Hydrologic Impacts of Cloud Seeding in the Medicine Bow and Sierra Madre Ranges using WRF-WxModⓇ and WRF-Hydro Simulations

The Medicine Bow and Sierra Madre Ranges in Wyoming provide an important source of water to the state’s agriculture, economy, and recreation via streamflow and snowpack. An aerial cloud-seeding program targeting these mountain ranges has been conducted for the Wyoming Water Development Commission (WWDC) by Weather Modification International (WMI) since 2018 in order to increase precipitation, and thus snowpack and streamflow, in this region. To assess the impact of cloud seeding on precipitation, streamflow, and snowpack, ensemble simulations of WRF-WxModⓇ forced WRF-Hydro, a spatially-distributed hydrologic model. These simulations cover the water year 2019–2020 to capture the full seasonal impacts of cloud-seeding on hydrology.

WRF-Hydro simulations are configured with a 1-km land surface model, Noah-MP, and terrain routing grid run at 250 m. Subsurface, surface, and channel routing are turned on in the model to simulate runoff, streamflow, and other processes. Neither lakes and reservoirs nor anthropogenic impacts are explicitly accounted for in these model runs such that the model results produced are fully “unregulated” flow responses. Baseline WRF-Hydro model runs are forced with bias-corrected 4-km convection-permitting WRF simulations (CONUS404) to perform calibration at 17 USGS stream gages from 2013–2018 and select optimal values of basin parameters, which are then transferred to hydrologically similar basins during the regionalization process. After two simulations are run using only CONUS404–the first being a spin-up run from 1999–2004, and the second being a baseline run from 1999–2021–WRF-Hydro is run from 2019–2020 using 36-ensemble members from WRF-WxMod to simulate the effects of seeding on the days during which seeding occurred. Changes to snowpack and streamflow are evaluated basin-wide to understand how cloud seeding alters precipitation and thus water resources in Wyoming.