This study experiments with reservoir representation schemes to improve the ability to model active water management in the National Water Model (NWM). For this purpose, we developed an integrated water management model, NWM-ResSim, by coupling the NWM with HEC-ResSim, and two reservoir representation schemes are tested: simulation of reservoir operations and retrieval of scheduled operations. The experiments focus on a pilot reservoir domain in the Russian River basin – Lake Mendocino, California – and its contributing watershed. The evaluation results suggest that the NWM-ResSim improves the simulation performance of reservoir outflow from this managed reservoir over the NWM default level pool routing scheme. The degree of this improvement depends on the suitability of the operation guidance; the reservoir operations simulation scheme could have acceptable errors for the purposes of water resources management, but not for flood operations. Results of the retrieval scheme of scheduled operations demonstrated better performance for sub-daily flood operations.

This study aims to address hydrological processes and impacts of an atmospheric river (AR) event that occurred during 15–18 February 2004 in the Russian River basin in California. The National Water Model (NWM), a fully distributed hydrologic model, was used to evaluate the hydrological processes including soil moisture flux, overland flow, and streamflow. Observed streamflow and volumetric soil water content data were used to evaluate the performance of the NWM using various error metrics. The simulation results showed that this AR event (15–18 February 2004) with a long duration of precipitation could cause not only deep soil saturation, but also high direct runoff depth. Taken together, the analysis revealed the complex interaction between precipitation and land surface response to the AR event. The results emphasize the significance of a change of water contents in various soil layers and suggest that soil water content monitoring could aid in improving flood forecasting accuracy caused by the extreme events such as the AR.

The magnitude and frequency of extreme precipitation events in the early twenty-first century have already proven to be increasing at a rate more quickly than previously anticipated. Currently, the biggest consequence of the change in extreme precipitation is the lack of a climate-adjusted national standard taking into account these recent increases that could be used to prevent life and property loss from catastrophic precipitation-driven floods. Here, we address how severe the change in extreme precipitation compares against the current national standard for precipitation climatology (NOAA Atlas 14) and how much of the population is affected by the underestimation of this risk in the contiguous United States (CONUS). As a result, extreme precipitation in the early twenty-first century has outpaced our current national standard in half of CONUS, and the heavy precipitation events experienced recently are quickly becoming a “new normal”, which will increase in severity and frequency in a continually changing climate. Over three-quarters of the U.S. population will likely experience this new normal occurrence of extreme precipitation. As much as one-third of the population is expected to experience the current definition of a 1-in-100-year storm as often as three times in their lifetime. Additionally, the current precipitation standards for designing transportation infrastructure and urban stormwater drainage systems that are built upon Atlas 14 may be insufficient to protect the public's safety and personal/community property from severe flooding. Areas where flood risk is mitigated by operating hydraulic and adaptation structures urgently need to assess the impact of the increased-hourly extreme precipitation and reevaluate their applicable operation rules. Understanding and predicting patterns and the likelihood of short-duration heavy precipitation would be beneficial in preparing for severe precipitation-driven disasters, such as flash floods and landslides, which would happen more frequently in a changing climate. Following the results of this analysis, accelerating the development and dissemination of the next generation of the national standard that has been climatically adjusted to adapt to the new normal is strongly recommended.

Soil moisture retention (SMR) capacity plays a key role in estimating the direct runoff when a multi-pulse storm event occurs. It is very important to know how much SMR will be recovered during the intervals of no rain of a multi-pulse storm. This study developed a new approach for derivation of the SMR recovery curve (R-curve) at sub-daily time-scales using the Curve Number (CN) method. The methodology was applied using complex storm events in the Napa River basin, California. The R-curve is classified into three sections depending on the recovery rate of SMR during the inter-storm interval of no rain (INR), and this study defines the characteristics. The first section of the R-curve (INR 0–21 h with 0.97 mm/h) is described as gradually recovering SMR, since water is being infiltrated and the upper soil layer is not fully saturated. The second section (INR 21–36 h with 2.11 mm/h) is defined as steeply recovering S due to downward drainage (sub-surface/inter flows) and evaporation without infiltration. The third section (INR 36–68 h with 0.34 mm/h) is described as gradually decreasing recovery dependent on evaporation since percolation and drainage have almost stopped.

Low-impact development (LID) methods are an important approach to storm-water mitigation. Modeling the effects of these installations using rainfall-runoff simulations can provide useful data for future design and implementation. In this study, we used the Storm Water Management Model to assess seven types of LID installations (vegetated areas, garden pots, tree filter boxes, permeable pavement, infiltration ditches, rain barrels, and infiltration blocks) at a South Korean industrial site. Using both short- and long-term simulation periods and distinct sub-basins within the study site, we were able to assess LID performance at the combined watershed, as well as at one LID facility. All LID types showed reasonable performance for storm-water runoff reduction, though rain barrels were the least effective. The effect of rainfall runoff reduction on LID facilities is changed according to rainfall depth (annual precipitation, monthly rainfall), the ratio of drainage area and facility capacity. We concluded that SWMM-LID modeling can effectively support the management of LID installations by providing additional design and planning data to better mitigate the effects of storm-water runoff.

Compound flooding, resulting from a combination of riverine and coastal processes, is a complex but important hazard to resolve along urbanized shorelines in the vicinity of river mouths. However, inland flooding models rarely consider oceanographic conditions, and vice versa for coastal flood models. Here, we describe the development of an operational, integrated coastal-watershed flooding model to address this issue of compound flooding in a highly urbanized estuarine environment, San Francisco Bay (CA, USA), where the surrounding communities are susceptible to flooding along the bay shoreline and inland rivers and creeks that drain to the bay. The integrated tributary-coastal forecast model (Hydro-Coastal Storm Modeling System, or Hydro-CoSMoS) was developed to provide water managers and other users with flood forecast information beyond what is currently available. Results presented here are focused on the interaction of the Napa River watershed and the San Pablo Bay at the northern end of San Francisco Bay. This paper describes the modeling setup, the scenario used in a tabletop exercise (TTE), and the assessment of the various flood forecast information products. Hydro-CoSMoS successfully demonstrated the capability to provide watershed and coastal flood information at scales and locations where no such information is currently available and was also successful in showing how tributary flows could be used to inform the coastal storm model during a flooding scenario. The TTE provided valuable feedback on how to guide continued model development and to inform what model outputs and formats are most useful to end-users.