Modeling streamflow is an important approach for understanding landscape-scale drivers of flow and estimating flows where there are no streamgage records. In this study conducted by the U.S. Geological Survey in cooperation with Colorado State University, the objectives were to model streamflow metrics on small, ungaged streams in the Upper Colorado River Basin and identify streams that are potentially threatened with becoming intermittent under drier climate conditions. The Upper Colorado River Basin is a region that is critical for water resources and also projected to experience large future climate shifts toward a drying climate. A random forest modeling approach was used to model the relationship between streamflow metrics and environmental variables. Flow metrics were then projected to ungaged reaches in the Upper Colorado River Basin using environmental variables for each stream, represented as raster cells, in the basin. Last, the projected random forest models of minimum flow coefficient of variation and specific mean daily flow were used to highlight streams that had greater than 61.84 percent minimum flow coefficient of variation and less than 0.096 specific mean daily flow and suggested that these streams will be most threatened to shift to intermittent flow regimes under drier climate conditions. Map projection products can help scientists, land managers, and policymakers understand current hydrology in the Upper Colorado River Basin and make informed decisions regarding water resources. With knowledge of which streams are likely to undergo significant drying in the future, managers and sci- entists can plan for stream-dependent ecosystems and human water users.

Our objective was to model intermittency (perennial, weakly intermittent, or strongly intermittent) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate.We used a random forest modeling approach to model the relation between intermittency on gaged streams (115 gages) and environmental variables. We then projected intermittency status to ungaged reaches in the Upper Colorado River Basin using environmental variables for each raster stream cell in the basin. This data layer shows modeled values for intermittency of each stream cell.

Our objective was to model frequency of low-pulse events on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a random forest modeling approach to model the relation between frequency of low-pulse events on gaged streams (115 gages) and environmental variables. We then projected frequency of low-pulse events to ungaged reaches in the Upper Colorado River Basin using environmental variables for each stream cell in the basin. This data layer shows modeled values for the frequency of low-pulse events.

Our objective was to model frequency of low-pulse events on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a random forest modeling approach to model the relation between frequency of low-pulse events on gaged streams (115 gages) and environmental variables. We then projected frequency of low-pulse events to ungaged reaches in the Upper Colorado River Basin using environmental variables for each stream cell in the basin. This data layer shows modeled values for the frequency of low-pulse events.

Our objective was to model specific mean daily flow (mean daily flow divided by drainage area [cubic feet per second per square mile]) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate.We used a random forest modeling approach to model the relation between specific mean daily flow on gaged streams (115 gages) and environmental variables. We then projected specific mean daily flow to ungaged reaches in the Upper Colorado River Basin using environmental variables for each raster stream cell in the basin. This data layer shows modeled values for specific mean daily flow of each stream cell.

Our objective was to model specific mean daily flow (mean daily flow divided by drainage area [cubic feet per second per square mile]) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate.We used a random forest modeling approach to model the relation between specific mean daily flow on gaged streams (115 gages) and environmental variables. We then projected specific mean daily flow to ungaged reaches in the Upper Colorado River Basin using environmental variables for each raster stream cell in the basin. This data layer shows modeled values for specific mean daily flow of each stream cell.

Our objective was to model minimum flow coefficient of variation (CV) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a random forest modeling approach to model the relation between minimum flow CV (the standard deviation of annual minimum flows times 100 divided by the mean of annual minimum flows) on gaged streams (115 gages) and environmental variables. We then projected minimum flow CV to ungaged reaches in the Upper Colorado River Basin using environmental variables for each stream cell in the basin. This data layer shows modeled values for minimum flow CV.

Our objective was to model minimum flow coefficient of variation (CV) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a random forest modeling approach to model the relation between minimum flow CV (the standard deviation of annual minimum flows times 100 divided by the mean of annual minimum flows) on gaged streams (115 gages) and environmental variables. We then projected minimum flow CV to ungaged reaches in the Upper Colorado River Basin using environmental variables for each stream cell in the basin. This data layer shows modeled values for minimum flow CV.

Our objective was to model specific minimum flow (mean of the annual minimum flows divided by drainage area [cubic feet per second per square mile]) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a random forest modeling approach to model the relation between specific minimum flow on gaged streams (115 gages) and environmental variables. We then projected specific minimum flow to ungaged reaches in the Upper Colorado River Basin using environmental variables for each raster stream cell in the basin. This data layer shows modeled values for specific minimum flow of each stream cell.

Our objective was to model specific minimum flow (mean of the annual minimum flows divided by drainage area [cubic feet per second per square mile]) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a random forest modeling approach to model the relation between specific minimum flow on gaged streams (115 gages) and environmental variables. We then projected specific minimum flow to ungaged reaches in the Upper Colorado River Basin using environmental variables for each raster stream cell in the basin. This data layer shows modeled values for specific minimum flow of each stream cell.