Predicted specific mean daily flow of small streams in the Upper Colorado River Basin based on historic flow data

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.

本研究旨在为科罗拉多河上游流域的小型无流量监测河段构建单位面积日平均流量模型——单位面积日平均流量即日均流量除以流域面积，单位为立方英尺每秒每平方英里。径流模拟是理解景观尺度径流驱动因子、估算无观测记录河段流量的重要工具。本研究聚焦科罗拉多河上游流域，该区域不仅是水资源保障的关键区域，且未来预计将经历显著的气候干旱化转变。本研究采用随机森林（Random Forest）建模方法，以115个有实测流量水文站对应河段的单位面积日平均流量与环境变量之间的关联为建模目标。随后，本研究利用该流域内每个栅格化河道单元的环境变量，将单位面积日平均流量的模拟结果推演至科罗拉多河上游流域的无观测河段。本数据图层展示了每个河道栅格单元的单位面积日平均流量模拟值。