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At least 523 records · Page 29Linked to original sources
USGS2020

Short-term forecasts of insect phenology inform pest management

Insect pests cost billions of dollars per year globally, negatively impacting food crops and infrastructure, and contributing to the spread of disease. Timely information regarding developmental stages of pests can facilitate early detection and control, increasing efficiency and effectiveness. In 2018, the U.S. National Phenology Network (USA-NPN) released a suite of ‘Pheno Forecast’ map products relevant to science and management. The Pheno Forecasts include real-time maps and short-term forecasts of insect pest activity at management-relevant spatial and temporal resolutions and are based on accumulated temperature thresholds associated with critical life-cycle stages of economically important pests. Pheno Forecasts indicate, for a specified day, the status of the insect’s target life-cycle stage in real time across the contiguous United States. The maps are available for 12 pest species including the invasive emerald ash borer ( Agrilus planipennis Fairmaire [Coleoptera: Buprestidae]), hemlock woolly adelgid ( Adelges tsugae Annand), and gypsy moth ( Lymantria dispar Linnaeus [Lepidoptera: Erebidae]). Preliminary validation based on in-situ observations for hemlock woolly adelgid egg and nymph stages in 2018 indicated the maps to be ≥93% accurate depending on phenophase. Since their release in early 2018, these maps have been adopted by tree care specialists and foresters across the United States. Using a consultative mode of engagement, USA-NPN staff have continuously sought input and critique of the maps and delivery from end users. Based on feedback received, maps have been expanded and modified to include additional species, improved descriptions of the phenophase event of interest, and e-mail-based notifications to support management decisions.

Annals of the Entomological Society of America↗
USGS2019

Shorebird subsistence harvest and indigenous knowledge in Alaska: Informing harvest assessment and management, and engaging users in shorebird conservation

Limited data on harvest and population parameters are major impediments to assess shorebird harvest sustainability. Because of sharp declines in shorebird populations, timely conservation efforts require approaches that account for uncertainty in harvest sustainability. We combined harvest assessment and ethnographic research to better understand shorebird conservation concerns related to subsistence harvest in Alaska and to support culturally sensible conservation actions. Our objectives were to (1) estimate the Alaska-wide shorebird subsistence harvest and (2) document shorebird indigenous knowledge on the Yukon-Kuskokwim Delta. Harvest estimates were based on surveys conducted in 1990–2015 (n = 775 community-years). Key respondent interviews conducted in 2017 (n = 72) documented shorebird ethnotaxonomy and ethnography. The Alaska-wide shorebird harvest was 2,783 birds per year. Harvest of godwits was relatively low (1,115 birds per year) and likely included mostly Bar-tailed Godwits Limosa lapponica baueri, but this population has a low harvest potential. The egg harvest was 4,676 eggs per year, mostly small shorebird eggs. We documented 24 Yup’ik shorebird names and 10 main ethnotaxonomic categories. Children learning harvesting skills focused on small birds and adults also occasionally harvested shorebirds, but shorebirds were not primary food or cultural resources. Older generations associated shorebirds with a time when people were in closer contact with nature and their cultural roots. Shorebirds connected people with the environment as well as with Yup’ik traditions and language. Our results can inform improvements to harvest assessment and management, as well as outreach and communication efforts to engage subsistence users in shorebird conservation.

Alaska↗
USGS2014

Evaluating the predictive performance of empirical estimators of natural mortality rate using information on over 200 fish species

Many methods have been developed in the last 70 years to predict the natural mortality rate, M , of a stock based on empirical evidence from comparative life history studies. These indirect or empirical methods are used in most stock assessments to (i) obtain estimates of M in the absence of direct information, (ii) check on the reasonableness of a direct estimate of M , (iii) examine the range of plausible M estimates for the stock under consideration, and (iv) define prior distributions for Bayesian analyses. The two most cited empirical methods have appeared in the literature over 2500 times to date. Despite the importance of these methods, there is no consensus in the literature on how well these methods work in terms of prediction error or how their performance may be ranked. We evaluate estimators based on various combinations of maximum age ( t max ), growth parameters, and water temperature by seeing how well they reproduce >200 independent, direct estimates of M . We use tenfold cross-validation to estimate the prediction error of the estimators and to rank their performance. With updated and carefully reviewed data, we conclude that a t max -based estimator performs the best among all estimators evaluated. The t max -based estimators in turn perform better than the Alverson–Carney method based on t max and the von Bertalanffy K coefficient, Pauly’s method based on growth parameters and water temperature and methods based just on K . It is possible to combine two independent methods by computing a weighted mean but the improvement over the t max -based methods is slight. Based on cross-validation prediction error, model residual patterns, model parsimony, and biological considerations, we recommend the use of a t max -based estimator ( M = 4.899 t max − 0.916 "> M = 4.899 t − 0.916 max M=4.899tmax−0.916 , prediction error = 0.32) when possible and a growth-based method ( M = 4.118 K 0.73 L ∞ − 0.33 "> M = 4.118 K 0.73 L − 0.33 ∞ M=4.118K0.73L∞−0.33 , prediction error = 0.6, length in cm) otherwise.

ICES Journal of Marine Science↗
USGS2025

Evaluating detection of temporal trends in long-term freshwater fisheries data to inform future monitoring efforts

Objective Florida’s Freshwater Fisheries Long-Term Monitoring Program was implemented in 2006 to track changes in freshwater fish populations and communities. As part of an evaluation of the program, this study used a simulation framework to assess trend detection for fish abundance and biomass indices and how sampling intensity (number of samples per year) and frequency (number of years) can influence detection of these trends. Methods Using count and weight data from fall electrofishing samples collected between 2006 and 2021 from 21 lakes, trends were simulated for annual mean count and weight over a 10-year period that ranged from −70% to +200%. In all, simulations were performed for seven game fish species and three management-relevant groups (large nongame, nonnative, and prey species). For sampling intensity, data were simulated with a range of sample sizes, from 10 to 40 electrofishing transects or the maximum number available for a given lake. For sampling frequency, data were simulated for different sampling schedules that included sampling 1 year followed by 1- or 2-year breaks (4–5 years of sampling in a 10-year period), sampling two consecutive years followed by 1- or 2-year breaks (6–7 years of sampling in a 10-year period), and sampling the first 5 years only. Results Simulations based on weight and count data yielded similar results, but the effect of sampling frequency and sampling schedule varied by species, management group, and lake. Trend detection was lower and more variable when mean counts and weights of fish in electrofishing samples were low. Overall, at least a 60% increase or 40% decrease over a 10-year period was typically needed for trends in mean weight and count to be detected at least 80% of the time in at least half of the lakes. Increasing sampling intensity did not substantially improve trend detection for lower-magnitude changes, but reducing sample intensity to a minimum of 10 electrofishing transects per year would have a large negative effect on trend detection in almost all lakes. Detection of trends improved as the number of years sampled increased, but ideally, sampling should be spaced throughout the entire 10-year period to capture the full magnitude of change. Sampling every year generally resulted in better trend detection and for many species and groups was the only sampling schedule that resulted in all study lakes achieving the 80% target detection level. Of the alternative schedules considered, those involving 2 years of consecutive sampling outperformed those with only 1 year of sampling followed by a 1- or 2-year break. Conclusions Relatively large changes in mean count and weight were required to detect trends over a 10-year period, but there was no clear advantage of using count or weight data for monitoring purposes. Further, study results support the current sampling intensity, but trend detection is optimized at higher mean catch and weight values. Although sampling every year is ideal, an alternative schedule involving sampling two consecutive years with 1- or 2-year breaks could be considered in certain situations. These results will be important for informing future decisions regarding Florida’s Freshwater Fisheries Long-Term Monitoring Program and other monitoring initiatives.

North American Journal of Fisheries Management.↗
USGS2025

Satellite imagery can predict bird species occupancy and inform multispecies management in pine savannas

Multispecies management can contribute to meeting growing challenges of preserving biodiversity, yet current game and threatened species management often focuses on individual species. Satellite imagery available at high spatial and temporal resolution provides a potential tool to overcome the challenge posed by multispecies management of linking patterns of habitat use among species. We sought to determine whether satellite imagery could be used to describe patterns of species occupancy and inform multispecies management in pine savannas in Georgia, USA. We conducted point-count surveys at 7 sites in 2022 for 3 bird species: Colinus virginianus (Northern Bobwhite), Dryobates borealis (Red-cockaded Woodpecker), and Peucaea aestivalis (Bachman’s Sparrow). We built single-season occupancy models comparing a set of models using covariates collected from field vegetation surveys and another set using covariates extracted from Sentinel-2 satellite imagery. We then used a multi-objective optimization algorithm to identify quasi-optimal management solutions (i.e., sets of covariate values from top satellite imagery metric models). We found that models created using satellite imagery performed well at predicting occupancy of all 3 species as measured by the area under the receiver operating characteristic curve (AUC > 0.8) and had higher AUC scores than field-derived habitat covariate-based models. We found combinations of metrics that could result in high rates of predicted probability of occupancy for all species (within 86% of highest possible occupancy probability), but these combinations did not exist at any of the sites. Our results demonstrate that (1) satellite imagery can allow users to build reliable occupancy models without intensive field-based vegetation surveys; and (2) C. virginianus , D. borealis, and P. aestivalis in pine savanna ecosystems could be simultaneously managed through more frequent burning, changes in canopy cover or by producing suitable heterogeneity of habitats after identifying an appropriate scale of management.

Georgia↗
USGS2025

Seasonal movements and demographics of the endangered White River Spinedace to inform restoration and translocation

Objective Translocation is a tool being explored to restart extirpated populations or facilitate new populations of endangered spring-­dependent fish populations. Our objective was to provide information on habitat requirements for endangered White River Spinedace Lepidomeda albivallis during all seasons of the year and the population demographics that are necessary to plan conservation translocations of this species Methods We tagged and released White River Spinedace with passive integrated transponders during four twice-a-year events. Fish were subsequently recaptured or detected on six passive antennas placed throughout the Flag Springs Complex, Nevada. We evaluated movement data to understand seasonal habitat use patterns, used a Barker model to estimate monthly survival rates, adjusted counts to account for capture probability and estimate abundance, and applied reverse-time mark–recapture models to estimate recruitment to 70 mm total length. Results White River Spinedace were more active but used similar habitats during spawning seasons than during nonspawning seasons. Median life expectancy was about 5 months after tagging, and only 1% of adult White River Spinedace survived 3–4 years posttagging. The estimated population size in the Flag Springs Complex during our sampling period (November 2020 to June 2022) was fewer than a thousand White River Spinedace, and this estimate has been steady or slightly increasing. Conclusions Complex spring habitats with water temperatures ranging about 13°C to 21°C that are free from piscivorous fish are appropriate for White River Spinedace. The White River Spinedace population at Flag Springs is small but stable or increasing in size.

Transactions of the American Fisheries Society↗
USGS2021

Waterfowl use of wetland habitats informs wetland restoration designs for multi‐species benefits

Extensive global estuarine wetland losses have prompted intensive focus on restoration of these habitats. In California, substantial tracts of freshwater, brackish and tidal wetlands have been lost. Given the anthropogenic footprint of development and urbanization in this region, wetland restoration must rely on conversion of existing habitat types rather than adding new wetlands. These restorations can cause conflicts among stakeholders and species that win or lose depending on identified restoration priorities. Suisun Marsh on the San Francisco Bay Estuary is the largest brackish marsh on the U.S. Pacific coast. To understand how conversion of brackish managed wetlands to tidal marsh would impact waterfowl populations and whether future tidal marsh restorations could provide suitable habitat for dabbling ducks, we examined waterfowl wetland use with a robust GPS‐GSM tracking dataset (442,017 locations) from six dabbling duck species (N=315). Managed wetlands, which comprise 47% of Suisun Marsh, were consistently and strongly selected by waterfowl over tidal marshes, with use ~98% across seasons and species. However, while use of tidal marsh (only 14% of Suisun Marsh) was generally <2%, almost half our ducks (~44%) spent some time in this habitat and exhibited strong utilization of pond‐like features. Ponds only comprise ~10% of this habitat but attracted 44% use (~4.5 times greater than availability). Synthesis and applications : Managed wetlands were vital to dabbling ducks, but losses from conversion of these habitats may be partially mitigated by incorporating pond features that are more attractive to waterfowl, and likely to offer multi‐species benefits, into tidal marsh restoration designs. While waterfowl are presently a common taxon, previously seen calamitous population declines can be avoided through informed ecosystem‐based management that promotes species richness, biodiversity and helps “keep common species common”.

California↗
USGS2025

Site-level connectivity identified from multiple sources of movement data to inform conservation of a migratory bird

Migratory birds depend on a suite of sites across their annual cycles, making them vulnerable to a wide variety of anthropogenic pressures. Current area-based conservation measures have been found inadequate to safeguard migratory birds, in part due to a lack of consideration for the connectivity between sites mediated by the movements of individuals. To address this issue, we develop a network analysis integrating different types of individual movement data for a migratory shorebird, the Black-tailed Godwit ( Limosa limosa ), across the East Atlantic Flyway. Leveraging metal-ring recoveries, colour-ring re-sightings and satellite tracking from over 10,000 individual godwits, we quantify variation in connectivity between sites across the migratory range, using two weighted metrics to address sampling biases. Colour-ring re-sightings provided the largest number of sites (70%) and links (60% and 43% per season) overall, followed by tracking data (50% of sites, 49% and 63% of links per season) and ring recoveries (25% of sites, <1% of links per season), with clear regional variation in datatype contributions. Sampling completeness of the network structure varied with longitude, with information particularly lacking in central and eastern countries of both Europe and Africa. We identified 49 sites playing a disproportionate role in the site network, each with direct connections to 48 (interquartile range 32–84) other sites, on average. Just 23 (47%) top sites are formally recognized for their international importance for Black-tailed Godwits, and 33 (67%) were robust to sampling incompleteness. Across all 1058 sites, 20% lacked protected area coverage, and per site, 44% (44% ± SD) of bird relocations fell within protected areas. Integrating multiple sources of data improved geographical coverage and completeness of the site network, allowing us to quantify the importance of sites in terms of connectivity across the flyway. Our results highlight shortcomings of existing area-based conservation measures and add value to ongoing efforts to identify important sites for migratory birds. Policy implications . The increasing availability of individual movement data provides valuable opportunities to reveal the inter-dependence of sites used by migratory species, which can help identify priority areas and facilitate flyway-scale management.

Journal of Applied Ecology↗
USGS2016

Integrating seasonal information on nutrients and benthic algal biomass into stream water quality monitoring

Benthic chlorophyll a (BChl a ) and environmental factors that influence algal biomass were measured monthly from February through October in 22 streams from three agricultural regions of the United States. At-site maximum BChl a ranged from 14 to 406 mg/m 2 and generally varied with dissolved inorganic nitrogen (DIN): 8 out of 9 sites with at-site median DIN >0.5 mg/L had maximum BChl a >100 mg/m 2 . BChl a accrued and persisted at levels within 50% of at-site maximum for only one to three months. No dominant seasonal pattern for algal biomass accrual was observed in any region. A linear model with DIN, water surface gradient, and velocity accounted for most of the cross-site variation in maximum chlorophyll a (adjusted R 2 = 0.7), but was no better than a single value of DIN = 0.5 mg/L for distinguishing between low and high-biomass sites. Studies of nutrient enrichment require multiple samples to estimate algal biomass with sufficient precision given the magnitude of temporal variability of algal biomass. An effective strategy for regional stream assessment of nutrient enrichment could be based on a relation between maximum BChl a and DIN based on repeat sampling at sites selected to represent a gradient in nutrients and application of the relation to a larger number of sites with synoptic nutrient information.

Journal of the American Water Resources Associatio↗
USGS2013

Integrating resource selection information with spatial capture--recapture

1. Understanding space usage and resource selection is a primary focus of many studies of animal populations. Usually, such studies are based on location data obtained from telemetry, and resource selection functions (RSFs) are used for inference. Another important focus of wildlife research is estimation and modeling population size and density. Recently developed spatial capture–recapture (SCR) models accomplish this objective using individual encounter history data with auxiliary spatial information on location of capture. SCR models include encounter probability functions that are intuitively related to RSFs, but to date, no one has extended SCR models to allow for explicit inference about space usage and resource selection. 2. In this paper we develop the first statistical framework for jointly modeling space usage, resource selection, and population density by integrating SCR data, such as from camera traps, mist-nets, or conventional catch traps, with resource selection data from telemetered individuals. We provide a framework for estimation based on marginal likelihood, wherein we estimate simultaneously the parameters of the SCR and RSF models. 3. Our method leads to increases in precision for estimating parameters of ordinary SCR models. Importantly, we also find that SCR models alone can estimate parameters of RSFs and, as such, SCR methods can be used as the sole source for studying space-usage; however, precision will be higher when telemetry data are available. 4. Finally, we find that SCR models using standard symmetric and stationary encounter probability models may not fully explain variation in encounter probability due to space usage, and therefore produce biased estimates of density when animal space usage is related to resource selection. Consequently, it is important that space usage be taken into consideration, if possible, in studies focused on estimating density using capture–recapture methods.

Methods in Ecology and Evolution↗
USGS2026

Constructed value of information with iterative scoring and parametric uncertainty to identify management-relevant research priorities for a declining raptor species

Constructed value of information (CVoI) is an expert elicitation decision-analytic tool used to prioritize sources of uncertainty based on their potential to improve decision outcomes if resolved. Despite increased application of CVoI, the robustness of CVoI prioritization of sources of uncertainty relative to differences in expert elicitation and scoring methods has not been evaluated. We engaged a group of species experts in a decision-analytic process to elicit uncertainties, framed as alternative hypotheses, about current population declines of the American kestrel ( Falco sparverius ) in the United States. Participants scored 13 hypotheses across 3 CVoI criteria, which are defined as constructed scales. Rather than experts selecting a single score per criterion, we used a likelihood point method to incorporate parametric uncertainty in the scoring process, in which experts were given 100 points to distribute across possible score categories within the criterion-specific constructed scale. Experts provided scores over 2 scoring rounds, with an opportunity to review and discuss initial scores between rounds. We used a Shannon entropy calculation to quantify how evenly participants allotted their points. We used simulation to evaluate the robustness of our prioritization results relative to a scoring method in which participants selected a single score category for each criterion. Participants often spread their points across 2 adjacent scores, reflecting parametric uncertainty. For one third of the hypothesis-scoring round combinations, the prioritization results differed in approximately 50% of simulations. The highest scoring hypotheses related to how the use of artificial versus natural nest cavities affects fecundity or survival, whether winter roosting sites are a limiting factor for population growth, and whether gamebird habitat management may benefit kestrel populations. Our CVoI prioritization framework can be used to develop collaborative research that is directly relevant to a management decision and is an advance in eliciting more representative expert beliefs.

Conservation Biology↗
USGS2025

Challenges and priorities for climate-informed invasive species management across multiple scales

In recent decades, substantial evidence has accumulated regarding the effects of climate change on the establishment, spread, and impact of invasive species. While the importance of incorporating climate change into invasive species management and policy is increasingly recognized, practitioner experiences and perspectives are often overlooked. Consequently, invasive species research may be misaligned with the needs of managers and the threats of climate change. Here, we compare survey responses from a boundary-spanning organization, the Regional Invasive Species and Climate Change (RISCC) Management Network, to identify common priorities and challenges in managing invasive species in a changing climate in the United States. Survey respondents reported that 22% of management and research time is dedicated to emerging invasive species threats. Common barriers to climate-informed invasive species management include limited time, funding, and personnel. Understanding how climate change may impact control strategies was consistently identified as a high priority for invasive species management, followed by identifying resilient ecosystems and range-shifting taxa. These results demonstrate the critical need for stronger researcher-practitioner networks and greater investment in research and policy topics that more closely align with management needs to address the interacting stressors of invasive species and climate change.

Conservation Science and Practice↗
USGS2025

A network of refugia: Whooping Crane drought response informs international habitat conservation goals

Whooping Cranes land in a palustrine-emergent wetland amid row crop agriculture near Atkinson, Nebraska, during spring migration in April of 2020 (photo by M. L. Forsberg). From 2023 to 2024, the U.S. and Canada updated conservation plans for the Whooping Crane through international workshops. These forthcoming documents will reflect shared goals for wetland conservation aimed at boosting the species' resilience to climate change and habitat loss, which were informed by applied research regarding drought impacts on migrating Whooping Cranes. The active protection and management of hydrologically diverse wetland complexes can create climate refugia that help ensure the integrity of Whooping Crane migration through the Central Flyway into the foreseeable future.

Great Plains↗
USGS2011

Exploring sensitivity of a multistate occupancy model to inform management decisions

1. Dynamic occupancy models are often used to investigate questions regarding the processes that influence patch occupancy and are prominent in the fields of population and community ecology and conservation biology. Recently, multistate occupancy models have been developed to investigate dynamic systems involving more than one occupied state, including reproductive states, relative abundance states and joint habitat‐occupancy states. Here we investigate the sensitivities of the equilibrium‐state distribution of multistate occupancy models to changes in transition rates. 2. We develop equilibrium occupancy expressions and their associated sensitivity metrics for dynamic multistate occupancy models. To illustrate our approach, we use two examples that represent common multistate occupancy systems. The first example involves a three‐state dynamic model involving occupied states with and without successful reproduction (California spotted owl Strix occidentalis occidentalis ), and the second involves a novel way of using a multistate occupancy approach to accommodate second‐order Markov processes (wood frog Lithobates sylvatica breeding and metamorphosis). 3. In many ways, multistate sensitivity metrics behave in similar ways as standard occupancy sensitivities. When equilibrium occupancy rates are low, sensitivity to parameters related to colonisation is high, while sensitivity to persistence parameters is greater when equilibrium occupancy rates are high. Sensitivities can also provide guidance for managers when estimates of transition probabilities are not available. 4. Synthesis and applications. Multistate models provide practitioners a flexible framework to define multiple, distinct occupied states and the ability to choose which state, or combination of states, is most relevant to questions and decisions about their own systems. In addition to standard multistate occupancy models, we provide an example of how a second‐order Markov process can be modified to fit a multistate framework. Assuming the system is near equilibrium, our sensitivity analyses illustrate how to investigate the sensitivity of the system‐specific equilibrium state(s) to changes in transition rates. Because management will typically act on these transition rates, sensitivity analyses can provide valuable information about the potential influence of different actions and when it may be prudent to shift the focus of management among the various transition rates.

Journal of Applied Ecology↗
USGS2007

Use of topological information in hydrograph estimation

Discharge hydrographs computed from the theory of linear flow through topologically random channel networks are compared to actual discharge hydrographs for basins in semiarid regions of central Wyoming. The basins drained by the channel networks range in size from 0.69 to 10.8 square miles. Topological information consisting of stream-network magnitude and link -length distribution parameters are used in calibrating celerity values that ensure that the peak discharge and excess rainfall volume of the resulting computed hydrographs match the peak discharge and excess-rainfall volume of the actual hydrographs. Results indicate that, for a given peak discharge and excess-rainfall volume in a basin, the sensitivity of the calibrated celerity values to excess-rainfall duration is small if the ratio of excess-rainfall volume to peak discharge is at least 1.75 times the excess-rainfall duration.

Journal of the American Water Resources Associatio↗
USGS2007

Using a Geographic Information System to determine the relation between stream quality and geology in the Roberts Creek watershed, Clayton County, Iowa

A geographic information system (GIS) was used to determine the relation between the stream-water quality and underlying geology in Roberts Creek watershed, Clayton County, Iowa, for base-flow conditions during the spring and summer of 1988&ndash;90. Geologic, stream, basin and subbasin boundaries, and water-quality sampling-site coverages were created by digitizing available maps. A contour coverage was created from digital line-graph data. The areal extent of geologic units subcropping in each subbasin was quantified with GIS, and the results then were output and joined with the discharge and water-quality data for statistical analyses. Illustrations showing the geology of the study area and the results of the study were prepared using GIS. By using GIS and a statistical software package, a weak but statistically significant relation was found between the water temperature, pH, and nitrogen concentrations in Roberts Creek and the underlying geology during base-flow conditions.

Iowa↗
USGS2007

A Geographic Information System procedure to quantify drainage-basin characteristics

The Basin Characteristics System (BCS) has been developed to quantify characteristics of a drainage basin. The first of four main BCS processing steps creates four geographic information system (GIS) digital maps representing the drainage divide, the drainage network, elevation contours, and the basin length. The drainage divide and basin length are manually digitized from 1:250,000-scale topographic maps. The drainage network is extracted using GIS software from 1:100,000-scale digital line graph data. The elevation contours are generated using GIS software from 1:250,000-scale digital elevation model data. The second and third steps use software developed to assign attributes to specific features in three of the four digital maps and analyze the four maps to quantify 24 morphometric basin characteristics. The fourth step quantifies two climatic characteristics from digitized State maps of precipitation data. Compared to manual methods of measurement, the BCS provides a reduction in the time required to quantify the 26 basin characteristics. Comparison tests indicate the BCS measurements are not significantly different from manual topographic-map measurements for 11 of 12 primary drainage-basin characteristics. Tests indicate the BCS significantly underestimates basin slope. Comparison-measurement differences for basin slope, main channel slope, and basin relief appear to be due to limitations in the digital elevation model data.

Conference Paper↗
USGS2007

Channel stability downstream from a dam assessed using aerial photographs and stream-gage information

The stability of the Neosho River channel downstream from John Redmond Dam, in southeast Kansas, was investigated using multiple-date aerial photographs and stream-gage information. Bankfull channel width was used as the primary indicator variable to assess pre- and post-dam channel change. Five six-mile river reaches and four stream gages were used in the analysis. Results indicated that, aside from some localized channel widening, the overall channel change has been minor with little post-dam change in bankfull channel width. The lack of a pronounced postdam channel change may be attributed to a substantial reduction in the magnitude of the post-dam annual peak discharges in combination with the resistance to erosion of the bed and bank materials. Also, the channel may have been overwidened by a series of large floods that predated construction of the dam, including one with an estimated 500-year recurrence interval.

Kansas↗