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.

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 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 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 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 7-day minimum flow (mean of the annual minimums of a 7-day moving average for each year [cubic feet per second]) 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 7-day minimum flow on gaged streams (115 gages) and environmental variables. We then projected 7-day minimum flow 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 7-day minimum flow of each stream cell.