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Research about Santa Rosa, California

Source-linked reports with geographic coverage including Santa Rosa, California.

6 recordsLinked to original sources

Updating and recalibrating the integrated Santa Rosa Plain Hydrologic Model to assess stream depletion and to simulate future climate and management scenarios in Santa Rosa, Sonoma County, California

The Santa Rosa Plain Hydrologic Model (SRPHM) was developed and published in 2014 through a collaboration between the U.S. Geological Survey (USGS) and Sonoma Water to analyze the hydrologic system in the Santa Rosa Plain watershed, help meet the increasing demand for fresh water, and prepare for future uncertainties in water resources. The original model simulated hydrological conditions and water use from water years 1975 to 2010. Recently (2023), the USGS, in cooperation with Sonoma Water and the California State Water Resources Control Board, updated the SRPHM model to extend its simulation period to the end of the 2018 calendar year, incorporate new estimates of rural and agricultural water use, and use efficient input format for climate variables. The updated model was recalibrated, and evaluation of the new model calibration is included in this report. This report presents the results of comparing the hydraulic heads, streamflow, and groundwater budget simulated by the updated model with those generated by the original model and observed data. The main difference in the simulated budget between the original and updated SRPHM is the estimates of agricultural pumping, rural domestic pumping, and return flow generated from rural water use that was not simulated in the original model. The revised agricultural pumping is simulated using the agricultural package, which constrains pumping to available groundwater. The use of the agricultural package leads to a more realistic estimation of agricultural water use, with revised agricultural pumping being one-third less than that in the original model. The revised rural pumping is about half of the pumping in the original model because of using detailed parcel data to estimate population density in rural areas instead of coarse census tracts. Overall, average total inflows for water years 2006–10 simulated by the updated model were about 2 percent less than the original model, and the average total updated outflows were nearly 5 percent less than the original model. The updated model was then used to generate stream depletion maps, simulate climate change scenarios during 2019–99, and simulate water rights allocation using the Model for Decision Support in Integrated River Basin Management (MODSIM). The results from simulating eight future climate scenarios indicated either an increase in groundwater storage or no significant change in the next 80 years, along with an increase in recharge, an increase in actual evapotranspiration in six out of eight climate projections, and an increase in surface runoff. The increases in the simulated future groundwater storage, recharge, evapotranspiration, and runoff in most climate projections are mainly driven by the projected increase in precipitation in most of the future climate scenarios. The updated model also was used to test a pilot case study demonstrating water-resource allocation among different users with different water rights using the integrated MODSIM-Groundwater and Surface-Water Flow Model (GSFLOW) platform. The updated SRPHM serves as a valuable tool for analyzing historical and future hydrologic conditions in the Santa Rosa Plain watershed and preparing for future uncertainties.

California

Fine-scale surficial soil moisture mapping using UAS-based L-band remote sensing in a mixed oak-grassland landscape

Soil moisture maps provide quantitative information that, along with climate and energy balance, is critical to integrate with hydrologic processes for characterizing landscape conditions. However, soil moisture maps are difficult to produce for natural landscapes because of vegetation cover and complex topography. Satellite-based L-band microwave sensors are commonly used to develop spatial soil moisture data products, but most existing L-band satellites provide only coarse scale (one to tens of kilometers grid size), information that is unsuitable for measuring soil moisture variation at hillslope or watershed-scales. L-band sensors are typically deployed on satellite platforms and aircraft but have been too large to deploy on small uncrewed aircraft systems (UAS). There is a need for greater spatial resolution and development of effective measures of soil moisture across a variety of natural vegetation types. To address these challenges, a novel UAS-based L-band radiometer system was evaluated that has recently been tested in agricultural settings. In this study, L-band UAS was used to map soil moisture at 3–50-m (m) resolution in a 13 square kilometer (km 2 ) mixed grassland-forested landscape in Sonoma County, California. The results represent the first application of this technology in a natural landscape with complex topography and vegetation. The L-band inversion of the radiative transfer model produced soil moisture maps with an average unbiased root mean squared error (ubRMSE) of 0.07 m 3 /m 3 and a bias of 0.02 m 3 /m 3 . Improved fine-scale soil moisture maps developed using UAS-based systems may be used to help inform wildfire risk, improve hydrologic models, streamflow forecasting, and early detection of landslides.

California

Santa Rosa's past and future earthquakes

Santa Rosa is no stranger to earthquakes. This northern California city was damaged several times in the late 19th and early 20th centuries by shaking from earthquakes, culminating in the devastating earthquake of 1906, whose rupture passed 20 miles to the west of the city on the San Andreas Fault. Then in 1969, Santa Rosa was again strongly shaken and buildings were damaged by a pair of nearby, moderate-sized earthquakes on the Rodgers Creek Fault. Since then, scientists have learned how the underlying geology increases shaking damage in Santa Rosa, have mapped where the Rodgers Creek Fault runs beneath the city, and have discovered that this fault is capable of much larger earthquakes. Following the 1969 earthquakes, Santa Rosa rose to the challenge of improving seismic safety; however, continued progress is needed to increase seismic resilience and reduce the impact of future earthquakes.

California

Detailed mapping and rupture implications of the 1 km releasing bend in the Rodgers Creek Fault at Santa Rosa, northern California

Airborne light detection and ranging (lidar) topography reveals for the first time the trace of the Rodgers Creek fault (RCF) through the center of Santa Rosa, the largest city in the northern San Francisco Bay area. Vertical deformation of the Santa Rosa Creek floodplain expresses a composite pull‐apart basin beneath the urban cover that is part of a broader 1‐km‐wide right‐releasing bend in the fault. High‐resolution geophysical data illuminate subsurface conditions that may be responsible for the complex pattern of surface faulting, as well as for the distribution of seismicity and possibly for creep behavior. We identify a dense, magnetic basement body bounded by the RCF beneath Santa Rosa that we interpret as a strong asperity, likely part of a larger locked patch of the fault to the south. A local increase in frictional resistance associated with the basement body appears to explain (1) distributed fault‐normal extension above where the RCF intersects the body; (2) earthquake activity around the northern end of the body, notably the 1969 M L 5.6 and 5.7 events and aftershocks; and (3) creep rates on the RCF that are higher to the north of Santa Rosa than to the south. There is a significant probability of a major earthquake on the RCF in the coming decades, and earthquakes associated with the proposed asperity have the potential to release seismic energy into the Cotati basin beneath Santa Rosa, already known from damaging historical earthquakes to produce amplified ground shaking.

California

Estimating floodplain sedimentation in the Laguna de Santa Rosa, Sonoma County, CA

We present a conceptual and analytical framework for predicting the spatial distribution of floodplain sedimentation for the Laguna de Santa Rosa, Sonoma County, CA. We assess the role of the floodplain as a sink for fine-grained sediment and investigate concerns regarding the potential loss of flood storage capacity due to historic sedimentation. We characterized the spatial distribution of sedimentation during a post-flood survey and developed a spatially distributed sediment deposition potential map that highlights zones of floodplain sedimentation. The sediment deposition potential map, built using raster files that describe the spatial distribution of relevant hydrologic and landscape variables, was calibrated using 2 years of measured overbank sedimentation data and verified using longer-term rates determined using dendrochronology. The calibrated floodplain deposition potential relation was used to estimate an average annual floodplain sedimentation rate (3.6 mm/year) for the ~11 km 2 floodplain. This study documents the development of a conceptual model of overbank sedimentation, describes a methodology to estimate the potential for various parts of a floodplain complex to accumulate sediment over time, and provides estimates of short and long-term overbank sedimentation rates that can be used for ecosystem management and prioritization of restoration activities.

California