Geology topics

David M. Bjerklie

Publications and source records attributed to David M. Bjerklie.

At least 19 recordsLinked to original sources

USGS2026

Estimating baseline flow resistance parameters for remote sensing river discharge (RSQ) from river morphology characteristics

This study demonstrates that flow resistance in rivers, quantified via calibration of a modified Manning equation, can be estimated from channel hydrometric information available from globally derived data sets for a subset of river reaches in Alaska and with less certainty in a subset of river reaches in the contiguous United States. The channel morphometry data sets tested include the National Aeronautics and Space Administration (NASA) Surface Water Ocean Topography (SWOT) river database (SWORD) and U.S. Geological Survey (USGS) Scale Specific Sinuosity (S3) river channel morphometry metrics. It is found that for the subset of rivers considered, the meander length, number of active channels, maximum width, width variance, and slope of the channel are strongly correlated with the flow resistance term in the Manning equation. Analytical machine learned models were derived, and a statistical multiple regression model developed to map the flow resistance in rivers across Alaska that are contained in the SWORD data base. The study points to the possibility of global a priori estimation of flow resistance in rivers for application in remote sensing of river discharge from river water surface-width, slope and height measurements made by SWOT and other satellites.

Journal of the American Water Resources Associatio↗

USGS2025

A first look at river discharge estimation from SWOT satellite observations

The Surface Water and Ocean Topography (SWOT) satellite has the potential to transform global hydrologic science by offering simultaneous and synoptic estimates of river discharge and other hydraulic variables. Discharge is estimated from SWOT observations of water surface elevation, width, and slope. A first assessment using just the highest quality SWOT measurements, over the first 15 months (March 2023–July 2024) of the mission evaluated at 65 gauged reaches shows results consistent with pre-launch expectations. SWOT estimates track discharge dynamics without relying on any gauge information: median correlation is 0.73, with a correlation interquartile range of 0.51–0.89. SWOT estimates capture discharge magnitude correctly in some cases but are biased (median bias is 50%) in others. There are already a total of 11,274 ungauged global locations with highest quality SWOT measurements where SWOT discharge is expected to accurately track discharge variations: this value will increase as SWOT data record length grows, algorithms are refined and SWOT measurements are reprocessed. This first look indicates that SWOT discharge is performing as expected for SWOT data that achieve performance requirements, providing observed information on discharge variations in ungauged basins globally.

Ohio River basin↗

USGS2024

Siting considerations for satellite observation of river discharge

With growing global capability for satellite measurement of river discharge (flow) comes a need to understand and reduce error in satellite-based discharge measurements. Satellite-based discharge estimates are based on measurements of water surface width, elevation, slope, and potentially velocity. Site selection is important for reducing error and uncertainty in both conventional and satellite-based discharge measurements because geomorphic river characteristics have strong control over the relationships between discharge and width, water surface elevation (or depth), slope, and velocity. A large ground-truth data set of 8,445 conventional hydraulic measurements, collected by acoustic Doppler current profilers at 503 stations in the United States, was developed and quality assured to examine correlation between river discharge and water surface width, depth, velocity, and cross-sectional area. A separate database of river surface slope and discharge time-series was developed from paired continuous monitoring stations to examine slope-discharge correlations. Results show that discharge correlates most strongly with velocity, cross-sectional area, depth, width, and slope, in that order. Uncertainty of satellite discharge estimates is affected by observed hydraulic variable and reach-specific variability in observed variable(s) characteristics including range of variability, georegistration accuracy, and stability over time of relationships between discharge and observed hydraulic variable.

Water Resources Research↗

USGS2023

A framework for estimating global river discharge from the Surface Water and Ocean Topography satellite mission

The Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new data sets for both gaged and ungaged basins. SWOT discharge products (available approximately 1 year after launch) will provide discharge for all river that reaches wider than 100 m. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present for the first time a complete estimate of the SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge time series. We expect that discharge uncertainty will be less than 30% for two-thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these “gage-constrained” discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge time series will be dominated by random error and are expected to be estimated within 15% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.

Water Resources Research↗

USGS2023

Satellite remote sensing of river discharge: A framework for assessing the accuracy of discharge estimates made from satellite remote sensing observations

This research presents an evaluation of the accuracy and uncertainty of estimates of river discharge made using satellite observed data sources as input to a modified form of Manning’s equation. Conventional U.S. Geological Survey (USGS) streamflow gaging station data and in-situ measurements of width, depth, height, slope, discharge, and velocity from 30 USGS gage sites were used as ground-truth to assess accuracy. This study explores accuracy in relation to the amount of ground truth information available, the number of calibration points available, and the accuracy of the input data. This research indicates that remotely sensed discharge estimates associated with the modified Manning equation may be expected to have an uncertainty in range of 10% overall given a sufficient number of calibration points. The uncertainty associated with the modified Manning algorithm increased markedly for depths <3 meters (m) and for discharges <1000 cubic meters per second (m 3 / s) for many rivers after calibration. Rivers that exhibit (1) a wide range of flow conditions, (2) a significant number of dams in the watershed and along the channel, and (3) a high baseflow index are more likely to have relatively large errors overall and particularly at the low end of the streamflow range. Uncertainty in remotely sensed measurements of water-surface elevation (WSE) and width in the expected range (WSE, + / − 10 cm; Width, + / − 15 m) introduces uncertainty in the discharge estimates on the order of 10% and is greatest at the low end of discharge as rivers get shallower and narrower. As WSE and width measurement uncertainty increases, discharge uncertainty increases accordingly. In general, the observation errors are greater than the errors associated with the algorithm for a well-calibrated model (e.g., 20 calibration points).

Journal of Applied Remote Sensing↗

USGS2021

Simulating the effects of climate-related changes to air temperature and precipitation on streamflow and water temperature in the Meduxnekeag River watershed, Maine

Responsible stewardship of native fish populations and riparian plants in the Meduxnekeag River watershed in northeastern Maine is a high priority for the Houlton Band of Maliseet Indians. Understanding the potential changes in hydrology and water temperature as a result of climate change is important to this priority for evaluating future habitat conditions in the watershed. This report, prepared in cooperation with the Houlton Band of Maliseet Indians, documents and presents the results of a model using the Precipitation-Runoff Modeling System (PRMS), a hydrologic model designed to provide streamflow and water temperature simulations under predicted changes in precipitation and air temperature during the next century. To estimate streamflows and water temperature in the Meduxnekeag River watershed, a PRMS model was developed and calibrated. By using the calibrated PRMS model, simulations were made for projected scenarios of 0, 5, 10, and 15 percent increases in precipitation and for increases in air temperature of 0.0, 3.6, 7.0, and 10.4 degrees Fahrenheit (°F). The increases in precipitation and temperature were applied to all the daily input values uniformly. These scenarios were based upon the results from 30 climate change models summarized in the National Climate Change Viewer. Streamflows and water temperatures modeled for different climate scenarios were compared with streamflows and water temperatures modeled with unadjusted climate inputs. Overall, streamflow increased with increasing precipitation and decreased with increasing air temperature. Water temperature increased with increasing air temperature. At the outlet of the studied Meduxnekeag River watershed, with both a 15 percent increase in precipitation and a 10.4 °F increase in air temperature, the mean annual streamflow increased by 17 percent from 489 cubic feet per second (ft 3 /s) to 572 ft 3 /s, and the mean annual maximum streamflow decreased by 8.3 percent from 3,870 ft 3 /s to 3,550 ft 3 /s. At the same location and under the same scenario, the mean annual water temperature increased by 17.5 percent from 47.4 °F to 55.7 °F. Significant changes in mean monthly streamflows were found with increasing air temperature. The PRMS model results showed that when air temperature was increased, there was an increase in mean monthly streamflow during the winter months and a decrease in mean monthly streamflow during the spring months. In addition, with a 10.4 °F increase in the air temperature, the month with the greatest monthly streamflow changed from April to December. In addition, the PRMS model estimated that the mean annual maximum snowpack in snow water equivalent for the watershed would decrease from 7.67 inches to 1.26 inches, and the mean annual date of the maximum snowpack would change from March 21 to January 28 with a 15 percent increase in precipitation and a 10.4 °F increase in air temperature.

Maine↗

USGS2021

Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates

The Surface Water and Ocean Topography (SWOT) satellite mission will measure river width, water surface elevation, and slope for rivers wider than 50-100 m. SWOT observations will enable estimation of river discharge by using simple flow laws such as the Manning-Strickler equation, complementing in-situ streamgages. Several discharge inversion algorithms designed to compute unobserved flow law parameters ( e.g. friction coefficient, bathymetry) have been proposed, but to date, a systematic assessment of factors controlling algorithm performance has not been conducted. Here, we assess the performance of the five algorithms that are expected to be used in the construction of the SWOT product. To perform this assessment, we used synthetic SWOT observations created with hydraulic model output corrupted with SWOT-like error. Prior information provided to the algorithms was purposefully limited to an estimate of mean annual flow (MAF), designed to produce a “worst case” benchmark. Prior MAF error was an important control on algorithm performance, but discharge estimates produced by the algorithms are less biased than the MAF; thus, the discharge algorithms improve on the prior. We show for the first time that accuracy and frequency of remote sensing observations are less important than prior bias, hydraulic variability among reaches, and flow law accuracy in governing discharge algorithm performance. The discharge errors and error sensitivities reported herein are a bounding benchmark, representing worst possible expected errors and error sensitivities. This study lays the groundwork to develop predictive power of algorithm performance, and thus map the global distribution of worst-case SWOT discharge accuracy.

Water Resources Research↗

USGS2020

QCam: sUAS-based doppler radar for measuring river discharge

The U.S. Geological Survey is actively investigating remote sensing of surface velocity and river discharge (discharge) from satellite-, high altitude-, small, unmanned aircraft systems- (sUAS or drone), and permanent (fixed) deployments. This initiative is important in ungaged basins and river reaches that lack the infrastructure to deploy conventional streamgaging equipment. By coupling alternative discharge algorithms with sensors capable of measuring surface velocity, streamgage networks can be established in regions where data collection was previously impractical or impossible. To differentiate from satellite or high-altitude platforms, near-field remote sensing is conducted from sUAS or fixed platforms. QCam is a Doppler (velocity) radar mounted and integrated on a 3DR © Solo sUAS. It measures the along-track surface velocity by spot dwelling in a river cross section at a vertical where the maximum surface velocity is recorded. The surface velocity is translated to a mean-channel (mean) velocity using the probability concept (PC), and discharge is computed using the PC-derived mean velocity and cross-sectional area. Factors including surface-scatterer quality, flight altitude, propwash, wind drift, and sample duration may affect the radar-returns and the subsequent computation of mean velocity and river discharge. To evaluate the extensibility of the method, five science flights were conducted on four rivers of varying size and dynamics and included the Arkansas River, Colorado (CO), USA (two events); Salcha River near Salchaket, Alaska (AK), USA; South Platte River, CO, USA; and the Tanana River, AK, USA. QCam surface velocities and river discharges were compared to conventional streamgaging methods, which represented truth. QCam surface velocities for the Arkansas River, Salcha River, South Platte River, and Tanana River were 1.02 meters per second (m/s) and 1.43 m/s; 1.58 m/s; 0.90 m/s; and 2.17 m/s, respectively. QCam discharges (and percent differences) were 9.48 (0.3%) and 20.3 cubic meters per second (m 3 /s) (2.5%); 62.1 m 3 /s (−10.4%); 3.42 m 3 /s (7.3%), and 1579 m 3 /s (−18.8%). QCam results compare favorably with conventional streamgaging and are a viable near-field remote sensing technology that can be operationalized to deliver real-time surface velocity, mean velocity, and river discharge, if cross-sectional area is available.

Remote Sensing↗

USGS2020

Fundamental hydraulics of cross sections in natural rivers: Preliminary analysis of a large data set of acoustic doppler flow measurements

We have assembled a comprehensive and publicly accessible U.S. Geological Survey (USGS) streamflow measurement data set, called HYDRoSWOT, from a USGS National Water Information System archive of acoustic Doppler current profiler river discharge measurements collected from a wide range of rivers throughout the United States. The data set provides a wealth of information on the range of hydraulic characteristics of river cross sections in the United States. Preliminary exploration of the data set, filtered for quality control, indicates that rivers tend toward consistent and predictable forms as discharge increases. The ratio of maximum-to-mean depth is highly predictable and is remarkably consistent across all river sizes and discharges. Distributions of hydraulic characteristics provide a large-scale perspective on the general hydraulic characteristics of rivers. The data set affords the opportunity to analyze hydraulic relations for individual rivers as a function of stage, geomorphic setting, and energy environments and, combined with additional information contained in this data set, might yield predictive relations that could help constrain and parameterize river hydraulic models.

Water Resource Research↗

USGS2018

Simulated hydrologic response to climate change during the 21st century in New Hampshire

The U.S. Geological Survey, in cooperation with the New Hampshire Department of Environmental Services and the Department of Health and Human Services, has developed a hydrologic model to assess the effects of short- and long-term climate change on hydrology in New Hampshire. This report documents the model and datasets developed by using the model to predict how climate change will affect the hydrologic cycle and provide data that can be used by State and local agencies to identify locations that are vulnerable to the effects of climate change in areas across New Hampshire. Future hydrologic projections were developed from the output of five general circulation models for two future climate scenarios. The scenarios are based on projected future greenhouse gas emissions and estimates of land-use and land-cover change within a projected global economic framework. An evaluation of the possible effect of projected future temperature on modeling of evapotranspiration is summarized to address concerns regarding the implications of the future climate on model parameters that are based on climate variables. The results of the model simulations are hydrologic projections indicating increasing streamflow across the State with large increases in streamflow during winter and early spring and general decreases during late spring and summer. Wide spatial variability in changes to groundwater recharge is projected, with general decreases in the Connecticut River Valley and at high elevations in the northern part of the State and general increases in coastal and lowland areas of the State. In general, total winter snowfall is projected to decrease across the State, but there is a possibility of increasing snow in some locations, particularly during November, February, and March. The simulated future changes in recharge and snowfall vary by watershed across the State. This means that each area of the State could experience very different changes, depending on topography or other factors. Therefore, planning for infrastructure and public safety needs to be flexible in order to address the range of possible outcomes indicated by the various model simulations. The absolute magnitude and timing of the daily streamflows, especially the larger floods, are not considered to be reliably simulated compared to changes in frequency and duration of daily streamflows and changes in accumulated monthly and seasonal streamflow volumes. Simulated current and future streamflow, groundwater recharge, and snowfall datasets include simulated data derived from the five general circulation models used in this study for a current reference time period and two future time periods. Average monthly streamflow time series datasets are provided for 27 streamgages in New Hampshire. Fourteen of the 27 streamgages associated with daily streamflow time series showed a good calibration. Average monthly groundwater recharge and snowfall time series for the same reference time period and two future time periods are also provided for each of the 467 hydrologic response units that compose the model.

New Hampshire↗

USGS2018

Satellite remote sensing estimation of river discharge: Application to the Yukon River Alaska

A methodology based on general hydraulic relations for rivers has been developed to estimate the discharge (flow rate) of rivers using satellite remote sensing observations. The estimates of discharge, flow depth, and flow velocity are derived from remotely observed water surface area, water surface slope, and water surface height, and demonstrated for two reaches of the Yukon River in Alaska, at Eagle (reach length 34.7 km) and near Stevens Village (reach length 38.3 km). The method is based on fundamental equations of hydraulic flow resistance in rivers, including the Manning equation and the Prandtl-von Karman universal velocity distribution equation. The method employs some new hydraulic relations to help define flow resistance and height of the zero flow boundary in the channel. Estimates are made both with and without calibration. The water surface area of the river reach is measured by using a provisional version of the U.S. Geological Survey (USGS) Landsat based product named Dynamic Surface Water Extent (DSWE). The water surface height and slope measurements require a self-consistent datum, and are derived from observations from the Jason-2 satellite altimeter mission. At both reach locations, the Jason-2 radar altimeter non-winter heights consistently tracked the stage recorded at USGS streamgages with a standard deviation of differences (error) during the non-winter periods of less than 7%. Part of the error may be due to differences in the gage and altimeter crossing locations with respect to the range of stage change and the response to changes in discharge at the upstream and downstream locations. For the non-winter periods, the radar derived slope estimates (mean = 0.0003) were constant over the mission lifetime, and in agreement with previously measured USGS water surface slopes and slopes determined from USGS topographic maps. The accuracy of the mean of the uncalibrated daily estimates of discharge varied between reaches, ranging from 13% near Stevens Village (N = 90) to −21% at Eagle (N = 246) based on the absolute error, and 5% to −6% based on the error of the log of the estimates. Calibrating to the mean of USGS daily discharge estimates from the streamflow rating for the same period of record at each streamgage resulted in mean absolute errors ranging from 1% to 2%, and log errors ranging from 1% or less. The error pattern of the estimates shows that without calibration, even though the mean is well simulated, the high and low end values over the range of estimates may have significant bias.

Alaska↗

USGS2017

Engaging the user community for advancing societal applications of the Surface Water Ocean Topography mission

Scheduled for launch in 2021, the Surface Water and Ocean Topography (SWOT) mission will be a truly unique mission that will provide high-temporal-frequency maps of surface water extents and elevation variations of global water bodies (lakes/reservoirs, rivers, estuaries, oceans, and sea ice) at higher spatial resolution than is available with current technologies (Biancamaria et al. 2016; Alsdorf et al. 2007). The primary instrument on SWOT is based on a Ka-band radar interferometer (KaRIN), which uses radar interferometery technology. The satellite will fly two radar antennas at either end of a 10-m (33 ft) mast, allowing it to measure the elevation of the surface along a 120-km (75 mi)-wide swath below. The availability of high-frequency and high-resolution maps of elevations and extents for surface water bodies and oceans will present unique opportunities to address numerous societally relevant challenges around the globe (Srinivasan et al. 2015). These opportunities may include such diverse and far-ranging applications as fisheries management, flood inundation mapping/risk mitigation/forecasting, wildlife conservation, global data assimilation for improving forecast of ocean tides and weather, reservoir management, climate change impacts and adaptation, and river discharge estimation, among others. Although SWOT is a research mission and not scheduled for launch for another 4 years, there is a need to build engagement within the application community now and to explore how best to advance the societal relevance and benefits of the SWOT mission from concept to reality. The SWOT Applications Working Group organized a workshop on 5–6 April 2017 at the U.S. Geological Survey (USGS) headquarters in Reston, Virginia. The goal of the workshop was to understand and communicate how the applications community can use SWOT data to address problems of profound societal relevance.

Bulletin of the American Meteorological Society↗

USGS2016

An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope

The Surface Water and Ocean Topography (SWOT) satellite mission planned for launch in 2020 will map river elevations and inundated area globally for rivers >100 m wide. In advance of this launch, we here evaluated the possibility of estimating discharge in ungauged rivers using synthetic, daily ‘‘remote sensing’’ measurements derived from hydraulic models corrupted with minimal observational errors. Five discharge algorithms were evaluated, as well as the median of the five, for 19 rivers spanning a range of hydraulic and geomorphic conditions. Reliance upon a priori information, and thus applicability to truly ungauged reaches, varied among algorithms: one algorithm employed only global limits on velocity and depth, while the other algorithms relied on globally available prior estimates of discharge. We found at least one algorithm able to estimate instantaneous discharge to within 35% relative root-mean-squared error (RRMSE) on 14/16 nonbraided rivers despite out-of-bank flows, multichannel planforms, and backwater effects. Moreover, we found RRMSE was often dominated by bias; the median standard deviation of relative residuals across the 16 nonbraided rivers was only 12.5%. SWOT discharge algorithm progress is therefore encouraging, yet future efforts should consider incorporating ancillary data or multialgorithm synergy to improve results

Water Resources Research↗

USGS2016

Benchmarking wide swath altimetry-based river discharge estimation algorithms for the Ganges river system

The objective of this study is to compare the effectiveness of three algorithms that estimate discharge from remotely sensed observables (river width, water surface height, and water surface slope) in anticipation of the forthcoming NASA/CNES Surface Water and Ocean Topography (SWOT) mission. SWOT promises to provide these measurements simultaneously, and the river discharge algorithms included here are designed to work with these data. Two algorithms were built around Manning's equation, the Metropolis Manning (MetroMan) method, and the Mean Flow and Geomorphology (MFG) method, and one approach uses hydraulic geometry to estimate discharge, the at-many-stations hydraulic geometry (AMHG) method. A well-calibrated and ground-truthed hydrodynamic model of the Ganges river system (HEC-RAS) was used as reference for three rivers from the Ganges River Delta: the main stem of Ganges, the Arial-Khan, and the Mohananda Rivers. The high seasonal variability of these rivers due to the Monsoon presented a unique opportunity to thoroughly assess the discharge algorithms in light of typical monsoon regime rivers. It was found that the MFG method provides the most accurate discharge estimations in most cases, with an average relative root-mean-squared error (RRMSE) across all three reaches of 35.5%. It is followed closely by the Metropolis Manning algorithm, with an average RRMSE of 51.5%. However, the MFG method's reliance on knowledge of prior river discharge limits its application on ungauged rivers. In terms of input data requirement at ungauged regions with no prior records, the Metropolis Manning algorithm provides a more practical alternative over a region that is lacking in historical observations as the algorithm requires less ancillary data. The AMHG algorithm, while requiring the least prior river data, provided the least accurate discharge measurements with an average wet and dry season RRMSE of 79.8% and 119.1%, respectively, across all rivers studied. This poor performance is directly traced to poor estimation of AMHG via a remotely sensed proxy, and results improve commensurate with MFG and MetroMan when prior AMHG information is given to the method. Therefore, we cannot recommend use of AMHG without inclusion of this prior information, at least for the studied rivers. The dry season discharge (within-bank flow) was captured well by all methods, while the wet season (floodplain flow) appeared more challenging. The picture that emerges from this study is that a multialgorithm approach may be appropriate during flood inundation periods in Ganges Delta.

Ganges River Delta↗

USGS2015

Simulating hydrologic response to climate change scenarios in four selected watersheds of New Hampshire

The State of New Hampshire has initiated a coordinated effort to proactively prepare for the effects of climate change on the natural and human resources of New Hampshire. An important aspect of this effort is to develop a vulnerability assessment of hydrologic response to climate change. The U.S. Geological Survey, in cooperation with the New Hampshire Department of Health and Human Services, is developing tools to predict how projected changes in temperature and precipitation will affect change in the hydrology of watersheds in the State. This study is a test case to assemble the information and create the tools to assess the hydrologic vulnerabilities in four specific watersheds. The study uses output from general circulation models to drive hydrologic simulations of streamflow, groundwater base flow (hereafter referred to as base flow), and snowfall in four representative watersheds in New Hampshire during the 21st century, including the watersheds of the Ashuelot, Oyster, Pemigewasset, and Souhegan Rivers. Simulations show that on average, relative to current conditions, streamflow is likely to increase and base flow is likely to decrease, although this change is highly variable by geographic location and season. Streamflow variability will likely increase, with more high streamflows and more low streamflows. The largest increases in streamflow are in the winter, with small decreases in summer. Change in base flow varies across the State with the largest change in the northern Pemigewasset River watershed. Changes in snowfall are consistently decreasing for all watersheds on average, with the largest change also in the Pemigewasset. However, monthly snowfall totals during any given winter could be higher in the future than expected under current conditions. Increasing frequency of floods (the largest seven floods expected to occur in 20 years) could be more significant than the size of the floods, except in the northern high altitude watersheds. In other words, the projections indicate a pattern of multiple floods that might not breach the riverbanks, yet the increased frequency could put additional strain on the existing river banks, infrastructure, and nearby human settlements. There is also likely to be an increase in high flows during the winter and spring months, which could result in more uncertainty in planning for the design, operation, and maintenance of infrastructure, including roads and utilities. Similarly, it is expected that, on average, there will be less base flow available and a wider range of seasonal fluctuation in base flow than experienced historically. These issues could necessitate more attention to planning and management of the resource. Based on past experience, the most important effects of climate change could be less certain planning options and a greater need for planning that accounts for the effects of larger streamflows than are currently available. The effects of hydrologic change on human health and well-being could be most readily apparent with respect to changes in streamflow and the subsequent increase in the frequency of minor flooding and the frequency of summer and fall low streamflows. These changes could require the development of plans to adapt, protect, and upgrade infrastructure, such as bridges, culverts, roads, and other structures. The precipitation runoff modeling shows that rivers and watersheds in New Hampshire will likely change in response to climate change, and that this response varies with season and latitude. Although four representative areas were simulated in this study, additional models could be used to predict the response over the entire State.

New Hampshire↗

USGS2014

Assessment of the spatial extent and height of flooding in Lake Champlain during May 2011, using satellite remote sensing and ground-based information

Landsat 5 and moderate resolution imaging spectro-radiometer satellite imagery were used to map the area of inundation of Lake Champlain, which forms part of the border between New York and Vermont, during May 2011. During this month, the lake’s water levels were record high values not observed in the previous 150 years. Lake inundation area determined from the satellite imagery is correlated with lake stage measured at three U.S. Geological Survey lake level gages to provide estimates of lake area at different lake levels (stage/area rating) and also compared with the levels of the high-water marks (HWMs) located on the Vermont side of the lake. The rating developed from the imagery shows a somewhat different relation than a similar stage/area rating developed from a medium-resolution digital elevation model (DEM) of the region. According to the rating derived from the imagery, the lake surface area during the peak lake level increased by about 17 percent above the average or “normal” lake level. By using a comparable rating developed from the DEM, the increase above average is estimated to be about 12 percent. The northern part of the lake (north of Burlington) showed the largest amount of flooding. Based on intersecting the inundation maps with the medium-resolution DEM, lake levels were not uniform around the lake. This is also evident from the lake level gage measurements and HWMs. The gage data indicate differences up to 0.5 feet between the northern and southern end of the lake. Additionally, the gage data show day-to-day and intradaily variation of the same range (0.5 foot). The high-water mark observations show differences up to 2 feet around the lake, with the highest level generally along the south- and west-facing shorelines. The data suggest that during most of May 2011, water levels were slightly higher and less variable in the northern part of the lake. These phenomena may be caused by wind effects as well as proximity to major river inputs to the lake. The inundation areas generated from the imagery generally coincide with flood mapping as estimated by the Federal Emergency Management Agency (FEMA) and shown on its digital flood insurance rate maps. Where areas in the flood inundation map derived from the imagery and the FEMA estimated flooded areas differ substantially, this difference may be due to differences between the flood magnitude at the time of the image and the assumed flood condition used for the FEMA modeling and mapping, wind/storage effects not accounted for by the FEMA modeling, and the resolution of the image compared to the DEM used in the FEMA mapping.

Lake Champlain↗

USGS2013

Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960–2000). We define and map extreme precipitation hazard , exposure , affected populations, vulnerability and risk , and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.

Philosophical Transactions of the Royal Society A:↗

USGS2013

A one-dimensional diffusion analogy model for estimation of tide heights in selected tidal marshes in Connecticut

A one-dimensional diffusion analogy model for estimating tide heights in coastal marshes was developed and calibrated by using data from previous tidal-marsh studies. The method is simpler to use than other one- and two-dimensional hydrodynamic models because it does not require marsh depth and tidal prism information; however, the one-dimensional diffusion analogy model cannot be used to estimate tide heights, flow velocities, and tide arrival times for tide conditions other than the highest tide for which it is calibrated. Limited validation of the method indicates that it has an accuracy within 0.3 feet. The method can be applied with limited calibration information that is based entirely on remote sensing or geographic information system data layers. The method can be used to estimate high-tide heights in tidal wetlands drained by tide gates where tide levels cannot be observed directly by opening the gates without risk of flooding properties and structures. A geographic information system application of the method is demonstrated for Sybil Creek marsh in Branford, Connecticut. The tidal flux into this marsh is controlled by two tide gates that prevent full tidal inundation of the marsh. The method application shows reasonable tide heights for the gates-closed condition (the normal condition) and the one-gate-open condition on the basis of comparison with observed heights. The condition with all tide gates open (two gates) was simulated with the model; results indicate where several structures would be flooded if the gates were removed as part of restoration efforts or if the tide gates were to fail.

Connecticut↗