Water/Wastewater Utilities and Extreme Climate and Weather Events: Case Studies on Community Response, Lessons Learned, Adaptation, and Planning Needs for the Future

This project consisted of a series of workshops that (1) examined the actions taken by water and wastewater utility practitioners who faced a recent extreme weather and climate-related event and documented their planning and response; (2) determined and recorded lessons learned; (3) documented and analyzed the decision process, including decision makers, organizations involved, and data … Continue reading “Water/Wastewater Utilities and Extreme Climate and Weather Events: Case Studies on Community Response, Lessons Learned, Adaptation, and Planning Needs for the Future”

A Machine Learning Tool for Design of Behavioral Fish Barriers in the Sacramento-San Joaquin River Delta

Survival of out-migrating juvenile salmonids (Oncorhynchus spp.) through the Sacramento-San Joaquin River Delta averages less than 33 percent, depending on water flow through the delta, and is partially governed by the distribution of fish among three Sacramento River distributaries: Sutter, Steamboat, and Georgiana sloughs. Behavioral altering structures in the junctions of the distributaries can effectively … Continue reading “A Machine Learning Tool for Design of Behavioral Fish Barriers in the Sacramento-San Joaquin River Delta”

A Machine Learning Approach to Predict Groundwater Levels in California Reveals Ecosystems at Risk

Groundwater dependent ecosystems (GDEs) are increasingly threatened worldwide, but the shallow groundwater resources that they are reliant upon are seldom monitored. In this study, we used satellite-based remote sensing to predict groundwater levels under groundwater dependent ecosystems across California, USA. Depth to groundwater was modelled for a 35-years period (1985–2019) within all groundwater dependent ecosystems … Continue reading “A Machine Learning Approach to Predict Groundwater Levels in California Reveals Ecosystems at Risk”

Machine learning based downscaling of GRACE-estimated groundwater in Central Valley, California

California’s Central Valley, one of the most agriculturally productive regions, is also one of the most stressed aquifers in the world due to anthropogenic groundwater over-extraction primarily for irrigation. Groundwater depletion is further exacerbated by climate-driven droughts. Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry has demonstrated the feasibility of quantifying global groundwater storage changes … Continue reading “Machine learning based downscaling of GRACE-estimated groundwater in Central Valley, California”

What Can We Learn From How the State Responded to the Last Major Drought?

For the second consecutive year, the state is experiencing extremely low rates of precipitation. As we prepare for what could be an extended period of dry conditions, it is helpful to review how the state responded to the last major drought. Such information can inform—and thereby potentially improve—the state’s current and ongoing response to developing … Continue reading “What Can We Learn From How the State Responded to the Last Major Drought?”

Anthropogenic Stressors and Changes in the Clear Lake Ecosystem as Recorded in Sediment Cores

Sediment cores were collected to investigate multiple stresses on Clear Lake, California, USA, through the period of European occupation to the present day. Earlier workers suggested the hypothesis that the use of mechanized earthmoving equipment, starting in the 1920s and 1930s, was responsible for erosion, mercury (Hg) contamination, and habitat loss stresses. Cores (;2.5 m in depth) were collected … Continue reading “Anthropogenic Stressors and Changes in the Clear Lake Ecosystem as Recorded in Sediment Cores”