and one using a timeseries of stages adjusted to account for changes in discharge under one possible climate change scenario. These metrics are calculated on a per pixel basis and encompass a variety of temporal criteria generally relevant to flora and fauna of interest to floodplain managers, including, for example, the average number of days inundated per year within a growing season. We also include a series of maps of water depths across the floodplain by return interval for each scenario, and the minimum return interval at which each pixel is inundated. Lastly, we include the base elevation layer that we generated to calculate depth of inundation from interpolated water-surface elevations.

This data release contains grids, in geographic tagged imaged file(.tif) format, summarizing inundation frequency of the U. S. Geological Survey (USGS) Dynamic Surface Water Extent (DSWE) Landsat Science Product at 114 National Wildlife Refuges throughout the U.S. Fish and Wildlife Service (USFWS) Mountain-Prairie Region (Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, and Wyoming). The DSWE product provides long-term (1982 to present), high temporal resolution data (30-meter) on surface water inundation patterns that can help identify locations of past or current drought conditions. For each refuge, three files were produced using data from different periods: the baseline period (1982-2000), the evaluation period (2001–20), and the period of record (1982-2020). Inundation frequencies for each pixel were derived by dividing the total number of observations classified as any one of the DSWE water classes by the total number of observations of water extent or presence. This child item contains data for wildlife refuges within the state of Kansas (KS). See keywords for specific refuges.

This data release contains grids, in geographic tagged imaged file(.tif) format, summarizing inundation frequency of the U. S. Geological Survey (USGS) Dynamic Surface Water Extent (DSWE) Landsat Science Product at 114 National Wildlife Refuges throughout the U.S. Fish and Wildlife Service (USFWS) Mountain-Prairie Region (Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, and Wyoming). The DSWE product provides long-term (1982 to present), high temporal resolution data (30-meter) on surface water inundation patterns that can help identify locations of past or current drought conditions. For each refuge, three files were produced using data from different periods: the baseline period (1982-2000), the evaluation period (2001–20), and the period of record (1982-2020). Inundation frequencies for each pixel were derived by dividing the total number of observations classified as any one of the DSWE water classes by the total number of observations of water extent or presence. This child item contains data for wildlife refuges within the state of Kansas (KS). See keywords for specific refuges.