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Future changes in the number of dry days per year can either reinforce or counteract projected increases in daily precipitation intensity as the climate warms. We analyze climate model projected changes in the number of dry days using 28 coupled global climate models from the Coupled Model Intercomparison Project, version 5 (CMIP5). We find that the Mediterranean Sea region, parts of Central and South America, and western Indonesia could experience up to 30 more dry days per year by the end of this century. We illustrate how changes in the number of dry days and the precipitation intensity on precipitating days combine to produce changes in annual precipitation, and show that over much of the subtropics the change...
Exposure (vulnerability) index for the future time period (2061-2080) representing projected climate conditions from the Meteorological Research Institute's Coupled Atmosphere-Ocean General Circulation Model, version 3, and the rcp85 emissions scenario. The exposure model uses LANDFIRE vegetation data and Worldclim climate data .The raster values represent exposure scores for the corresponding vegetation type. The modeled vegetation types can be spatially associated with the exposure values by overlaying them with the "landfire_veg_sw_300m.tif" raster.Exposure values represent where the location falls in climate space relative to its recent historical distribution:5 (core 5% of historical climate space); 10 (5 -...
This code computes the analytical solution for the damping of sinusoidal infiltration in variably saturated soils described by Bakker and Neiber (2009) and implemented by Dickinson et al. (2014). The usage of the code is documented in the appendix of Dickinson et al. (2014). Bakker, M., Nieber, J.L., 2009. Damping of sinusoidal surface flux fluctuations with soil depth. Vadose Zone J. 8, 119–126,http://dx.doi.org/10.2136/vzj2008.0084. Dickinson, J.E., Ferré, T.P.A., Bakker, M., Crompton, B., 2014. A screening tool for delineating subregions of steady recharge within groundwater models.Vadose Zone J. 13, 15, http://dx.doi.org/10.2136/vzj2013.10.0184. The code can be obtained at http://az.water.usgs.gov/software/damp.html
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To assess the current topography of the tidal marshes we conducted survey-grade elevation surveys at all sites between 2009 and 2013 using a Leica RX1200 Real Time Kinematic (RTK)Global Positioning System (GPS) rover (±1 cm horizontal, ±2 cm vertical accuracy; Leica Geosystems Inc., Norcross, GA; Figure 4). At sites with RTK network coverage (San Pablo, Petaluma, Pt. Mugu, and Newport), rover positions were received in real time from the Leica Smartnet system via a CDMA modem (www.lecia-geosystems.com). At sites without network coverage (Humboldt, Bolinas, Morro and Tijuana), rover positions were received in real time from a Leica GS10 antenna base station via radio link. When using the base station, we adjusted...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for tidal marsh areas around San Francisco Bay using the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). Survey-grade GPS survey data (6614 points), NAIP-derived Normalized Difference Vegetation Index, and original 1 m lidar DEM from 2010 were used to generate a model of predicted bias across tidal marsh areas. The predicted bias was then subtracted from the original lidar DEM and merged with the NOAA...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for Suisun marsh using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (6912 points, collected across public and private land in 2018), Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image (June 2018), a 1 m lidar DEM from September 2018, and a 1 m canopy surface model were used to generate models of predicted bias across the...
How quickly a lake fills after water is drawn for irrigation or drinking is easily measured, but that’s not true for underground water reserves, called aquifers. Because it takes place belowground, groundwater replenishment—or recharge—can’t be directly observed. Scientists must estimate it, often by using complex mathematical models. A new screening tool may now ease the task.
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We performed bathymetric surveys using a shallow-water echo-sounding system (Takekawa et al., 2010, Brand et al., 2012) comprised of an acoustic profiler (Navisound 210; Reson, Inc., Slangerup, Denmark), Leica RTK GPS Viva rover, and laptop computer mounted on a shallow-draft, portable flat-bottom boat (Bass Hunter, Cabelas, Sidney, NE; Figure 7). The RTK GPS obtained high resolution elevations of the water surface (reported precision 10 cm water depth. We recorded twenty depth readings and one GPS location each second along transects spaced 100 m apart perpendicular to the nearby salt marsh. We calibrated the system before use with a bar-check plate and adjusted the sound velocity for salinity and temperature differences....
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We performed bathymetric surveys using a shallow-water echo-sounding system (Takekawa et al., 2010, Brand et al., 2012) comprised of an acoustic profiler (Navisound 210; Reson, Inc., Slangerup, Denmark), Leica RTK GPS Viva rover, and laptop computer mounted on a shallow-draft, portable flat-bottom boat (Bass Hunter, Cabelas, Sidney, NE; Figure 7). The RTK GPS obtained high resolution elevations of the water surface (reported precision 10 cm water depth. We recorded twenty depth readings and one GPS location each second along transects spaced 100 m apart perpendicular to the nearby salt marsh. We calibrated the system before use with a bar-check plate and adjusted the sound velocity for salinity and temperature differences....
Abstract (from http://journals.ametsoc.org/doi/abs/10.1175/JHM-D-14-0236.1): Global climate model (GCM) output typically needs to be bias corrected before it can be used for climate change impact studies. Three existing bias correction methods, and a new one developed here, are applied to daily maximum temperature and precipitation from 21 GCMs to investigate how different methods alter the climate change signal of the GCM. The quantile mapping (QM) and cumulative distribution function transform (CDF-t) bias correction methods can significantly alter the GCM’s mean climate change signal, with differences of up to 2°C and 30% points for monthly mean temperature and precipitation, respectively. Equidistant quantile...
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To assess the current topography of the tidal marshes we conducted survey-grade elevation surveys at all sites between 2009 and 2013 using a Leica RX1200 Real Time Kinematic (RTK)Global Positioning System (GPS) rover (±1 cm horizontal, ±2 cm vertical accuracy; Leica Geosystems Inc., Norcross, GA; Figure 4). At sites with RTK network coverage (San Pablo, Petaluma, Pt. Mugu, and Newport), rover positions were received in real time from the Leica Smartnet system via a CDMA modem (www.lecia-geosystems.com). At sites without network coverage (Humboldt, Bolinas, Morro and Tijuana), rover positions were received in real time from a Leica GS10 antenna base station via radio link. When using the base station, we adjusted...


map background search result map search result map San Pablo, California: Tidal Marsh Digital Elevation Model Tijuana: Tidal Marsh Digital Elevation Model Humboldt, California: Tidal Marsh Bathymetry Digital Elevation Model San Pablo, California: Tidal Marsh Bathymetry Digital Elevation Models LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 LEAN-Corrected DEM for Suisun Marsh Tijuana: Tidal Marsh Digital Elevation Model San Pablo, California: Tidal Marsh Bathymetry Digital Elevation Models LEAN-Corrected DEM for Suisun Marsh LEAN-corrected San Francisco Bay Digital Elevation Model, 2018