Estimates of present and future flood risk in the conterminous United States

Environmental Research Letters (IOP) | February 28th, 2018

Past attempts to estimate rainfall-driven flood risk across the US either have incomplete coverage, coarse resolution or use overly simplified models of the flood

Past attempts to estimate rainfall-driven flood risk across the US either have incomplete coverage, coarse resolution or use overly simplified models of the flooding process. In this paper, we use a new 30 m resolution model of the entire conterminous US with a 2D representation of flood physics to produce estimates of flood hazard, which match to within 90% accuracy the skill of local models built with detailed data. These flood depths are combined with exposure datasets of commensurate resolution to calculate current and future flood risk. Our data show that the total US population exposed to serious flooding is 2.6–3.1 times higher than previous estimates, and that nearly 41 million Americans live within the 1% annual exceedance probability floodplain (compared to only 13 million when calculated using FEMA flood maps). We find that population and GDP growth alone are expected to lead to significant future increases in exposure, and this change may be exacerbated in the future by climate change.

Estimating reservoir sedimentation rates at large spatialand temporal scales: A case study of California

Water Resources Research, American Geophysical Union (AGU) | December 25th, 2009

Previous reservoir sedimentation models have ignored two key factors for large spatial and temporal modeling of multiple reservoirs: trapping by upstream dams and decre

Previous reservoir sedimentation models have ignored two key factors for large spatial and temporal modeling of multiple reservoirs: trapping by upstream dams and decreasing sediment trapping as reservoirs fill. We developed a spreadsheet-based model that incorporates both factors. Using California as a case study, we used measured sedimentation rates to estimate sediment yields for distinct geomorphic regions and applied those rates to unmeasured reservoirs by region. Statewide reservoirs have likely filled with 2.1 billion m3 of sediment to date, decreasing total reservoir capacity by 4.5%. About 200 reservoirs have likely lost more than half their initial capacity to sedimentation.

Estuary News, April 2001

San Francisco Estuary Partnership (SFEP) | April 15th, 2001

Estuary News, December 2017

San Francisco Estuary Partnership (SFEP) | December 15th, 2017

Estuary News, December 2020

San Francisco Estuary Partnership (SFEP) | December 15th, 2020

Estuary News, February 1997

San Francisco Estuary Partnership (SFEP) | February 15th, 1997

Estuary News, March 2015

San Francisco Estuary Partnership (SFEP) | March 15th, 2015

Estuary News, March 2017

San Francisco Estuary Partnership (SFEP) | March 15th, 2017

Estuary News, September 2017

San Francisco Estuary Partnership (SFEP) | September 15th, 2017

Evaluating GFS and ECMWF Ensemble Forecasts of Integrated Water Vapor Transport along the U.S. West Coast

American Meteorological Society (AMS) | October 28th, 2022

Atmospheric rivers (ARs) are long and narrow regions in the atmosphere of enhanced integrated water vapor transport (IVT) and can produce extreme precipitation and high s

Atmospheric rivers (ARs) are long and narrow regions in the atmosphere of enhanced integrated water vapor transport (IVT) and can produce extreme precipitation and high societal impacts. Reliable and skillful forecasts of landfalling ARs in the western United States are critical to hazard preparation and aid in decision support activities, such as Forecast-Informed Reservoir Operations (FIRO). The purpose of this study is to compare the cool-season water year skill of the NCEP Global Ensemble Forecast System (GEFS) and ECMWF Ensemble Prediction System (EPS) forecasts of IVT along the U.S. West Coast for 2017–20. The skill is analyzed using probability-over-threshold forecasts of IVT magnitudes ≥ 250 kg m−1 s−1 (P250) using contingency table skill metrics in coastal Northern California and along the west coast of North America. Analysis of P250 with lead time (dProg/dt) found that the EPS provided ∼1 day of additional lead time for situational awareness over the GEFS at lead times of 6–10 days. Forecast skill analysis highlights that the EPS leads over the GEFS with success ratios 0.10–0.15 higher at lead times > 6 days for P250 thresholds of ≥25% and ≥50%, while event-based skill analysis using the probability of detection (POD) found that both models were largely similar with minor latitudinal variations favoring higher POD for each model in different locations along the coast. The relative skill of the EPS over the GEFS is largely attributed to overforecasting by the GEFS at longer lead times and an increase in the false alarm ratio.