Geology topics

Research about Kansas

Source-linked reports with geographic coverage including Kansas.

At least 19 recordsLinked to original sources

USGS2026

Long-term trends of selected pesticides in the Little Arkansas River, south-central Kansas, 1995–2023

The eastern part of the High Plains Aquifer, herein called the Equus beds aquifer, is currently a primary source of water (2026) for the city of Wichita, Kansas. The Equus Beds Aquifer Storage and Recovery Project was developed in the early 1990s to meet future water demands by using the Little Arkansas River as an artificial aquifer recharge water source during above-base-flow conditions in the river. Little Arkansas River water is diverted at an intake structure, treated following National Primary Drinking Water Regulations as a guideline, and delivered to the aquifer through recharge basins or injection wells for later use. The U.S. Geological Survey, in cooperation with the city of Wichita, completed the study described in this report to quantify and characterize Little Arkansas River water-quality data. Data in this report can be used to evaluate changing conditions in aquifer recharge source water, provide science-based information for decision making, and help meet regulatory monitoring requirements. Continuous streamflow, specific conductance, turbidity, and discrete atrazine data were collected from two Little Arkansas River study sites and discrete glyphosate and aminomethylphosphonic acid was collected from one of the two Little Arkansas River study sites from 1995 to 2023 to evaluate water-quality conditions and assess pesticide trends. Pesticide trends in the herbicides atrazine and glyphosate and the herbicide-associated compound aminomethylphosphonic acid (a glyphosate degradate) were evaluated using the R package seawaveQ. Pesticides modeled with the seawaveQ R package had increasing and decreasing trends during the study period, depending on the individual pesticide and if there were strong seasonal patterns; larger estimated concentrations occurring in late spring and early summer. Modeled atrazine concentrations exceeded the Federal maximum contaminant level of 3 micrograms per liter about 8 percent of the time at both study sites. Atrazine had a nonsignificant increasing trend (98 percent) at the Highway 50 site and a nonsignificant decreasing trend (31 percent) at the downstream Sedgwick site during the study period. Glyphosate and aminomethylphosphonic acid trends were not evident at the Sedgwick site during the study period.

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USGS2026

3D Elevation Program—Kansas

Using 3D Elevation Program data, a modern illustration of each State's landscape showcases its elevation differences in vivid detail. Each State has been consistently adjusted and colorized according to its highest and lowest elevations, accentuating differences even in States with low relief. To further emphasize landforms, shaded relief has been added on top of the elevation colors.

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USGS2026

Landscape composition and proximity to water affect American badger occupancy in shortgrass prairies

Land use change in prairie ecosystems is pervasive. Prairie obligate species may be affected by these changes, though many carnivore-specific examples are unknown. We used 3 years (2018–2020) of camera-trap ( n = 381) data from Kansas, USA, to assess multiscale effects of landscape composition on habitat use by American badgers (badger, Taxidea taxus ). We predicted that site occupancy and colonization would be positively associated with the amount of prairie surrounding sites. We also predicted that site occupancy and colonization would be negatively related to amounts of agriculture and the number of wind towers surrounding sites. Badgers were insensitive to amounts of prairie surrounding sites and likely to occupy and colonize sites surrounded by row-crop agriculture. Badgers were also less likely to occupy sites farther from permanent water. Badgers may be exploiting agricultural areas because of increased prey densities or suitable burrowing substrates. Moreover, our study highlights the importance of water resources to badgers in arid regions.

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USGS2026

Statistical facilitation in environmental science: Integrating results from complementary statistical analyses can improve ecological interpretations

Professionals working in biological conservation seek to understand, manage, and restore populations of native organisms using many techniques. A common approach for this discipline is using long-term data collections to inform decision making. However, several quantitative issues complicate statistical analysis of monitoring datasets and can reduce the utility of results for conservation decision making. Integrating results from multiple analyses applied to the same dataset (i.e., approaching the same biological problem using different techniques) is one way to address concerns related to field data that violate statistical assumptions. This process allows data analysts, researchers, and managers to assemble insights based on the weight of evidence. Here we tested whether three different statistical techniques [(1) multiple logistic regression on original data, (2) multiple logistic regression on standardized data (i.e., mean of 0 and standard deviation of 1), and (3) random forest analysis] identified a similar hierarchy for selecting natural and anthropogenic habitat regressors. Our examination of how environmental variables affected Plains Minnow ( Hybognathus placitus ), a state-threatened fish, is relevant to other taxa and locations. We gained useful information from redundancies (i.e., agreements across analyses). New directions also emerged by addressing ambiguities (i.e., disagreements among results across analyses). When multiple analyses were integrated into one ecological story, a clearer interpretation emerged. Viewing different statistical tests as facilitators that provide mutual advantages can advance the understanding and application of statistical analyses applied to non-experimental field datasets.

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USGS2026

Restoration based on cost-benefit optimization: A grasslands pilot study

Ecological restoration is essential to meeting global biodiversity conservation goals. Given limited conservation budgets, deciding where to restore habitat is a key challenge for the coming decade. We developed a spatially explicit framework to optimize ecological restoration site selection by integrating land use history, species distributions, and economic costs. The framework includes the following steps: identify potential restoration area based on relevant environmental measures like land use; identify species of interest; calculate restoration benefits by modeling habitat and climate suitability and estimating reduced extinction risk associated with restoring a particular land parcel based on a modified species–area relationship; aggregate benefits across species; and compare to parcel-level land acquisition costs. We applied linear programming to maximize conservation benefit/restoration cost ratios to identify optimized restoration sites. We illustrate this approach using a case study for highly threatened grassland ecosystems in the Great Plains region of Kansas, USA. We selected five grassland animal species (greater prairie chickens [ Tympanuchus cupido ], lesser prairie chickens [ Tympanuchus pallidicinctus ], swift fox [ Vulpes velox ], pronghorn [ Antilocapra americana ], and regal fritillary [ Speyeria idalia ]) as indicators of restoration benefit across taxa. For the indicator species that we chose, shortgrass and mixed-grass prairies had the highest conservation benefit to cost ratio. Setting a minimum restoration threshold for each habitat type allowed us to identify high-priority tallgrass prairie sites. Despite increasing interest in ecological restoration, optimizing restoration site selection is challenging because one must consider habitat features that do not currently exist. The modeling approach described here is flexible and can be updated for different ecosystems, species, and conservation priorities. We outline potential alterations that can be made in future analyses, depending on desired restoration goals.

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USGS2026

Estimating paleotemperature using stable isotopes of soil-formed phyllosilicates from paleosols: A review

Fossilized soils, or paleosols, contain soil-formed phyllosilicates whose stable isotopic compositions may be used to calculate paleotemperature and thus reconstruct ancient terrestrial environments. Though paleosols are common in the geologic record, the use of phyllosilicates as paleotemperature proxies is limited in the literature owing to difficulties with selecting optimal paleosols, isolation from non-clay minerals and organic materials, mixtures of phyllosilicates in natural samples, wide variations of chemical compositions for phyllosilicates, and limited to undefined equilibrium fractionation factors between phyllosilicates-water. Here, we address these challenges by examining and comparing methods used for sample selection, mineral isolation, pretreatments, mineral identification, conventional and developing methods for oxygen and hydrogen isotopic analyses, and determination of phyllosilicate-water equilibrium fractionation factors, concluding with recommendations for best approaches for paleotemperature estimation. Additionally, we discuss how to identify and avoid detrital phyllosilicates, the impacts of diagenesis, comparison of stable isotope and non-isotope paleosol paleotemperature proxies, and challenges and opportunities for broadly using paleosols as paleoclimate archives. With ongoing efforts to refine this multi-faceted paleotemperature approach, the stable isotope geochemistry of soil-formed phyllosilicates continues to be an invaluable proxy system, enhancing our understanding of terrestrial paleoenvironments and paleoclimate.

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USGS2026

Contemporary greater prairie-chicken habitat distribution change and landscape thresholds in Kansas

Grassland bird monitoring efforts continue to document population declines in the Great Plains, USA and there is limited understanding of how declines are associated with landscape changes over broad scales. Within Kansas, USA, surveys indicate the resident grassland obligate greater prairie-chicken ( Tympanuchus cupido ) declined during the past 30 years. Grassland loss has been cited as the main driver of the decline; however, other factors including pesticide application, woody encroachment, and anthropogenic vertical structures are likely attributable. To evaluate, we used a random forest modeling approach to compare grassland cover, woody cover, and pesticide use between occupied ( n = 5552) and “pseudoabsent” ( n = 11,223) greater prairie-chicken lek site locations from 1993 to 2020. Our best-supported variables were grassland within 5 km, woody cover within 800 m, and pesticide application within 5 km of lek locations. The model correctly predicted the use or absence of leks with 89.95% accuracy based on independent validation. Our analysis suggests that grasslands have become aggregated within a 5 km radius where woody encroachment is less pronounced in the Smoky Hills and Northern High Plains management units and therefore landscapes have become more favorable for greater prairie-chickens at this scale. In contrast, the Flint Hills management unit netted a 13% loss of greater prairie-chicken habitat coinciding with woody encroachment and increased pesticide use. For 2020, we predicted a further loss of functional habitat from the presence of wind turbines, power transmission lines, and oil and gas infrastructure using previous literature documenting scales of avoidance. Our results support hypotheses that grassland loss, woody encroachment, and pesticide use all present negative population consequences for greater prairie-chickens. Current trends may be altered with grassland conservation action that seeks to conserve grasslands with < 10% woody cover and minimal pesticide use.

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USGS2026

A weight-of-evidence system for integrating monitoring and environmental indicators to guide biological conservation and resource management of native taxa

Many state and federal environmental management agencies are charged with using data-driven evidence to conserve and restore threatened and endangered species that are adversely impacted by humans. Yet, statistical analyses of available environmental indicator data do not always promote unambiguous, ecologically-meaningful, evidence-based decisions for managing native biota. Here we modified our multi-step quantitative adaptive management framework to identify natural and anthropogenic environmental indicators that maintain or threaten native species. In a proof-of-concept example, we quantified how three native stream fish taxa responded to nine environmental indicators based on three criteria (i.e., statistical significance, ecological relevance, and agreement with expectations). The resulting Weight of Evidence (WoE) integration identified five groups of indicators, clarified ambiguous trends, and identified promising future directions that would not have emerged from examining a single analysis or a single taxon alone. Our evaluation and categorization of environmental indicators established the biological foundation on which multi-disciplinary sustainability rests. Our research contribution demonstrates how following a structured integration framework can lead to novel insights that benefit conservation across organisms and systems even when employing relatively simple analytical techniques. Our results address the following often ignored questions: How do we systematically link together different analytical components of the same larger problems? How do we ecologically integrate similar and dissimilar results across analyses? How can we identify generalities by comparing multiple taxa?

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USGS2025

A framework tool that applies weight-of-evidence integration to the analysis of existing datasets to guide freshwater conservation

The overarching issue we address here is how to extract clear and actionable ecological and management insights from real-world field data that often do not satisfy traditional statistical assumptions. Toward this goal, we developed a general 12+6 step adaptive management framework tool. We applied this framework tool to existing biodiversity monitoring data to create a proof-of-concept result that addresses the overarching question of “ why might a specific native stream fish taxon be present or absent at specific locations? ” Our multi-step framework tool links established steps and steps that are unique to our framework through weight-of evidence (WOE) integration, an approach that combines quantitative results from multiple visualization and statistical procedures. The systematic use of all steps in our framework can provide improved conservation outcomes compared to a single analysis. Advantages accrue from our approach because our framework tool refines the overarching goal into related sub-questions, applies a specific quantitative procedure to each sub-step, combines results from all sub-questions using a WOE integration, identifies testable questions that elucidate ambiguities and gaps revealed through WOE integration, and proposes practical field methods for obtaining this clarifying information through future research and data collections. The process of considering multiple visualizations and analyses as individual pieces of a shared puzzle offers a new way to approach the use of existing data. Our team-based approach transforms the collection and analysis of existing data into a series of field tests that can guide future actions (e.g., data collection-analysis events, restoration initiatives, research). Habitat and impact regressors will vary with taxa and system, but our structured process tool has broad generality for a range of conservation issues in which freshwater systems are threatened by human impacts.

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USGS2025

Detection probabilities of Flathead Catfish in small Kansas impoundments

A primary challenge of Flathead Catfish Pylodictis olivaris management is uncertainty associated with sampling strategies and resulting ambiguity in population-level information. Assessment of impoundment and environmental conditions that affect detection probability may aid in reducing sample variance and benefit inferences regarding changes to Flathead Catfish populations. We sampled eight small impoundments in Kansas (37–114 surface ha) using low-frequency electrofishing in summer, 2021. We revisited sites nine times over three months using an occupancy modeling framework to estimate the influence of impoundment and environmental conditions on detection probability of Flathead Catfish. We employed an information theoretic approach and ranked models built with impoundment as a random effect and three environmental variables predicted to influence detection of Flathead Catfish in small impoundments. Detection probability across all populations was 0.526 (SE = 0.020) and was influenced by water temperature, mean depth of the impoundment, and proportion of impoundment sampled. Generally, detection probability increased with all measured variables. The inclusion of detection probability in assessments of Flathead Catfish in small impoundments can inform interpretation of catch-related metrics. Further, variable detection suggests collection of multiple samples during a defined sampling period might be more suitable for characterizing populations than a single sample.

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USGS2024

The 3D Elevation Program—Supporting the Kansas Economy

Introduction High-resolution elevation data for Kansas inform decision making to improve the State’s economy. Existing elevation data coverage is used to support State water planning initiatives, facilitate infrastructure management, and improve resilience to natural disasters. The expanding availability of current and more accurate elevation data helps better support natural resources conservation, agriculture and precision farming, flood risk management, water supply planning, infrastructure and construction management, and geologic resource assessment and hazard mitigation. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Kansas. The status of available and in-progress 3DEP baseline lidar data in Kansas is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $14.41 million in new benefits annually to the State. The top nine Kansas business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

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USGS2024

Empirical assessments of the type and strength of stream fish habitat associations can advance understanding of functional diversity and promote effective conservation.

The ability to accurately quantify biodiversity is fundamental to understanding ecological trends, identifying drivers of declines, and selecting effective conservation options. Scientists and resource managers have grappled with what metrics best show relevant biodiversity patterns and are still practical enough to aid on-the-ground resource conservation. Our purpose is to construct empirically derived, functional habitat guilds for prairie stream fish, then recommend future directions for constructing and using diversity metrics that aid field-based conservation. Working in the Upper Neosho River, KS, USA, we used univariate methods, cluster analysis, non-metric multi-dimensional scaling, and an analysis of similarity to functionally group stream fish taxa. The 11 most abundant fish species grouped into seven ecological guilds: riffle specialist, pool specialist, riffle generalist, pool generalist, riffle–run generalist, pool–run generalist, and generalist. Combining the habitat type and strength of association added ecological accuracy to our species groups. Employing multiple statistical methods increased confidence and generality in our grouping results. Moving forward will require a coordinated, coalition-driven, conservation-related strategy on which researchers and practitioners collaborate to synthesize diverse empirical results, organize general principles of structure and function, and balance accuracy with practicality.

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USGS2024

Computation of bromide concentrations at the Kansas River at De Soto, Kansas, January 2021 through October 2023

The Kansas River is an essential water resource that provides drinking water to more than 950,000 people in northeastern Kansas. Water suppliers that rely on the Kansas River as a water-supply source use physical and chemical water-treatment strategies to remove contaminants before distribution. Water District No. 1 of Johnson County, Kansas (WaterOne), is the largest water supplier in the State and uses the Kansas and Missouri Rivers as water-supply sources to provide drinking water to the Kansas City metropolitan area. WaterOne has been using ozone disinfection as a primary water-treatment strategy since the summer of 2020. Water suppliers that rely on ozone disinfection have become increasingly concerned with the presence of elevated dissolved bromide (the negatively charged form of bromine; hereafter referred to as “bromide”) concentrations in their water-supply source. Ozone disinfection of source water containing elevated concentrations of bromide can lead to the formation of bromate, a regulated disinfection byproduct and probable carcinogen. Real-time computations of bromide concentrations upstream from the WaterOne source-water intake in the Kansas River can be used to assist WaterOne with proactive adjustment of water-treatment strategies. These computations can also be used to advance understanding of hydrologic processes affecting ozone disinfection and formation of bromate. This report documents the development of the surrogate-regression model that computes bromide concentrations in real time at De Soto, Kansas, and characterizes daily and monthly bromide concentrations at this location during the study period. The U.S. Geological Survey (USGS), in cooperation with WaterOne, collected specific conductance and discrete bromide sample data at the USGS streamgage Kansas River at De Soto, Kans. (06892350; hereafter referred to as “De Soto”), during January 2021 through October 2023 to develop a surrogate-regression model using ordinary least-squares regression that computes bromide concentrations at De Soto, which is about 15 miles upstream from the WaterOne source-water intake in the Kansas River. Specific conductance explained about 85 percent of the variance in bromide concentrations at De Soto during the study period. The surrogate-regression model documented in this report estimated that bromide concentrations at De Soto were likely to exceed the WaterOne water-treatment level of concern (150 micrograms per liter [μg/L]) when specific conductance was greater than or equal to about 930 microsiemens per centimeter at 25 degrees Celsius. Surrogate-regression model computations of bromide concentrations documented in this report are available at the USGS National Real-Time Water-Quality website ( https://nrtwq.usgs.gov/ ). Bromide concentrations in discrete samples ranged from 31.9 to 251 μg/L and exceeded the water-treatment level of concern in about 34 percent of the 41 samples collected at De Soto during January 2021 through October 2023. Computed daily bromide concentrations ranged from 38.2 to 277 μg/L and exceeded the water-treatment level of concern about 46 percent of the time during January 2021 through October 2023. Generally, an inverse relation was observed between bromide and streamflow during the study period. Higher bromide concentrations were observed during September through February, and lower bromide concentrations were observed during March through August. Seasonal median bromide concentrations were significantly different in all pairwise seasonal combinations, except for summer versus spring. Computed median bromide concentrations were highest during winter, followed by fall, then spring and summer.

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USGS2024

Water-quality constituent concentrations and loads computed using real-time water-quality data for the Republican River, Clay Center, Kansas, August 2018 through July 2023

Milford Lake, the largest reservoir by surface area in Kansas, has had confirmed harmful algal blooms every summer since reporting began in 2011, except 2018–19. Milford Lake has been listed as impaired and designated hypereutrophic under section 303(d) of the 1972 Clean Water Act. In 2014, the Kansas Department of Health and Environment established a total maximum daily load for eutrophication and dissolved oxygen impairments. In 2018, the Natural Resources Conservation Service funded the Regional Conservation Partnership Program for the Milford Lake Watershed to focus on best management practices in the Lower Republican River Basin. The U.S. Geological Survey, in cooperation with the Kansas Water Office, completed this study to assess and quantify water-quality constituent concentrations and loads for total nitrogen (TN), total phosphorus (TP), and suspended sediment (SS) using previously published models for the Republican River near Clay Center, Kansas (U.S. Geological Survey station 06856600), about 15 miles upstream from Milford Lake, during August 1, 2018, through July 31, 2023. TN, TP, and SS concentrations and loads were monitored because of their relation to water supply and water-quality issues in Milford Lake, including nutrient and sediment transport, taste-and-odor events, potentially toxic cyano-harmful algal bloom events, and subsequent downstream transport of contaminants. Data from this report can be used to evaluate changing conditions, provide science-based information for decision making, and help meet regulatory requirements. The study mean annual loads for TN and TP were greater than the reported mean annual total maximum daily load and exceeded the watershed reduction goals as well as Kansas nonpoint source reduction goals defined by the Watershed Restoration and Protection Strategy for the Lower Republican watershed. TN and TP annual loads during 2019–20 were greater than the defined mean annual total maximum daily load. During 2022, TN and TP annual loads were less than the Kansas nonpoint source reduction goal and during 2023 were less than the watershed reduction goal. SS loads were less than the mean annual sedimentation rate computed from the total maximum daily load for the entirety of the study period, and the study mean annual load was 72 percent less than the designed annual reservoir sedimentation rate for Milford Lake. Data collected during the study period represented a wide range of streamflow and water-quality conditions at the Clay Center site, ranging from low-flow with less frequent runoff during 2023 to high-flow with frequent runoff during 2018. Nutrient reduction goals were only met in the final 2 years of the study period when annual mean flow conditions were lower than normal, indicating that goals may be unattainable during average or high-flow conditions. In all years except 2019, the annual mean SS load was less than the 20-year sediment load reduction target. Although annual SS loads at the Clay Center site generally decreased over time, corresponding reductions in annual streamflow indicated that these reductions may primarily be related to less frequent runoff from the upstream basin. Continued water-quality monitoring and tracking of best management practices are necessary to understand the success of Regional Conservation Partnership Program efforts to reduce nutrient transport in the Milford Lake Watershed.

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USGS2024

Water-quality trends in the Kansas River, Kansas, since enactment of the Clean Water Act, 1972–2020

The Clean Water Act was passed by Congress in 1972 to regulate pollution within the waters of the United States. The U.S. Geological Survey (USGS), in cooperation with the Kansas Department of Health and Environment (KDHE), the Kansas Water Office, the Nature Conservancy, the City of Lawrence, the City of Manhattan, the City of Olathe, the City of Topeka, WaterOne, and Evergy, compiled and analyzed historical streamflow and water-quality data collected by USGS and KDHE to characterize trends in water-quality constituents of interest because of their relation to water supply, drinking-water treatment, and sediment and nutrient transport, among others (total dissolved solids, chloride, ammonia, dissolved inorganic nitrogen [ammonia and nitrate plus nitrite], total nitrogen, orthophosphate, total phosphorus, total suspended solids, and fecal coliform bacteria) during mean- and low-flow conditions in the Kansas River since the passage of the Clean Water Act in 1972 through 2020. Trends in water-quality concentrations, or densities, and loads were analyzed using the Exploration and Graphics for RivER Trends R package and Weighted Regressions on Time, Discharge, and Season (WRTDS) model at upstream (Kansas River at Wamego, Kansas; USGS station 06887500) and downstream (Kansas River at De Soto, Kansas; USGS station 06892350) locations along the Kansas River using streamflow and water-quality data collected by the USGS and KDHE during 1972 through 2020. The Exploration and Graphics for RivER Trends Confidence Intervals R package and WRTDS bootstrap test estimated direction, uncertainty, and likelihood of trends in concentration and loads for each water-quality constituent of interest. Downward trends in concentration and load were observed for 5 of the 9 water-quality constituents at both sites during mean-flow conditions during the study period. During low-flow conditions, 7 of the 9 constituents exhibited downward trends, possibly reflecting reductions in point-source contributions to the Kansas River. Downward trends in ammonia, dissolved inorganic nitrogen, and total nitrogen during mean- and low-flow conditions were observed at both Kansas River sites, which were similar to patterns observed nationally. Upward trends were generally observed for orthophosphate and total phosphorus, which were similar to patterns observed at sites in the Mississippi River Basin. Downward trends, or no trend, were observed for chloride. Upward and downward trends were observed for total dissolved solids. Downward trends in total suspended solids and fecal coliform bacteria were observed at both sites, which were also similar to patterns observed nationally. The long-term trend analyses in this report are an essential step to understanding how water-quality conditions have changed in the Kansas River since the passage of the Clean Water Act.

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USGS2024

Streamflow characterization and hydromodification, Indian and Kill Creek Basins, Johnson County, Kansas, 1985–2018

Urban stream restoration requires a quantitative understanding of hydromodification to provide a scientific basis for establishing, prioritizing, and monitoring stream quality improvement goals. A study by the U.S. Geological Survey, in cooperation with the Johnson County Urban stream restoration benefits from a quantitative understanding of hydromodification to provide a scientific basis for establishing, prioritizing, and monitoring stream quality improvement goals. A study by the U.S. Geological Survey, in cooperation with the Johnson County Stormwater Management Program, began in 2017 to assess streamflow conditions at U.S. Geological Survey streamgages along Indian and Kill Creeks in Johnson County, Kansas. These streams represent the most urban (Indian Creek) and least urban (Kill Creek) drainage basins in the county. The assessment used 40 streamflow indicators to characterize streamflow conditions for both streams and quantify the degree of hydromodification for Indian Creek. The 40 streamflow indicators consisted of 35 commonly used indicators for characterizing streamflow, 2 less common seasonality indicators, and 3 other indicators based on duration curves, runoff hydrographs, and streamflow percentile classes. The indicators represented five key components of the natural streamflow regime: magnitude, frequency, duration, timing, and rate of change. As part of the study, indicators were evaluated as to general utility for characterizing streamflow conditions, quantifying hydromodification, and assessing the effectiveness of implemented management practices intended to restore urban streams. Results identifying indicators that serve these purposes could be applied more generally to other streams in Johnson County to assess hydromodification and potential restoration opportunities. Although the same set of streamflow indicators may not apply to other regions, methods and results presented in this report provide guidance, techniques, and perspective for future related or similar studies elsewhere, particularly those designed to quantify hydromodification of urban streams and monitor the effectiveness of restoration efforts. Compared to Kill Creek, which, for the purposes of this study, was considered representative of a least disturbed rural reference condition, Indian Creek hydrology was determined to be substantially modified because of urbanization. Of the 35 streamflow indicators evaluated, 19 indicated a generally consistent and substantial difference between the 2 streams. Hydromodification of Indian Creek was characterized by larger annual mean and monthly mean streamflows (and, thus, larger streamflow volumes), larger low streamflows of shorter duration, larger high streamflows with increased frequency and shorter duration, faster rise and fall rates, and decreased seasonality of high and low streamflows. For the two seasonality indicators, seasonality of high and low streamflows decreased. Duration curves, runoff event hydrographs, and streamflow percentile classes also indicated differences between the two streams for specific ranges of streamflow. Indicators that were useful in identifying generally consistent and substantial differences between the two streams, and therefore demonstrating they collectively or individually may be indicators of hydromodification, included annual median and mean flows; monthly mean flows for February, July, August, September, October, November, and December; all the minimum mean flow indictors (1-day, 3-day, 7-day, 30-day, and 90-day); annual number and mean magnitude of peak flows; some of the flow pulse indicators; and rise and fall rates. Indicators determined to be marginally useful or not useful for identifying consistent and substantial streamflow differences between streams included the flashiness indicators Richards-Baker flashiness index and the fraction of the year the daily mean flow is greater than the annual mean flow, which was not expected. Municipalities are challenged by the need to restore stream quality in urbanized areas where options are limited because of existing development. Understanding hydromodification effects and implications for stream quality can help managers plan urban development that minimizes degradation of stream quality and provides insights for implementing effective management practices. Streamflow indicators identified in this report can be used to guide urban stream restoration. In particular, the most useful indicators could form the basis of numeric criteria for restoration goals aimed at achieving or progressing toward more natural streamflow conditions—and, by extension, more healthy ecosystems—by characterizing flow conditions, quantifying hydromodification, establishing stream-restoration goals, and monitoring progress toward achieving those goals as management practices are implemented.

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USGS2023

Long-term water-quality constituent trends in the Little Arkansas River, south-central Kansas, 1995–2021

The Equus Beds aquifer and Cheney Reservoir are primary sources for the city of Wichita’s current (2023) water supply. The Equus Beds aquifer storage and recovery (ASR) project was developed by the city of Wichita in the early 1990s to meet future water demands using the Little Arkansas River as an artificial aquifer recharge water source during above-base-flow conditions. Little Arkansas River water is removed from the river at an ASR Facility intake structure, treated using National Primary Drinking Water Regulations as a guideline, and is infiltrated into the Equus Beds aquifer through recharge basins or injected into the aquifer through recharge wells for later use. The U.S. Geological Survey, in cooperation with the city of Wichita, completed this study to quantify and characterize Little Arkansas River water-quality data. Data in this report can be used to evaluate changing conditions, provide science-based information for decision making, and help meet regulatory requirements. Continuous (hourly) physicochemical properties were measured, and discrete water-quality samples were collected from three Little Arkansas River sites located along the easternmost extent of the Equus Beds aquifer during 1995 through 2021 over a range of streamflow conditions. The Little Arkansas River at Highway 50 near Halstead, Kansas, streamgage (U.S. Geological Survey station 07143672; hereafter referred to as the “Highway 50 site”) is located upstream from the other two sites, and the Little Arkansas River near Sedgwick, Kans., streamgage (U.S. Geological Survey station 07144100; hereafter referred to as the “Sedgwick site”) is located downstream from the other two sites; these two sites bracket most of the easternmost part of the Equus Beds aquifer. The Little Arkansas River upstream of ASR Facility near Sedgwick, Kans., streamgage (U.S. Geological Survey station 375350097262800; hereafter referred to as the “Upstream ASR site”) is located between the Highway 50 and Sedgwick sites, about 14.7 river miles (mi) downstream from the Highway 50 site, about 1.7 river mi upstream from the Sedgwick site, and immediately upstream from the ASR Facility intake structure. Surrogate models for water-quality constituents of interest (including bromide, dissolved organic carbon, 2-chloro-4-isopropylamino-6-amino- s -triazine [deethylatrazine], atrazine, and metolachlor) were updated or developed using continuously measured and concomitant discrete data. These surrogate models, along with previously developed regression models, were used to compute concentrations (at the Highway 50, Sedgwick, and Upstream ASR sites) and loads (at the Highway 50 and Sedgwick sites) during the study period. Federal criteria were used to evaluate water quality. Where applicable, water-quality data were compared to Federal national drinking-water regulations. Flow-normalized water-quality constituent trends were evaluated using Weighted Regressions on Time, Discharge, and Season (WRTDS) statistical models and water-quality trends were described using WRTDS bootstrap tests. Continuously computed primary ion concentrations were generally larger at the Highway 50 site compared to the Sedgwick site. During the study period, the Federal secondary maximum contaminant level (SMCL) for dissolved solids was exceeded 57 percent of the time at the Highway 50 site and 38 percent of the time at the Sedgwick site. Computed bromide concentrations were larger at the Highway 50 site and exceeded the city of Wichita treatment threshold about 70, 21, and 19 percent of the time at the Highway 50, Sedgwick, and Upstream ASR sites, respectively. Chloride concentrations exceeded the Federal SMCL about 16 percent of the time at the Highway 50 site and did not exceed the SMCL at the Sedgwick site. Continuous arsenic concentrations exceeded the Federal Maximum Contaminant Level (MCL) 9 to 15 percent of the time at the Sedgwick and Highway 50 sites, respectively, during the study. Atrazine concentrations exceeded the Federal MCL 10 percent of the time at the Highway 50 and Sedgwick sites and 14 percent of the time at the Upstream ASR site during the study; computed glyphosate concentrations at the Sedgwick site never exceeded the MCL during the study. Little Arkansas River flow-normalized primary ion concentrations during 1995 through 2021 generally had downward trends and decreases were generally larger at the Highway 50 site compared to the Sedgwick site. Dissolved solids and chloride concentrations decreased at the Highway 50 and Sedgwick sites. Bromide had no trend at the Highway 50 site and a downward trend at the Sedgwick site. Nitrate plus nitrite and total phosphorus concentrations had upward trends at the Highway 50 site but downward trends at the Sedgwick site, whereas total organic carbon had upward trends at both sites. Nitrate plus nitrite, total nitrogen, total phosphorus, and total organic carbon fluxes had upward trends at the Highway 50 and Sedgwick sites. Suspended-sediment concentrations had an upward trend at the Highway 50 site and had no trend at the Sedgwick site. Arsenic concentrations had downward trends at the Highway 50 and Sedgwick sites. About one-quarter to one-half of the Little Arkansas River loads, including nutrients and sediment, were transported during 1 percent of the time during the study. Because streamflows are highly sensitive to climatic variation and an increase of extreme precipitation events in the Great Plains is expected, similar disproportionately large pollutant loading events may increase into the future. Continuous measurement of physicochemical properties in near-real time allowed characterization of Little Arkansas River surface water during conditions and time scales that would not have been possible otherwise and served as a complement to discrete water-quality sampling. Continuation of this water-quality monitoring will provide data to characterize changing conditions in the Little Arkansas River and possibly identify new and changing trends. Information in this report allows the city of Wichita to make informed municipal water-supply decisions using past and present water-quality conditions and trends in the watershed.

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USGS2023

Lesser Prairie-chicken incubation behavior and nest success most influenced by nest vegetation structure

Incubation breaks are necessary for any nesting bird but can increase the mortality risk of the nest or attending parent. How intrinsic and extrinsic variables affect nest attentiveness—the proportion of time a female is on nest during incubation— and subsequent survival of the nest remains unclear for uniparental species. We related female nest attentiveness to nest survival and tested the effects of intrinsic and extrinsic variables on nest attentiveness by female Lesser Prairie-chickens ( Tympanuchus pallidicinctus ) using GPS locations of 87 females at 109 nest sites in 3 study areas in Kansas during 2013–2015. Daily nest survival increased by 39% when nest attentiveness increased from 21% to 98%. Female Lesser Prairie-chickens were 18% less attentive as body mass increased from 600 to 920 g. Daily precipitation and temperature, controlled for days into the incubation period, had interactive effects on nest attentiveness with nest attentiveness lowest on cool, wet days and increasing as temperature increased, regardless of precipitation (41% attentiveness at 16°C and 79 mm of precipitation to 90% attentiveness at 37°C and 41 mm of precipitation). Nest attentiveness increased by 11% as the quantity of grass at the nest site increased from 5% to 78% when visual obstruction was at 1 and 2 decimeters (dm) and increased 9% as the quantity of grass at the nest site increased from 5% to 83% when visual obstruction was at its maximum (3 dm). Our findings reveal the critical importance of nest attentiveness and incubation behavior, not only in relation to demography, but within the context of changing environmental conditions. As warmer temperatures and extreme precipitation events become more common and change the growth rates of vegetation, species like the Lesser Prairie-chicken that are ground-nesting, rely on vegetation cover, and exhibit uniparental care could experience negative demographic consequences.

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