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Flood-inundation maps for the Withlacoochee River From Skipper Bridge Road to St. Augustine Road, within the City of Valdosta, Georgia, and Lowndes County, Georgia

Digital flood-inundation maps for a 12.6-mile reach of the Withlacoochee River from Skipper Bridge Road to St. Augustine Road (Georgia State Route 133) were developed to depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey (USGS) streamgage at Withlacoochee River at Skipper Bridge Road, near Bemiss, Ga. (023177483). Real-time stage information from this streamgage can be used with these maps to estimate near real-time areas of inundation. The forecasted peak-stage information for the USGS streamgage at Withlacoochee River at Skipper Bridge Road, near Bemiss, Ga. (023177483), can be used in conjunction with the maps developed for this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers Hydrologic Engineer-ing Center’s River Analysis System (HEC–RAS) software for the Withlacoochee River and was used to compute flood profiles for a 12.6-mile reach of the Withlacoochee River. The hydraulic model was then used to simulate 23 water-surface profiles at 1.0-foot (ft) intervals at the Withlacoochee River near the Bemiss streamgage. The profiles ranged from the National Weather Service action stage of 10.7 ft, which is 131.0 ft above the North American Vertical Datum of 1988 (NAVD 88), to a stage of 32.7 ft, which is 153.0 ft above NAVD 88. The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging (lidar) data having a 4.0-ft horizontal resolution—to delineate the area flooded at each 1.0-ft interval of stream stage.

Georgia

Adverse moisture events predict seasonal abundance of Lyme disease vector ticks (Ixodes scapularis)

Background : Lyme borreliosis (LB) is the most commonly reported vector-borne disease in north temperate regions worldwide, affecting an estimated 300,000 people annually in the United States alone. The incidence of LB is correlated with human exposure to its vector, the blacklegged tick ( Ixodes scapularis ). To date, attempts to model tick encounter risk based on environmental parameters have been equivocal. Previous studies have not considered (1) the differences between relative humidity (RH) in leaf litter and at weather stations, (2) the RH threshold that affects nymphal blacklegged tick survival, and (3) the time required below the threshold to induce mortality. We clarify the association between environmental moisture and tick survival by presenting a significant relationship between the total number of tick adverse moisture events (TAMEs - calculated as microclimatic periods below a RH threshold) and tick abundance each year. Methods : We used a 14-year continuous statewide tick surveillance database and corresponding weather data from Rhode Island (RI), USA, to assess the effects of TAMEs on nymphal populations of I. scapularis . These TAMEs were defined as extended periods of time (>8 h below 82% RH in leaf litter). We fit a sigmoid curve comparing weather station data to those collected by loggers placed in tick habitats to estimate RH experienced by nymphal ticks, and compiled the number of historical TAMEs during the 14-year record. Results : The total number of TAMEs in June of each year was negatively related to total seasonal nymphal tick densities, suggesting that sub-threshold humidity episodes >8 h in duration naturally lowered nymphal blacklegged tick abundance. Furthermore, TAMEs were positively related to the ratio of tick abundance early in the season when compared to late season, suggesting that lower than average tick abundance for a given year resulted from tick mortality and not from other factors. Conclusions : Our results clarify the mechanism by which environmental moisture affects blacklegged tick populations, and offers the possibility to more accurately predict tick abundance and human LB incidence. We describe a method to forecast LB risk in endemic regions and identify the predictive role of microclimatic moisture conditions on tick encounter risk.

Rhode Island

Fire behavior, weather, and burn severity of the 2007 anaktuvuk river tundra fire, North Slope, Alaska

In 2007, the Anaktuvuk River Fire (ARF) became the largest recorded tundra fire on the North Slope of Alaska. The ARF burned for nearly three months, consuming more than 100,000 ha. At its peak in early September, the ARF burned at a rate of 7000 ha d -1 . The conditions potentially responsible for this large tundra fire include modeled record high summer temperature and record low summer precipitation, a late-season high-pressure system located over the Beaufort Sea, extremely dry soil conditions throughout the summer, and sustained southerly winds during the period of vegetation senescence. Burn severity mapping revealed that more than 80% of the ARF burned at moderate to extreme severity, while the nearby Kuparuk River Fire remained small and burned at predominantly (80%) low severity. While this study provides information that may aid in the prediction of future large tundra fires in northern Alaska, the fact that three other tundra fires that occurred in 2007 combined to burn less than 1000 ha suggests site specific complexities associated with tundra fires on the North Slope, which may hamper the development of tundra fire forecasting models.

Arctic, Antarctic, and Alpine Research

New Jersey Tide Telemetry System

Each summer the population of the barrier-island communities of New Jersey increases by tens of thousands. When a coastal storm threatens these communities, the limited number of bridges and causeways that connect the islands with the mainland become overcrowded, making evacuations from the barrier islands to the mainland difficult. Timely evacuation depends on well-defined emergency evacuation plans used in conjunction with accurate flood forecasting and up to the minute (real-time) tide-level information. The 'Great Nor'easter' storm that struck the coastal areas of New Jersey on December 11, 1992, caused about $270 million in insured damages to public and private property (Dorr and others, 1995). Most of the damage was due to tidal flooding and storm surge, which were especially severe along the back bay areas. Comprehensive and reliable tide-level and meteorological data for the back bays was needed to make accurate flood forecasts. Collection of tidal data for the ocean and large bays was adequately covered by the National Oceanic and Atmospheric Administration's National Ocean Service (NOAA's NOS), but in New Jersey little to no data are available for the back-bay areas. The back bays behave quite differently than the ocean as a result of the complex interaction between the winds and the geometry of the inlets and bays. A slow moving Nor'easter can keep tide levels in back bays several feet higher than the ocean tide by not allowing tides to recede, resulting in flooding of bridges and causeways that link the barrier islands to the mainland. The U.S. Geological Survey (USGS), in cooperation with the New Jersey Department of Transportation (NJDOT), designed and installed the New Jersey Tide Telemetry System (NJTTS) with assistance from NOAA's NOS in 1997. This system is part of a statewide network of tide gages, weather stations, and stream gages that collect data in real time. The NJTTS supplies comprehensive, reliable real-time tide-level and meteorological data for flood-prone areas along the New Jersey shore and back bays. These data are transmitted to computer base stations located at offices of the National Weather Service, New Jersey State Police (NJSP), NJDOT, county emergency management agencies, other critical decision-making centers, and the World Wide Web (WWW). This fact sheet describes the NJTTS and identifies its benefits.

Fact Sheet

Characterizing wet slab and glide slab avalanche occurrence along the Going-to-the-Sun Road, Glacier National Park, Montana, USA

Wet slab and glide slab snow avalanches are dangerous and yet can be particularly difficult to predict. Both wet slab and glide slab avalanches are thought to depend upon free water moving through the snowpack but are driven by different processes. In Glacier National Park, Montana, both types of avalanches can occur in the same year and affect the Going-to-the-Sun Road (GTSR). Both wet slab and glide slab avalanches along the GTSR from 2003-2010 are investigated. Meteorological data from two high-elevation weather stations and one SNOTEL site are used in conjunction with an avalanche database and snowpit profiles. These data were used to characterize years when only glide slab avalanches occurred and those years when both glide slab and wet slab avalanches occurred. Results of 168 glide slab and 57 wet slab avalanches along the GTSR suggest both types of avalanche occurrence depend on sustained warming periods with intense solar radiation (or rain on snow) to produce free water in the snowpack. Differences in temperature and net radiation metrics between wet slab and glide slab avalanches emerge as one moves from one day to seven days prior to avalanche occurrence. On average, a more rapid warming precedes wet slab avalanche occurrence. Glide slab and wet slab avalanches require a similar amount of net radiation. Wet slab avalanches do not occur every year, while glide slab avalanches occur annually. These results aim to enhance understanding of the required meteorological conditions for wet slab and glide slab avalanches and aid in improved wet snow avalanche forecasting.

Montana

Nest mortality of sagebrush songbirds due to a severe hailstorm

Demographic assessments of nesting birds typically focus on failures due to nest predation or brood parasitism. Extreme weather events such as hailstorms, however, can also destroy eggs and injure or kill juvenile and adult birds at the nest. We documented the effects of a severe hailstorm on 3 species of sagebrush-associated songbirds: Sage Thrasher ( Oreoscoptes montanus ), Brewer's Sparrow ( Spizella breweri ), and Vesper Sparrow ( Pooecetes gramineus ), nesting at eight 24 ha study plots in central Wyoming, USA. Across all plots, 17% of 128 nests failed due to the hailstorm; however, all failed nests were located at a subset of study plots ( n = 3) where the hailstorm was most intense, and 45% of all nests failures on those plots were due to hail. Mortality rates varied by species, nest architecture, and nest placement. Nests with more robust architecture and those sited more deeply under the shrub canopy were more likely to survive the hailstorm, suggesting that natural history traits may modulate mortality risk due to hailstorms. While sporadic in nature, hailstorms may represent a significant source of nest failure to songbirds in certain locations, especially with increasing storm frequency and severity forecasted in some regions with ongoing climate change.

Wilson Journal of Ornithology

Radar image and data fusion for natural hazards characterisation

Fusion of synthetic aperture radar (SAR) images through interferometric, polarimetric and tomographic processing provides an all - weather imaging capability to characterise and monitor various natural hazards. This article outlines interferometric synthetic aperture radar (InSAR) processing and products and their utility for natural hazards characterisation, provides an overview of the techniques and applications related to fusion of SAR/InSAR images with optical and other images and highlights the emerging SAR fusion technologies. In addition to providing precise land - surface digital elevation maps, SAR - derived imaging products can map millimetre - scale elevation changes driven by volcanic, seismic and hydrogeologic processes, by landslides and wildfires and other natural hazards. With products derived from the fusion of SAR and other images, scientists can monitor the progress of flooding, estimate water storage changes in wetlands for improved hydrological modelling predictions and assessments of future flood impacts and map vegetation structure on a global scale and monitor its changes due to such processes as fire, volcanic eruption and deforestation. With the availability of SAR images in near real - time from multiple satellites in the near future, the fusion of SAR images with other images and data is playing an increasingly important role in understanding and forecasting natural hazards.

International Journal of Image and Data Fusion

Integrating environmental DNA results with diverse data sets to improve biosurveillance of river health

Autonomous, robotic environmental (e)DNA samplers now make it possible for biological observations to match the scale and quality of abiotic measurements collected by automated sensor networks. Merging these automated data streams may allow for improved insight into biotic responses to environmental change and stressors. Here, we merged eDNA data collected by robotic samplers installed at three U.S. Geological Survey (USGS) streamgages with gridded daily weather data, and daily water quality and quantity data into a cloud-hosted database. The eDNA targets were a rare fish parasite and a more common salmonid fish. We then used computationally expedient Bayesian hierarchical occupancy models to evaluate associations between abiotic conditions and eDNA detections and to simulate how uncertainty in result interpretation changes with the frequency of autonomous robotic eDNA sample collection. We developed scripts to automate data merging, cleaning and analysis steps into a chained-step, workflow. We found that inclusion of abiotic covariates only provided improved insight for the more common salmonid fish since its DNA was more frequently detected. Rare fish parasite DNA was infrequently detected, which caused occupancy parameter estimates and covariate associations to have high uncertainty. Our simulations found that collecting samples at least once per day resulted in more detections and less parameter uncertainty than less frequent sampling. Our occupancy and simulation results together demonstrate the advantages of robotic eDNA samplers and how these samples can be combined with easy to acquire, publicly available data to foster real-time biosurveillance and forecasting.

Idaho, Wyoming, Montana

Flood-inundation maps for the Yellow River from River Drive to Centerville Highway, Gwinnett County, Georgia

Digital flood-inundation maps for a 16.4-mile reach of the Yellow River in Gwinnett County, Georgia, from 0.5 mile upstream from River Drive to Centerville Highway (Georgia State Route 124) were developed to depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at two U.S. Geological Survey (USGS) streamgages in the mapped area. The maps for the 9.0-mile reach from 0.5 mile upstream from River Drive to Stone Mountain Highway (U.S. Route 78) are referenced to the streamgage Yellow River near Snellville, Ga. (station 02206500), and the maps for the 7.4-mile reach from Stone Mountain Highway to Centerville Highway are referenced to the streamgage Yellow River at Ga. 124, near Lithonia, Ga. (02207120). Real-time stage information from these streamgages can be used with these maps to estimate near real-time areas of inundation. The forecasted peak-stage information for the USGS streamgages Yellow River near Snellville, Ga. (02206500), and Yellow River at Ga. 124, near Lithonia, Ga. (02207120), can be used in conjunction with the maps developed for this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers Hydrologic Engineering Center's River Analysis System (HEC–RAS) software for the Yellow River and was used to compute flood profiles for a 16.4-mile reach of the Yellow River. The hydraulic model was then used to simulate 16 water-surface profiles at 1.0-foot (ft) intervals at the Yellow River near Snellville streamgage and 17 water-surface profiles at 1.0-ft intervals at the Yellow River near Lithonia streamgage. At the Yellow River near Snellville streamgage, the profiles ranged from a stage of 18.0 ft, which is 819.1 ft above the North American Vertical Datum of 1988 (NAVD 88), to a stage of 33.0 ft, which is 834.1 ft above NAVD 88. At the Yellow River near Lithonia streamgage, the profiles ranged from the National Weather Service action stage of 13.0 ft, which is 732.5 ft above NAVD 88, to a stage of 29.0 ft, which is 748.5 ft above NAVD 88. The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging (lidar) data having a 5.0-ft horizontal resolution—to delineate the area flooded at each 1.0-ft interval of stream stage for both streamgages.

Georgia

Spatially explicit modeling of 1992-2100 land cover and forest stand age for the conterminous United States

Information on future land-use and land-cover (LULC) change is needed to analyze the impact of LULC change on ecological processes. The U.S. Geological Survey has produced spatially explicit, thematically detailed LULC projections for the conterminous United States. Four qualitative and quantitative scenarios of LULC change were developed, with characteristics consistent with the Intergovernmental Panel on Climate Change (IPCC) Special Report on 5 Emission Scenarios (SRES). The four quantified scenarios (A1B, A2, B1, and B2) served as input to the Forecasting Scenarios of Land-use Change (FORE-SCE) model. Four spatially explicit datasets consistent with scenario storylines were produced for the conterminous United States, with annual LULC maps from 1992 through 2100. The future projections are characterized by a loss of natural land covers in most scenarios, with corresponding expansion of 10 anthropogenic land uses. Along with the loss of natural land covers, remaining natural land covers experience increased fragmentation under most scenarios, with only the B2 scenario remaining relatively stable in both proportion of remaining natural land covers and basic fragmentation measures. Forest stand age was also modeled. By 2100, scenarios and ecoregions with heavy forest cutting have relatively lower mean stand ages compared to those with less 15 forest cutting. Stand ages differ substantially between unprotected and protected forest lands, as well as between different forest classes. The modeled data were compared to the National Land Cover Database (NLCD) and other data sources to assess model characteristics. The consistent, spatially explicit, and thematically detailed LULC projections and the associated forest stand age data layers have been used to analyze LULC impacts on carbon and greenhouse gas fluxes, 20 biodiversity, climate and weather variability, hydrologic change, and other ecological processes.

Ecological Applications

Preliminary viability assessment of Lake Mendocino forecast informed reservoir operations

This report describes the preliminary viability assessment (PVA) of forecast informed reservoir operations (FIRO) for Lake Mendocino, which is located on the East Fork Russian River three miles east of Ukiah, California. The results described in this report represent the collective activities of the Lake Mendocino FIRO Steering Committee (SC) (SC members are named on the inside cover of the report). The SC consists of water managers and scientists from several federal, state, and local agencies, and universities who have teamed to evaluate whether current technology and scientific understanding can be utilized to improve reliability of meeting water management objectives of Lake Mendocino while not impairing flood protection. While the PVA provides an initial evaluation of the viability of FIRO as a concept, additional steps remain to complete the full viability assessment (FVA). Also, the PVA does not identify how FIRO strategies would be implemented. That effort would be the focus of the FVA, which builds off the analyses developed in the PVA. This report summarizes current Lake Mendocino operation and a preliminary analysis of FIRO alternatives, including analysis methods, results, and recommendations. A set of accompanying reports describes the analysis in detail. These are referred to herein as the Sonoma County Water Agency (SCWA) report, the Hydrologic Engineering Center (HEC) report, and the Center for Western Weather and Water Extremes (CW3E) report (SCWA 2017, USACE 2017, and CW3E 2017, respectively).

California

Operation of a landslide warning system during the California storm sequence of January and February 1993

From 1986 to late December 1995, the U.S. Geological Survey and the National Weather Service operated a landslide warning system for debris flows triggered by intense rainstorms in the San Francisco Bay region. The Landslide Warning System tracked storm systems as they approached the region, determined actual rainfall with a network of radio-telemetered rain gauges, compared the rainfall to thresholds for initi-ation of debris flows, and issued the appropriate public advisories. A series of intense rainstorms during January 1993 created hazards from landslid-ing and flooding over much of California. In the San Francisco Bay region, January rainfall was over 200% of normal, triggering debris flows on natural hillslopes and road cuts across Marin, San Mateo, Alameda, Santa Clara, and Santa Cruz Counties. The warning system issued Flash Flood/Debris Flow Watches during the most intense storms on January 13 and 15,1993. Most debris flows in this area were small and widely scattered, so damage was largely limited to several blocked roadways in mountainous areas. Storm damage was much heavier in southern California, where rainfall amounts were over 350% of normal for January, triggering flash floods and many landslides. This damage prompted inquiries about developing a landslide warning system for southern California. A number of elements for a landslide warning system already exist in southern Cal-ifornia, including quantitative rainfall forecasting and a network of radio-telemetered rain gauges. Regional rainfall thresholds for debris flow initiation, consistent with the climate, topography, and geology of the region, remain to be developed. Such thresholds could probably be developed with a modest investment of research effort and resources.

California

Processes controlling the episodic streamwater transport of atrazine and other agrichemicals in an agricultural watershed

Episodic streamwater transport of atrazine (a common agricultural herbicide) and nutrients has been observed throughout agricultural watersheds in the United States and poses a serious threat to the quality of its water resources. Catchment-scale atrazine and nutrient transport processes after agricultural application are still poorly understood, and predicting episodic streamwater composition remains an elusive goal. We instrumented a 1.2-km 2 agricultural catchment near Harrisonburg, Virginia, and examined streamwater, overland flow, soil water, groundwater, and rainfall during the summer of 1998. Storm chemographs demonstrated different patterns for constituents derived primarily from weathering (silica and calcium), compared to constituents derived primarily from early spring land applications (nitrate, atrazine, DOC, potassium, chloride, and sulfate). During storms, the concentrations of silica and calcium decreased, the atrazine response was variable, and the concentrations of nitrate, DOC, potassium, chloride, and sulfate increased; the elevated nitrate signal lagged several hours behind the other elevated constituents. Graphical and statistical analyses indicated a relatively stable spring-fed baseflow was modified by a mixture of overland flow and soil water. A rapid, short-duration overland-flow pulse dominated the streamflow early in the event and contributed most of the potassium, DOC, chloride, suspended sediment, and atrazine. A longer-duration soil–water pulse dominated the streamflow later in the event and contributed the nitrate as well as additional potassium, DOC, sulfate, and atrazine. The contributions to the episodic streamflow were quantified using a flushing model in which overland-flow and soil–water concentrations decreased exponentially with time during an episode. Flushing time constants for the overland-flow and soil–water reservoirs were calculated on a storm-by-storm basis using separate tracers for each time-variable reservoir. Initial component concentrations were estimated through regression analyses. Mass-balance calculations were used for flow separations and to predict the observed streamwater composition. Model forecasts indicated that reduced fertilizer and pesticide application (rather than elimination of overland-flow or soil–water contributions) was necessary to improve the episodic streamwater composition. This study provides important additional understanding of the catchment-scale processes by which land-applied pesticides and nutrients can move through agricultural systems.

Virginia

Fire activity as a function of fire–weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA

Climate has a strong influence on fire activity, varying across time and space. We analyzed the relationships between fire–weather conditions during the main fire season and antecedent water-balance conditions and fires in two Mediterranean-type regions with contrasted management histories: five southern countries of the European Union (EUMED)(all fires); the Pacific western coast of the USA (California and Oregon, PWUSA)(national forest fires). Total number of fires (≥1 ha), number of large fires (≥100 ha) and area burned were related to mean seasonal fire weather index (FWI), number of days over the 90th percentile of the FWI, and to the standardized precipitation-evapotranspiration index (SPEI) from the preceding 3 (spring) or 8 (autumn through spring) months. Calculations were made at three spatial aggregations in each area, and models related first-difference (year-to-year change) of fires and FWI/climate variables to minimize autocorrelation. An increase in mean seasonal FWI resulted in increases in the three fire variables across spatial scales in both regions. SPEI contributed little to explain fires, with few exceptions. Negative water-balance (dry) conditions from autumn through spring (SPEI8) were generally more important than positive conditions (moist) in spring (SPEI3), both of which contributed positively to fires. The R2 of the models generally improved with increasing area of aggregation. For total number of fires and area burned, the R2 of the models tended to decrease with increasing mean seasonal FWI. Thus, fires were more susceptible to change with climate variability in areas with less amenable conditions for fires (lower FWI) than in areas with higher mean FWI values. The relationships were similar in both regions, albeit weaker in PWUSA, probably due to the wider latitudinal gradient covered in PWUSA than in EUMED. The large variance explained by some of the models indicates that large-scale seasonal forecast could help anticipating fire activity in the investigated areas.

California, Oregon

Climate variation at Flagstaff, Arizona - 1950 to 2007

Much scientific research demonstrates the existence of recent climate variation, particularly global warming. Climate prediction models forecast that climate will change; it will become warmer, droughts will increase in number and severity, and extreme climate events will recur often—desiccating aridity, extremely wet, unusually warm, or even frigid at times. However, the global models apply to average conditions in large grids approximately 150 miles on an edge (Thorpe, 2005), and how or whether specific areas within a grid are affected is unclear. Flagstaff's climate is mentioned in the context of global change, but information is lacking on the amount and trend of changes in precipitation, snowfall, and temperature. The purpose of this report is to understand what may be happening to Flagstaff's climate by reviewing local climate history. Flagstaff is in north-central Arizona south of San Francisco Mountain, which reaches 12,633 feet, the highest in Arizona (fig. 1). At 6,900 feet, surrounded by ponderosa pine forest, Flagstaff enjoys a four-season climate; winter-daytime temperatures are cool, averaging 45 degrees (Fahrenheit). Summer-daytime temperatures are comfortable, averaging 80 degrees, which is pleasant compared with nearby low-elevation deserts. Flagstaff's precipitation averages 22-inches per year with a range of 9 to 39 inches. Snowfall occurs each season, averaging 97 inches annually. This report, written for the non-technical reader, interprets climate variation at Flagstaff as observed at the National Weather Service (NWS) station at Pulliam Field (or Airport), a first-order weather station staffed by meteorologists (Staudenmaier and others, 2007). The station is on a flat-topped ridge surrounded by forest 5-miles south of Flagstaff at an elevation of 7,003 feet. Data used in this analysis are daily measurements of precipitation (including snowfall) and temperature (maximum and minimum) covering the period from 1950, when the station began operation, through spring 2007. Conversations with Byron Peterson and Michael Staudenmaier of the NWS helped us understand the difficulties of collecting consistent weather data, operation of the station, and Flagstaff's climate. Weather is the daily or even instantaneous state of temperature and precipitation. Climate is the average or accumulation of these parameters over longer time scales such as a week, month, or year. Seasonal (winter, spring, summer, and fall) and annual averages of temperature and accumulated precipitation describe the temporal variation of Flagstaff's climate, which is shown graphically with time series (figs. 2, 4, 6, 8-15). These plots show precipitation or temperature on the ordinate plotted against time on the abscissa, which is a year for annually repeating data or the year of a particular season. The plots reveal changing patterns of precipitation and temperature related to droughts, wet episodes, and rising temperatures.

Arizona

Evaluation of SNODAS snow depth and snow water equivalent estimates for the Colorado Rocky Mountains, USA

The National Weather Service's Snow Data Assimilation (SNODAS) program provides daily, gridded estimates of snow depth, snow water equivalent (SWE), and related snow parameters at a 1-km 2 resolution for the conterminous USA. In this study, SNODAS snow depth and SWE estimates were compared with independent, ground-based snow survey data in the Colorado Rocky Mountains to assess SNODAS accuracy at the 1-km 2 scale. Accuracy also was evaluated at the basin scale by comparing SNODAS model output to snowmelt runoff in 31 headwater basins with US Geological Survey stream gauges. Results from the snow surveys indicated that SNODAS performed well in forested areas, explaining 72% of the variance in snow depths and 77% of the variance in SWE. However, SNODAS showed poor agreement with measurements in alpine areas, explaining 16% of the variance in snow depth and 30% of the variance in SWE. At the basin scale, snowmelt runoff was moderately correlated ( R 2 = 0.52) with SNODAS model estimates. A simple method for adjusting SNODAS SWE estimates in alpine areas was developed that uses relations between prevailing wind direction, terrain, and vegetation to account for wind redistribution of snow in alpine terrain. The adjustments substantially improved agreement between measurements and SNODAS estimates, with the R 2 of measured SWE values against SNODAS SWE estimates increasing from 0.42 to 0.63 and the root mean square error decreasing from 12 to 6 cm. Results from this study indicate that SNODAS can provide reliable data for input to moderate-scale to large-scale hydrologic models, which are essential for creating accurate runoff forecasts. Refinement of SNODAS SWE estimates for alpine areas to account for wind redistribution of snow could further improve model performance. Published 2011. This article is a US Government work and is in the public domain in the USA.

Colorado

Floods of 1952 in the basins of the upper Mississippi River and Red River of the North

The flood of April 1952 on the Mississippi River between the Minnesota and Des Moines Rivers established many record-high stages. In the Minnesota River basin, the floods of April 1952 exceeded those of 1951 in many locations but generally were smaller than those of 1881. The timing of flows on the Mississippi and Minnesota Rivers was favorable for the highest possible peak flow at and downstream from St. Paul. Below the Wisconsin River, the 1951 and 1952 floods on the Mississippi River were of approximately equal size. The experiences gained in fighting the flood of 1951 proved valuable in preventing much flood damage in 1952. Because the floods generally moved slowly, few lives were lost, and there was ample time for construction of emergency levees. Many urban areas flooded in 1951 were not damaged by floods of equal or greater size in 1952. The total flood damage in the Mississippi River basin above Keokuk, Iowa, was estimated by the Corps of Engineers to be $19,376,000. Snow surveys made during mid-March did not show conclusively that major floods were to be expected. The snow surveys showed small areas of high water content at the headwaters of both the Mississippi and Minnesota Rivers and above-normal snow cover over most of the upper Mississippi River basin. Heavy snowfall occurred over most of Minnesota, especially in the southern part, on March 22-23, 1952. Cold weather delayed the breakup until a period when more rapid melt was probable. These factors definitely set the stage for the floods. A rapid rise in temperature at the end of March and early April started the melting of the snow. Because the topsoil had been frozen when wet during the preceding fall, very little of the snowmelt was absorbed by the ground. Runoff in southeastern Minnesota occurred earliest and with greatest rapidity; the Root River crested at Rushford on March 31. Runoff in the Minnesota River basin occurred later and at a slower rate. Floods on the Red River of the North and its tributaries above Fargo occurred during April 1952 and were due to the same factors that caused flooding in the Minnesota River basin. Because the snow cover was light in the drainage basin north of (below) Fargo, flooding was serious for only that part of the basin at and upstream from Fargo. The 1952 flood on Red River of the North at Fargo was the greatest since 1897, and flood damage for the basin was heaviest in the urban area of Fargo-Moorhead. The 1952 floods in the upper Mississippi basin occurred 1 year after the greatest floods known in the area since 1881. The 1952 stages and discharges on the Mississippi River from St. Paul to the Wisconsin River slightly exceeded those of 1951; below the Wisconsin River, the stages and discharges of the 2 years were about equal. The similarity in the hydrographs of the 1951 and 1952 floods along the Mississippi River between McGregor and Keokuk, Iowa, is interesting and revealing. Forecasts of the 1952 flood events were accurate and timely, owing to the experience gained in 1951. The flood crests on the upper Mississippi and the Missouri Rivers nearly coincided at St. Louis. Because the Missouri crest reached St. Louis about 2 days before the Mississippi crest, the peak discharge at St. Louis was not exceptional.

Water Supply Paper

Predicting sea-level rise vulnerability of terrestrial habitat and wildlife of the Northwestern Hawaiian Islands

If current climate change trends continue, rising sea levels may inundate low-lying islands across the globe, placing island biodiversity at risk. Recent models predict a rise of approximately one meter (1 m) in global sea level by 2100, with larger increases possible in areas of the Pacific Ocean. Pacific Islands are unique ecosystems home to many endangered endemic plant and animal species. The Northwestern Hawaiian Islands (NWHI), which extend 1,930 kilometers (km) beyond the main Hawaiian Islands, are a World Heritage Site and part of the Papahanaumokuakea Marine National Monument. These NWHI support the largest tropical seabird rookery in the world, providing breeding habitat for 21 species of seabirds, 4 endemic land bird species and essential foraging, breeding, or haul-out habitat for other resident and migratory wildlife. In recent years, concern has grown about the increasing vulnerability of the NWHI and their wildlife populations to changing climatic patterns, particularly the uncertainty associated with potential impacts from global sea-level rise (SLR) and storms. In response to the need by managers to adapt future resource protection strategies to climate change variability and dynamic island ecosystems, we have synthesized and down scaled analyses for this important region. This report describes a 2-year study of a remote northwestern Pacific atoll ecosystem and identifies wildlife and habitat vulnerable to rising sea levels and changing climate conditions. A lack of high-resolution topographic data for low-lying islands of the NWHI had previously precluded an extensive quantitative model of the potential impacts of SLR on wildlife habitat. The first chapter (chapter 1) describes the vegetation and topography of 20 islands of Papahanaumokuakea Marine National Monument, the distribution and status of wildlife populations, and the predicted impacts for a range of SLR scenarios. Furthermore, this chapter explores the potential effects of SLR on wildlife breeding habitats for each island. The subsequent chapter (chapter 2) details a study of the Laysan Island ecosystem, describing a quantitative model that incorporates SLR, storm wave, and rising groundwater inundation. Wildlife, storm, and oceanographic data allowed for an assessment of the phenological and spatial vulnerability of Laysan Island's breeding bird species to SLR and storms. Using remote sensing and geospatial techniques, we estimated topography, classified vegetation, modeled SLR, and evaluated a range of climate change scenarios. On the basis of high-resolution airborne data collected during 2010-11 (root-mean-squared error = 0.05-0.18 m), we estimated the maximum elevation of 20 individual islands extending from Kure Atoll to French Frigate Shoals (range: 1.8-39.7 m) and computed the mean elevation (1.7 m, standard deviation 1.1 m) across all low-lying islands. We also analyzed general climate models to describe rainfall and temperature scenarios expected to influence adaptation of some plants and animals for this region. Outcomes for the NWHI predicted an increase in temperature of 1.8-2.6 degrees Celsius (°C) and an annual decrease in precipitation of 24.7-76.3 millimeters (mm) across the NWHI by 2100. Our models of passive SLR (excluding wave-driven effects, erosion, and accretion) showed that approximately 4 percent of the total land area in the NWHI will be lost with scenarios of +1.0 m of SLR and 26 percent will be lost with +2.0 m of SLR. Some atolls are especially vulnerable to SLR. For example, at Pearl and Hermes Atoll our analysis indicated substantial habitat losses with 43 percent of the land area inundated at +1.0 m SLR and 92 percent inundated at +2.0 m SLR. Across the NWHI, seven islands will be completely submerged with +2.0 m SLR. The limited global ranges of some tropical nesting birds make them particularly vulnerable to climate change impacts in the NWHI. Climate change scenarios and potential SLR impacts presented here emphasize the need for early climate change adaptation and mitigation planning, especially for species with limited breeding distributions and/or ranges restricted primarily to the low-lying NWHI: Cyperus pennatiformis var. bryanii , Black-footed Albatross ( Phoebastria nigripes ), Laysan Albatross ( P. immutabilis ), Bonin Petrel ( Pterodroma hypoleuca ), Gray-backed Tern ( Onychoprion lunatus ), Laysan Teal ( Anas laysanensis ), Laysan Finch ( Telespiza cantans ), and Hawaiian monk seal ( Monachus schauinslandi ). Furthermore, SLR scenarios that include the effects of wave dynamics and groundwater rise may indicate amplified vulnerability to climate change driven habitat loss on low-lying islands. In chapter 2, we incorporated the combined effects of SLR, dynamic wave-driven inundation, and rising groundwater in a quantitative study specifically for the Laysan Island ecosystem. This is the first hydrodynamic model to simulate the combined impacts of SLR and wave-driven inundation in the NWHI. We developed a high-resolution digital elevation model (mean vertical accuracy of 0.32 m) for the island. Then using recent satellite imagery, geospatial models, and historical oceanographic, storm, and biological data we estimated potential inundation extent, habitat loss, and wildlife population impacts for a range of potential SLR scenarios (0.00, +0.50, +1.00, +1.50, and +2.00 m) that may occur over the next century. Additionally, we estimated the carrying capacity of Laysan Island for five species based on the available population monitoring data and described how potential losses in nesting habitat could influence population dynamics for Black-footed Albatross, Laysan Albatross, Red-footed Booby (Sula sula), Laysan Teal, and Laysan Finch. For some other seabird populations (Masked Booby, S. dactylatra ; Brown Booby, S. leucogaster ; Great Frigatebird, Fregata minor ; and Sooty Tern, Onychoprion fuscata ), we used recent colony distribution data, land cover maps, and nesting behavior to estimate potential losses of nesting habitat from SLR and wave-driven inundation. We observed far greater potential impacts of SLR to wildlife with the dynamic wave-driven modeling approach than with the passive modeling approach. Depending on SLR scenario and coastal orientation, during storms under a +2.00 m SLR scenario, the wave-driven inundation model predicted three times more inundation than the passive model (17.2 percent of total terrestrial area versus 4.6 percent, respectively). Large-wave events generally added 1 m of water height to passive inundation surfaces, therefore our dynamic models (during storm events) forecasted comparable inundation extents earlier than passive models. Although wave-driven water levels were highest in the northwest quadrant of Laysan Island, the greatest extent of inundation occurred in the southeast where coastal dunes less than 3 m above mean sea level provide little protection from wave-driven inundation. When wave-driven inundation was included in the SLR model for Laysan Island greater nesting habitat loss and potential impacts on wildlife population dynamics were predicted. The consequences of habitat loss due to SLR may be worse for species with colonies in the wave-exposed coastal zones (for example, Black-footed Albatross) and for populations already near the island's carrying capacity (for example, Laysan Teal). Species whose peak incubation and chick-rearing periods coincide with seasonally high wave heights also will be increasingly vulnerable, especially those species nesting on the ground in areas vulnerable to inundation, such as Gray-backed Tern and Black-footed Albatross. Other species that have space for population growth, or are not restricted to a narrow range of habitat types on Laysan (for instance, Sooty Terns), may be less sensitive to habitat loss from SLR over the next century. Our assessments of inundation risk, habitat loss, and wildlife species vulnerability synthesize current knowledge about individual islands and contribute to a broader understanding of the impacts of inundation from SLR and storm-induced waves. Yet, most NWHI and their bird populations lack monitoring data to evaluate adaptations to and impacts of climate change. Exceptions include some data sets from long-term monitoring of wildlife populations, tides, or weather at French Frigate Shoals, Laysan Island, and Midway Atoll. These data sets are potentially valuable baselines, which could be informative for adaptive learning (integrating management and science) to predict, adapt, and mitigate the effects of climate change on NWHI wildlife in the future. This study provides the first quantitative vulnerability assessment for all of the low-lying NWHI, and results identify biological communities, locales, and resident endangered species of Papahanaumokuakea Marine National Monument expected to be at risk from SLR. This report is also intended as a reference for managers and conservation planners, a tool to identify and potentially reduce uncertainty, and a starting place for developing climate change monitoring priorities and future scientific studies.

Hawai'i