Kansas Governor's Water Conference

Extending the Kansas Flood Mapping Dashboard for Road Network Flooding

Abu Mahdi, Jude Kastens, Xingong Li, David Weiss

Abstract

Flooding of road networks poses significant concerns to public safety, emergency response, and evacuation planning. However, most existing flood mapping approaches focus primarily on broad inundation zones rather than detailed road-level impacts. Researchers at the Kansas Biological Survey have developed an operational flood mapping tool covering eastern Kansas. As an extension of this tool, we developed a multi-stage automated procedure that integrates two types of LiDAR data (1) bare-earth elevation and (2) first-return surface elevation with NG911 road centerline features as a spatial foundation. This process extracts continuous elevation profiles along road centerlines to identify inundated road segments. Results demonstrate that this method provides a more accurate picture of road-level flooding by accounting for elevated structures such as bridge decks, which conventional terrain-based flood models often misrepresent as open channels. Furthermore, the approach enhances the scalability of road inundation mapping across large areas with complex transportation networks, supporting drivers and emergency responders in route planning during flood events. This poster discusses the specific challenges the algorithm addresses in eastern Kansas and how it advances operational flood mapping for transportation resilience.

Presented by

Abu Mahdi

Institution

University of Kansas

Water Quality Assessment of Big Creek Reach in Ellis County, KS

Nathaniel Tabor, Olivia Reed, Fama Dia

Abstract

This study investigates water quality along an 8-mile segment of Big Creek trending from NW to SE in Ellis County, Kansas, with sampling concentrated in the city of Hays and the FHSU campus. Water samples were measured for physical-chemical parameters, and samples were collected for ionic composition analysis. The purpose was to determine spatial variations in nutrient and metal concentrations to assess water quality. Measurements show that pH values remain consistently above neutral (7.78). The analysis reveals that very few fluctuations in alkalinity, while salinity decreases slightly and stabilizes downstream. Major cations: Calcium, Sodium, Magnesium exhibit similar behavior to salinity. Cross-plot analyses confirm a strong positive relationship between total dissolved solids and salinity. The highest TDS measured was 925. These findings suggest that Big Creek maintains moderately fresh-water quality but exhibits clear spatial trends likely influenced by local geology, runoff, and agricultural inputs. Future research will expand sampling across seasons and tributaries, such as Chetloah, North Fork, and Mud Creek, and incorporate discharge data to understand better flow-dependent variations, nutrient cycling, and potential impacts within the Big Creek watershed.

Presented by

Olivia Reed

Institution

Fort Hays State University

On-farm solar arrays to enhance recharge, produce energy, and diversify farm income

Hanna Szydlowski, Sam Zipper

Abstract

Since mid-2024, a novel pilot project has been launched as an innovative approach to solving interlinked issues between water, energy, and economic struggles faced by the agricultural industry in western Kansas. This project aims to provide a solution to these issues by using the uncultivated non-irrigated corners of center pivot fields for the installation of on-farm solar arrays outfitted with rain collection gutters to route water directly into the subsurface and enhance groundwater recharge. These pivot-corner solar recharge systems are expected to simultaneously enhance water resources, reduce the agricultural carbon footprint, increase Kansas energy resiliency, and provide economic benefits to farmers.

Our pilot-scale pivot-corner solar recharge system became operational in late summer 2025. Following its deployment, we will conduct detailed hydrological and energy monitoring to evaluate the system’s performance against conventional solar designs and assess benefits in the hydrologic, climate, energy, and economic sectors. This poster highlights the current status of the project, next steps, and offers preliminary results on site soil hydrologic changes.

Presented by

Hanna Szydlowski

Institution

University of Kansas

Identifying tradeoffs between agro-economics and water resources to guide future management decisions

Bre Rivera Waterman, Sam Zipper

Abstract

Aridity is expected to increase across the central United States, shifting the dividing line between the humid East and arid West and placing regions such as the Great Plains at growing climatic risk. As an analog for future Great Plains conditions, the Eastern Kansas River Basin provides an opportunity to evaluate agricultural strategies that enhance crop productivity while protecting water quantity and quality. We asked: (1) What historical combinations of land use and climate minimized trade-offs between net returns and water resources? and (2) What alternative land-use configurations could further reduce these trade-offs? Using data from 2006-2024, we integrated independent statistical models of nitrate flux, irrigation water use, and net returns, and applied the NSGA-II optimization algorithm with land use as the decision variable. Our objectives were to maximize net returns and minimize both nitrogen flux and irrigation water use. We evaluated four alternate land-use scenarios (business-as-usual expansion, diversified expansion, irrigated management and rainfed management) and compared their Pareto frontiers, knee points, and ranges of predicted outcomes for each objective. We found that historically, optimal years were drier and characterized by higher-than-average soybean and wheat shares and lower corn and sorghum shares. Preliminary scenario results suggest that both diversified expansion and rainfed management maintain net returns while reducing impacts to water quantity and quality, highlighting promising pathways for climate-resilient agricultural planning in the Eastern Kansas River Basin and similar Great Plains landscapes.

Presented by

Bre Rivera Waterman

Institution

University of Kansas

Effect of cover crop and tillage on field saturated hydraulic conductivity in continuous corn systems

Anjan Bhatta, Sam Zipper

Abstract

Field saturated hydraulic conductivity (Kfs) is a key indicator of soil health and relates to the ability of soils to infiltrate and retain water. Cover crops and reduced tillage are widely used soil health management practices, but past studies have shown mixed impacts on Kfs. Here, we investigated the effects of cover cropping and tillage on Kfs in corn production systems across five different locations across the central US. Sites were located near Garden City KS; Alton KS; Gothenburg NE; Ames IA; and Scott MS. At each site, we measured Kfs using a Saturo automated infiltrometer during approximately peak growing season conditions in summer 2025. We found that location had a highly significant effect on Kfs, suggesting strong spatial variability across the sites. While the main effects of cover crop and tillage were not significant, they did have a significant interaction, which implies that the Kfs response to cover crops depends on the tillage practice (and vice versa). Visually, it appeared that Kfs was higher in tilled plots when combined with cover crops, and higher in no-till plots without cover crops at most sites. However, differences were small and not statistically significant. Ongoing work will characterize changes in Kfs through time at these sites to better understand how different soil health management practices affect soil hydraulic conductivity.

Presented by

Anjan Bhatta

Institution

University of Kansas

A Fluorescent Approach to Understanding Nutrient and Dye Translocation in Crops

Veronica Portillo, Rose Elbert, Audrey Empkey, Xuan Xu, Gaurav Jha, Amie Norton

Abstract

Understanding how molecules move through plants is fundamental to improving crop productivity, nutrient use efficiency, and stress resilience. Traditional methods to study molecular transport offer valuable insights but are limited by invasiveness, low spatial and temporal resolution, and poor scalability. These constraints hinder continuous visualization of transport dynamics during critical stages of germination and early development. This study introduces luminescent seeds as a novel, non-destructive approach to investigate molecular transport pathways in plants. By soaking seeds in fluorescent and luminescent dye solutions before germination, we created self-tracing plant systems that enable in vivo monitoring of dye translocation. During germination and seedling growth, fluorescence imaging revealed consistent movement of dyes from seed reserves into roots, shoots, and cotyledons, aligning with known xylem and phloem transport pathways. This technique provides a dynamic, high-resolution platform for real-time visualization of internal flow processes in intact, living plants. Luminescent seeds bridge a critical methodological gap in plant physiology by allowing continuous tracking of nutrient or xenobiotic movement under realistic growth conditions. The broader application of this approach extends to the study of nutrient allocation, agrochemical uptake, and stress-induced changes in transport efficiency. As a scalable, low-cost, and safe alternative to conventional tracing techniques, luminescent seeds offer a powerful new tool for advancing our understanding of plant transport mechanisms and supporting innovation in sustainable agriculture.

Presented by

Veronica Portillo

Institution

Kansas State University

Delineation of Arctic Valleys in Fennoscandia

Tyler Smith, Aleksey Sheshukov

Abstract

The environment in Arctic Fennoscandia can be broadly characterized by the micro-biomes/climates seen in the Uplands and Valleys. Uplands are largely devoid of life and characterized by their cragged bedrock surface and arid ground conditions. Valleys are lush areas which support and sustain plant and animal life, providing a stark contrast to the harsh uplands. However, there is no standardized method to delineate the extent of Valleys since the delineate the extent of Valleys since the definition of a "Valley" is arbitrary and regionally subjective. Further, the differences in classification schemes create additional discrepancies in the tangible characteristics by which valleys are defined. The goal of this study is to provide a standardized method for Valley delineation in Fennoscandia that is replicable, scalable, and verifiable. Delineation methods used in this study included the iterative use of preexisting tools to recognize spatial patterns in the terrain data (Geomorphons), image processing techniques (Progressive Black Top Hat), and hydrologic analysis (flow accumulation and routing). Preliminary results have shown the inclusion of hydrologic analysis in the increased efficacy of preexisting tools in accurately identifying biologically active valleys in the Fennoscandia Arctic. The iterative approach was referenced to the observational dataset and scaled up to represent the Valleys in the Varanger Peninsula region.

Presented by

Tyler Smith

Institution

Kansas State University

Assessment of Nitrate and PFAS Contamination of Private Wells in South Central Kansas

Thisura Ilukgoda Gedara, Helene Avocat, Amanda Alliband, Sherry Rogers, Richard Sloan, Saranya Puthalath, Randy Stotler, Caeli Richard, Matthew F. Kirk

Abstract

Private well water is not regulated by any of the federal or state laws within the state of Kansas, despite between 151,000 to 177,000 Kansans rely on it. In our study, we specifically targeted the private wells in the South-Central part of the state, where the Great Bend Prairie Aquifer is located. Out of the 218 wells that we sampled for nitrates in nine counties, 46.8% of the wells are exceeding EPA’s nitrate limit (10 mg/L as N) for safe drinking water. The positive correlation between water stable isotopes (δD and δ¹⁸O) and nitrate levels evidances that recharge happened during periods of higher evaporation carries elevated nitrate concentrations, reflecting the direct impact of agricultural activities on nitrate contamination. This idea is further supported by spatial and statistical analysis, as higher nitrate contamination was observed in cultivated areas compared to the areas that are treated with less amount of fertilizers. In 2024, PFAS was added as one of the water quality parameters to our study, making it the first detailed PFAS study in the area. We were able to detect concerning levels of PFOS(16.7%; ≥ EPA, 0.004 μg/L), PFOA(5.5%; EPA, 0.004μg/L), and PFOSA(46.3%; ≥ Wisconsin DHS, 0.004 μg/L ) within 54 analyzed samples despite there are no major PFAS releasing sites in the study area. Apart from these anthropogenic contaminations, this aquifer is showing a strong correlation between Na+ and Cl-, indicating saline water contamination from the deep part of the aquifer.

Presented by

Thisura Ilukgoda Gedara

Institution

Kansas State University

Agricultural Land Use and Nitrate in the Kansas River Alluvial Aquifer: Patterns Across Time and Space

Taylor Layman, L. French, C. Hatley, E. Seybold

Abstract

The Kansas River Alluvial Aquifer is used throughout the Kansas River Valley for agricultural irrigation and municipal supply. Nitrate derived from fertilizer can infiltrate the aquifer, creating risks for human health, environmental integrity, and agricultural sustainability. To better understand these risks, we examined spatial and temporal trends in nitrate concentrations. Nitrate data from 49 wells was analyzed using two datasets: the Kansas Department of Health and Environment's (KDHE) historical data (1985 - 2000), and the Kansas Geological Survey’s Aquifer Water Quality Assessment for Kansas (AWQUA) modern data (2021-2025). Across all samples, median nitrate concentration was 0.475 mg/L, ranging from 0.00275 to 53.6 mg/L. Outliers above 12 mg/L were excluded. Temporally, nitrate concentrations showed no significant correlation (p = 0.3369). Spatially, nitrate was analyzed relative to agricultural land use and distance from the river. Agricultural use was not a significant predictor, but distance from the river was. When both variables were analyzed together, spatial correlation was not significant (p = 0.1254). In the historical dataset, both land use and distance from the river were significant predictors of nitrate, suggesting the difference may stem from limited modern sampling. The historical data has 155 sampling events (average 7.05 visits per site), compared to only 48 modern samples (average 1.81 visits per site). Ongoing monitoring will improve long term comparisons and understanding of nitrate contamination. We will also expand this comparison to other aquifers for better insight into how these variables affect nitrate across the state.

Presented by

Taylor Layman

Institution

University of Kansas

Know your water II

Tatom Smith, Gus Peine, Carter Will, Dr. Jenne Lambert Sumeral, Dr. Richard Lisichenko

Abstract

The "Know Your Water" initiative is a collaborative, multi-agency effort to assess and communicate water quality trends across western Kansas. This study presents findings from over 200 domestic well samples collected across four regions, spanning five counties and four aquifers. Testing focused on eight key contaminants—sulfate, sodium, chloride, iron, lead, copper, E. coli, uranium, and radon—across two seasons and one precipitation event. Results reveal regional variability in contaminant concentrations, with sulfate and sodium levels showing notable aquifer-dependent patterns. Seasonal shifts and precipitation events influenced contaminant mobility, particularly in shallow aquifers. GIS mapping and longitudinal data analysis highlight emerging trends and potential risks to public health. These findings support ongoing community outreach and inform future groundwater management strategies tailored to aquifer type and regional land use.

Presented by

Tatom Smith

Institution

Fort Hays State University

SAVING KANSAS SOIL: QUANTIFYING SOIL LOSSES AND EVALUATING AGRICULTURAL BEST MANAGEMENT PRACTICES WITH GEOSPATIAL AND PHYSICALLY-BASED MODELING

Tahsin Ishrak Oishee, Brian Gelder, Tim Sklenar, Richard Cruse , Christian Conoscenti, Aleksey Sheshukov

Abstract

Soil erosion remains a threat to sustainable agriculture and water quality in Kansas, where rainfall-driven sheet and rill erosion degrade croplands and reduce productivity. This study applies the Water Erosion Prediction Project (WEPP) model to quantify soil losses and evaluate the effectiveness of Best Management Practices (BMPs) under diverse tillage and crop rotation systems. The study area, the Running Turkey Creek watershed within the Little Arkansas River Basin, was modeled using LiDAR-derived topography, gSSURGO soils, climate data, and management practices representative of Kansas croplands. WEPP simulates erosion along representative hillslopes by solving equations for infiltration, runoff generation, soil detachment, sediment transport, and deposition using the Green-Ampt infiltration and kinematic wave approaches. Preliminary runs were performed for three crop rotations: continuous corn (C), corn-wheat (CW), and corn-wheat-soybean (CWS), under four tillage systems: no-till (NT), light mulch (LM), moderate mulch (MM), and conventional tillage (CT). Results revealed that soil loss increases consistently with tillage intensity, with CT showing the highest erosion and NT the lowest. Transitioning from CT to NT reduced soil loss by 80-90% across all rotations, while LM and MM systems achieved intermediate reductions. Among rotations, CW generally exhibited slightly lower erosion than CWS due to greater residue cover from wheat. The findings demonstrate that reduced tillage and residue management are key to minimizing soil loss in Kansas croplands and support the use of WEPP as a powerful geospatial tool for designing site-specific BMP strategies.

Presented by

Tahsin Ishrak Oishee

Institution

Kansas State University

Understanding Controls on Nitrate Concentration in Groundwater: A Tandem Evolutionary Algorithm Approach

Shreya Chatterjee, Erin Seybold

Abstract

Groundwater nitrate contamination poses significant environmental and public health risks, particularly in intensively agricultural regions. Understanding the drivers of spatial and temporal nitrate variability remains a major challenge due to the complex, nonlinear, and interacting factors that influence groundwater systems. This study employs the Tandem Evolutionary Algorithm (TEVA), a novel machine learning tool that is well-suited for high-dimensional, noisy environmental datasets, to model nitrate concentrations in the Groundwater Management District 2 (GMD2) in Kansas. Using a comprehensive dataset of 3,059 groundwater samples (1974–2024) and multi-source predictor variables, the work aims to identify the specific combinations of anthropogenic (fertilizer application rates, land use, water use), and natural (climate, lithology, soil properties) factors that control nitrate exceedances above the U.S. EPA Maximum Contaminant Level (10 mg/L). Samples are classified as high (>10 mg/L) or low (<10 mg/L) nitrate classes. Preliminary work focuses on dataset assembly, predictor variable generation, and conducting exploratory spatial data analysis to prepare for the TEVA model run. The expected outcome is a set of interpretable rules that reveal how specific variable combinations drive nitrate contamination across the region. This research advances understanding of nitrate dynamics in complex hydrogeologic systems and demonstrates the potential of TEVA for environmental modeling and groundwater quality assessment.

Presented by

Shreya Chatterjee

Institution

University of Kansas

Comparative Effects of Soil Amendments on Soil Evaporation under Controlled Condition

Shahnawaz Alam Dip, Moises Gutierrez, Kasuni Gamage, Ryan Hansen, Ganga Hettiarachchi, Melanie Derby

Abstract

The depletion of the Ogallala Aquifer in the U.S. Central High Plains presents a significant challenge within the food-energy-water nexus, underscoring the need for strategies that minimize unproductive water loss from agricultural soils. This study investigates the effects of two soil amendments, wood-derived biochar and the biosurfactant Surfactin (naturally produced by Bacillus subtilis), on evaporation dynamics and water retention under controlled conditions. Experiments were conducted in a custom-built evaporation apparatus containing a 14 kg sandy loam soil layer (6 cm thick, 83.8 cm long, and 22.8 cm wide; 64% sand, 20% silt, and 16% clay) at a bulk density of 1.2 g cm⁻³. At the start of each experiment, the soil had a saturation ratio of 0.25 to 0.27. The chamber was exposed to a simulated solar flux of 150 ± 16 W m⁻² and an airflow of 1.444 kg h⁻¹, with evaporation rates determined via mass balance on the flow air. Separate trials were performed for 3 wt % biochar and 0.017 mg Surfactin g⁻¹ soil, each compared with untreated controls. Biochar reduced evaporation during the slow-rate stage by interrupting capillary continuity and retaining moisture within its micro and mesoporous structure, effectively doubling residual water content. Surfactin-treated soils exhibited lower evaporation across all saturation ratios due to a reduction in surface tension, which weakened capillary rise and enhanced adsorption at the solid-liquid interface. Although the two amendments influenced evaporation through different mechanisms, one by porous retention and the other by interfacial alteration, both improved water conservation efficiency.

Presented by

Shahnawaz Alam Dip

Institution

Kansas State University

Assessing Dryland Agriculture Management Practices Using UAV Multispectral Signatures

Sangam Bishwakarma, Dr. Augustine Obour, Dr. Dorivar Ruiz Diaz, and Dr. Deepak Joshi

Abstract

Conventional methods used to monitor impacts of regenerative agricultural practices on crop growth and productivity are laborious, prone to bias, and often require waiting until harvest. Digital technologies like Uncrewed Aerial Vehicle (UAV) based multispectral single-band signatures and vegetation indices (VIs) derived using band combinations can provide reliable, scalable insights to evaluate in-season crop growth. This study evaluated crop growth responses of corn (Zea mays) and soybean (Glycine max) to combined effects of nitrogen (60 lb/ac and 120 lb/ac), tillage (tillage and no tillage), and cover crops (with and without) treatments using a UAV equipped with a multispectral sensor. The multispectral UAV imageries were collected nine occasions throughout the growing season, and the normalized difference vegetation index (NDVI) was used to compare in-season growth responses across treatments. Both corn and soybean had higher NDVI for cover crop plots. Applying 120 lb/ac increased corn canopy NDVI values but N application had no effect on soybean in-season canopy NDVI. Soybean had significantly greater NDVI values under tillage compared to no-till treatments during later growth stages. UAV-derived canopy height showed strong correspondence with ground-measured height, with R² values of 0.74 for corn and 0.60 for soybean. Ongoing analysis will evaluate the predictive capacity of UAV, satellite, and fusion of UAV and satellite imagery to compare their effectiveness in predicting crop biomass and yield using machine learning models.

Presented by

Sangam Bishwakarma

Institution

Kansas State University

Spatio-temporal Models for Optimizing Best Management Practices

Robert Sholl, Trevor Hefley

Abstract

Nonpoint source (NPS) pollution continues to threaten the safety and quality of Kansas water supplies1. The Kansas Department of Health and Environment (KDHE) and Kansas Department of Agriculture (KDA) work to subsidize the implementation of Best Management Practices (BMPs) to control NPS pollution introduction. However, as practice implementations become more involved and complex the allocation of funds transforms into a problem of optimizing outcome per dollar spent. Presently, the allocation of funds is informed via basic quantitative techniques in coordination with expert knowledge. This creates significant burden on the subject matter experts and leaves large vulnerabilities for process breakdown should these experts vacate their positions. Existing and common techniques for assessing ideal practices at specific locations for optimal NPS pollution reduction focus on large, deterministic systems and simulation models2,3. The popularity of these techniques is mostly attributed to their ability to fuse the fundamentally separated data sources for NPS pollution and BMP implementation. However, these methods are often cumbersome to implement, computationally inefficient, and lack inherent uncertainty quantification. The objective of this study is to develop a modeling framework for informing optimal practice implementation for NPS pollution reduction that: 1. Accounts for uncertainty 2. Maximizes computational efficiency 3. Produces easily interpretable results The data from KDHE and KDA were spatially and temporally aligned, then fused for fitting to three proposed models. The models will be assessed for accuracy and computational efficiency to determine which will be included in a final dashboard tool for use by Kansas authorities.

Presented by

Robert Sholl

Institution

Kansas State University

Microplastics as a Vector for Cadmium Pollution of Groundwater

Reshma M Antony, M.B. Kirkham, and Kimberly A. Williams

Abstract

Since the mid-1950’s, plastics have been widely used in agriculture. They break down into microplastics (< 5 mm). They are a vector for heavy metal movement in soil. The microplastics end up in irrigation water. It is not known if the microplastics in irrigation water increase concentrations of heavy metals in groundwater. Therefore, the main objective of this experiment is to determine if drainage water from columns of soil with microplastics has more cadmium in the water than drainage water from columns without microplastics. Cadmium (Cd) is chosen, as it co-occurs geologically with phosphorus and is added to soil with phosphate fertilizer. Another objective is to determine if different types of microplastics affect the movement of cadmium through soil. Columns of soil will be irrigated with four types of microplastics: polyethylene glycol (hydrophilic); polystyrene (hydrophobic); polyethylene (neutral); polyvinyl chloride (neutral). Cadmium will be added to irrigation water. There will be ten irrigation treatments: control (tap water), with and without Cd; polyethylene glycol, with and without Cd; polystyrene, with and without Cd; polyethylene, with and without Cd; and polyvinyl chloride, with and without Cd. The concentration of Cd and microplastics in the drainage water will be analyzed by the Soil Testing Laboratory and by a laboratory in the College of Health and Human Services, respectively. The experiment will indicate if the presence of microplastics and their type in soil affect Cd and microplastic accumulation in groundwater, which is important to know to protect the aquifers in Kansas.

Presented by

Reshma M Antony

Institution

Kansas State University

Synthesis of ABA triblock copolymers via RAFT polymerization for water purification membranes

Prabhleen Kaur, Dr. Patricia R. Calvo

Abstract

Polymers have been widely used for various applications such as cosmetics, drug delivery, water waste treatment and many more. Previous studies have shown that triblock copolymers which are composed of three distinct hydrophobic and hydrophilic blocks can be used to make membranes that help in the purification of water by removing heavy metals, dyes, and pharmaceutical wastes. These block copolymers can be used due to their unique properties including chemical resistance, tunable pore size, balancing their hydrophobic and hydrophilic character and their ability to form micelles when they interact with water. In this study, we will be focusing on the synthesis of a library of amphiphilic triblock copolymers employing different hydrophobic and hydrophilic monomers. The final triblock copolymers (over 100 different compositions) will be characterized to examine their microstructure, which is important for membrane formation and determining pore size. We will also examine the aqueous self-assembly, which is important for encapsulation of contaminants. The synthesis of these triblock copolymers can be done using Thermal RAFT which employs the use of heat for polymerization and Photoiniferter polymerization which employs the use of light. We are expecting to synthesize polymers that have a more uniform molecular weight distribution (monodisperse) using the Photoiniferter RAFT. The data will be collected in the form of NMRs and Size Exclusion Chromatography traces to confirm the successful synthesis of polymers and to assess the molecular weight distribution of the polymer.

Presented by

Prabhleen Kaur

Institution

Kansas State University

Sequestering fertilizers from livestock wastes

Parnian Mohammadian, Elinor Steinbach, Huu Tuan Tran, Prathap Parameswaran, Jack Murphy, Ganga Hettiarachchi

Abstract

Global agriculture faces the dual pressure of nutrient pollution from concentrated animal feeding operations (CAFOs) and the reliance on finite resources like phosphate rock for fertilizer. This research developed a highly efficient, professional system to address these challenges by recovering valuable nutrients from swine wastewater that has been using an Anaerobic Membrane Bioreactor (AnMBR).

The purpose was to optimize a cost-effective, sequential process for simultaneously capturing ammonia (N) and orthophosphate (P) from the wastewater stream and converting them into value-added fertilizer products. This approach mitigates environmental risks, such as water pollution (eutrophication), while promoting sustainable resource management.

Integrated Recovery Process and Results

The study used two integrated physicochemical methods:

1. Phosphorus Recovery: This involved sequential chemical precipitation using calcium oxide (CaO). To prevent the co-formation of calcium carbonate, the wastewater was first acidified and aerated. This process achieved an outstanding phosphorus recovery efficiency of 98%, yielding a solid product.

2. Ammonia Recovery: The system demonstrated a high ammonia removal efficiency of up to 97.98%, bringing the ammonia concentration down to levels suitable for water reuse using ion exchange columns.

In conclusion, this work validates a technically viable and highly efficient integrated system capable of generating two distinct fertilizer products (solid P and liquid N solution). These findings provide a robust framework for designing scalable, decentralized treatment systems that both protect water quality and support a circular nutrient economy by reducing the need for energy-intensive synthetic fertilizers.

Future work:

1) Process Optimization for Extended Operation

2) Large-Scale Applicability and Validation

3) Clinoptilolite Regeneration and Performance

Presented by

Parnian Mohammadian

Institution

Kansas State University

Modeling Nitrate and Uranium Co-contamination in Groundwater in Kansas

Musabbir Turjo, Jeeban Panthi

Abstract

Groundwater contamination by nitrate and uranium has become an emerging concern across Kansas. Due to higher fertilizer application to produce food, the concentration of nitrate in groundwater is increasing as not all the nitrate is uptaken by plants. Some of these nitrates from the agricultural land leach into aquifer beneath the soils and act as a powerful oxidizing agent that can mobilize the insoluble uranium. Insoluble uranium (IV) is transformed into soluble uranium (VI) species by oxidative dissolution of minerals. This soluble uranium can easily get into the food chain by pumping groundwater by wells for irrigations and drinking purposes. Previous study found the correlation of nitrate and uranium across the high plain aquifer yet the mechanistic process of the transformation of U (IV) to U (VI) by nitrate is unresolved. This study examines the current conditions and hotspots of nitrate and uranium concentration and analyze the spatial correlation between the contaminants in groundwater across Kansas. The goal is to develop a coupled MODFLOW-PHREEQC model to simulate groundwater flow, solute transport and reactive transport of uranium using the hydrogeochemical parameters from a column experiment. The result shows that, high concentration of nitrate and uranium exceed the EPA MCL standard in groundwater in Kansas and nitrate and uranium are highly correlated in higher concentration zones.

Presented by

Musabbir Turjo

Institution

Kansas State University

Spray dynamics of Low energy precision application (LEPA) Irrigation Nozzles using biochar and water solution for water conservation

Michael Akinseloyin, Shahnawaz Alam Dip, Aiden Bienz, Melanie Derby

Abstract

Agricultural water scarcity in the U.S. Midwest, driven by rapid depletion of the Ogallala Aquifer, necessitates improved irrigation strategies that minimize water loss while maintaining crop productivity. Low Energy Precision Application (LEPA) center-pivot systems can enhance water‐use efficiency by delivering water closer to the soil surface; however, spray breakup and drift can still result in significant unintended losses. Biochar, a carbon-rich byproduct known for its superior water-retention and soil-enhancing capabilities, offers a promising approach for conserving water during irrigation if effectively dispersed through existing nozzle systems. This study experimentally investigates the spray dynamics and flow behavior of biochar-water solutions through LEPA spray nozzles under common operating conditions used by Midwest farmers. Experiments were conducted using water alone and mixtures containing biochar or biochar combined with viscosity modifiers(Xanthan gum). Flow rates, droplet breakup characteristics, and qualitative spray sheet behavior were compared. Results indicate that low-concentration biochar-water solutions exhibit higher surface tension and resistance to aerodynamic shear, reducing spray sheet breakup and maintaining droplet trajectories toward the target crop region. A 0.5 wt% biochar mixture delivered slightly higher flow rate (1.01 GPM) than water alone (0.961 GPM) at 6 psi, without significant operational complications. These observations suggest that biochar-laden water may reduce off-target drift and improve moisture deposition in soil. Future work will include droplet size measurement, quantification of soil water retention improvements, and greenhouse and field-scale validation of crop yield impacts. Overall, this work highlights biochar-water mixtures as a promising strategy for enhancing LEPA irrigation performance and reducing groundwater extraction demands.

Presented by

Michael Akinseloyin

Institution

Kansas State University

Quantifying the Effect of Crop Rotation on Seasonal Water Balance Components

Menard Soni, Jonathan Aguilar, Aleksey Sheshukov

Abstract

Soil-profile water dynamics shape irrigation decisions in western Kansas, where declining Ogallala aquifer heightens the need for rotation choices that use water efficiently. We quantified seasonal water-balance components under four cropping patterns: continuous corn (CONCOR), continuous cotton (CONCOT), corn-cotton (CORFCOT), and cotton-corn (COTFCOR). Precipitation and irrigation were measured using rain gauges; weekly neutron probe readings tracked root-zone storage; deep drainage was calculated from neutron probe reading below root zone; runoff was calculated from infiltration rate versus water inputs; actual evapotranspiration (Eta) was derived by closure. Seasonal totals were analyzed as completely randomized design using plot-level data. Across rotations, only the change in root-zone storage differed significantly: rotations finishing in cotton (CONCOT, COTFCOR) ended the season with more negative change in storage (drier profiles), whereas rotations finishing in corn (CONCOR, CORFCOT) retained more water by the common measurement end date (p < 0.05). Seasonal Eta, runoff, and deep drainage did not differ statistically among rotations. Because inputs and non-plant losses were comparable, change in storage reflects when water was used rather than how much was lost: cotton maintained later-season transpiration while corn senesced earlier, leaving more water in the profile. These findings imply that late-season irrigation thresholds may need to differ for rotations ending in cotton versus corn, and that post-harvest soil water status, and this off-season recharge and next crop starting conditions, depends on rotation end point.

Presented by

Menard Soni

Institution

Kansas State University

Land Use Change in Riparian Buffers: Impacts on Erosion and Flood Risk in the Blue River Headwaters Subwatershed

Matthew Paulson, Scott Schulte, Tony Layzell

Abstract

Headwater streams are an important but undervalued part of the watershed, and they can have an outsized impact on downstream flooding, water quality, and biodiversity. Over the past 20 years, Johnson County has been expanding south to cater to a growing population, often enclosing headwaters and encroaching into riparian vegetation buffers. This in-progress project investigates changes in riparian vegetation around the headwaters of the Blue River tributary to the Missouri River and evaluates associated increases in flood risk and erosion as identified in the Johnson County Watershed Phase 1 Master Plan published in 2022.

Land use and cover data are used to determine where new developments have been built and quantifies changes in land use within Federal Emergency Management Agency (FEMA) designated 1% flood zones and 30-meter riparian buffer zones between 2008 and 2024.

Presented by

Matthew Paulson

Institution

University of Kansas

INVESTIGATING SOIL MOISTURE DYNAMICS UNDER A NOVEL SPRAYABLE BIODEGRADABLE MULCH

Manavjot Singh, Vaishali Sharda

Abstract

It is well established that plastic mulches benefit crops by controlling weeds and conserving soil moisture. However, concerns about the environmental impacts of conventional plastics have accelerated a shift toward biodegradable polymers in agriculture. Yet installation, removal, and decompositional control of these films remain challenging. As an alternative, sprayable biodegradable mulches (SBM) are being developed, offering similar agronomic benefits without posing risk to the environment. This study (i) quantifies how a novel SBM, BioWRAP, affects soil moisture and evaporation, and (ii) evaluates modeling approaches to simulate soil moisture dynamics under SBM using soil column experiments. For this purpose, soil columns were placed in a growth chamber with and without BioWRAP application. Soil water content and water loss as evaporation were monitored regularly. To simulate moisture movement, we first applied HYDRUS-1D (a widely used one-dimensional soil water flow model) and then developed a standalone model that explicitly represents water-vapor transmission through the SBM. RESULTS/FINDINGS: Columns covered with BioWRAP lost significantly less water to evaporation and retained more soil moisture than bare-soil columns. HYDRUS-1D reproduced soil moisture dynamics well for both bare soil and SBM treatments. The standalone model closely matched observed soil moisture in bare soil and performed comparably to HYDRUS-1D. The modeling results clarify the role of SBM in suppressing soil evaporation and underscore the need for specialized frameworks that capture mulch–soil interactions. Our findings provide a foundation for optimizing biodegradable sprayable mulches in agricultural systems through modeling-guided design and management.

Presented by

Manavjot Singh

Institution

Kansas State University

Got Blue-Green Algae? But, is it Toxic? – Evaluating Reliability and Accuracy of Rapid Test Kits for Detection of Cyanotoxins

Laura Krueger, Dr. Trisha Moore, Dr. Aleksey Sheshukov

Abstract

Excessive growth of Cyanobacteria (also called Blue-Green Algae) can lead to Harmful Algal Blooms (HABs) that may produce harmful cyanotoxins, posing health risks to humans and animals. Bloom toxicity cannot be visually determined. Thus, quick and reliable detection methods are essential for minimizing toxin exposure. Several types of cyanotoxins may be present in a waterbody, but many HAB monitoring programs focus on one or two cyanotoxins due to analytical costs and time constraints. In Kansas, the Department of Health and Environment (KDHE) operates a complaint-based response program that monitors public recreational waterbodies for cyanobacteria and cyanotoxin microcystin. However, private waterbodies are not included in the statewide program leaving HAB monitoring and testing up to waterbody owners or managers’ discretion. Conventional cyanotoxin testing involves sending water samples to a diagnostic laboratory, such as the Kansas Veterinary Diagnostic Laboratory, for lab analyses such as the Enzyme Linked Immunosorbent Assay (ELISA). This process can take several days, delaying management responses. Commercially-available rapid test kits offer potential alternatives, though their application and accuracy are not well studied. This study evaluated the reliability and accuracy of two microcystin rapid test kits, 5 Strands and Eurofins-Abraxis. The variability in rapid kit application was explored, and kit results were compared to conventional cyanotoxin ELISA results. The study findings demonstrate that rapid test kits are practical tools for field detection of microcystin, offering quick qualitative results. However, interpretation can vary with user experience and sample conditions, and management decisions may still require conventional laboratory confirmation of toxin levels.

Presented by

Laura Krueger

Institution

Kansas State University

Closing the Water Budget Gap: Leveraging Satellite-Based Insights for Accurate Irrigation Water-Use Estimation Across Western U.S

Kelechi Igwe, Vaishali Sharda

Abstract

Accurately tracking how much water is used to grow crops is useful for managing and sustaining water resources, especially in water-limited regions like western Kansas where agriculture primarily depends on irrigation from groundwater reserves which is declining at a rate faster than its recharge. A current satellite-based system for monitoring crop water use is the OPENET platform. Although useful, there is significant lag between OPENET’s estimates of water use and annual irrigation withdrawals reported by the Water Information Management and Analysis System (WIMAS). This lag is likely due to the omission of critical components in OPENTET’s water budget calculations, such as the amount of moisture retained in the soil. This study aims to close this gap by integrating soil moisture observations from multiple satellite platforms into a machine learning-based soil water balance model. Soil moisture data from NASA’s Soil Moisture Active Passive (SMAP) mission, Western Land Data Assimilation System (WLDAS) and Optical Trapezoidal Model (OPTRAM) are each combined with precipitation data from GridMET and evapotranspiration data from OPENET’s Simplified Surface Energy Balance model for Operational Production of Evapotranspiration (SSEBOP) model. The results are annual estimates of irrigation water use from the ML model which are compared against WIMAS withdrawal reports to evaluate the model’s accuracy in predicting irrigation water use. By improving how we monitor irrigation water use, this research can guide and support informed decision-making for sustainable agricultural water resource management

Presented by

Kelechi Igwe

Institution

Kansas State University

Leveraging UAV Multispectral Imagery and Machine Learning for High- Throughput Phenotyping in Winter Wheat

Kaden Spencer, Dr. Romulo Pisa Lollato, Dr. Andres Patrignani and Dr. Deepak R Joshi

Abstract

High spatial and temporal resolution remote sensing imageries collected across diverse climatic regions paired with management practices are needed for robust and repeatable plot-scale phenotyping of winter wheat (Triticum aestivum L.). The main objective of this study was to assess the application of time series multispectral signature trajectories on in-season canopy growth and end-of-season grain protein and yield of winter wheat across different nitrogen (N) rates and cultivars. A field experiment was conducted across seven locations in Kansas representing diverse climatic regions (precipitation range 630–908 mm) with seven N rates and eight cultivars. At each site, multispectral UAV imagery was collected six times throughout the growing season, from early germination to mature pre-harvest stages, to compute ten vegetation indices (VIs). Temporal VI trajectories captured canopy development and nitrogen treatment responses with clear cultivar differences. Correlations of VIs with yield (r = 0.15–0.28) and grain protein (r = 0.19–0.25) were initially low early in the season but increased (r = 0.90–0.94 with yield; r = 0.85–0.92 with protein) as canopy coverage and growth progressed across N rates and cultivars. Using plot-level high temporal VIs, five machine learning models were developed; the multilayer perceptron (MLP) model achieved the highest yield prediction accuracy (R² = 0.89), while the Gaussian process regression (GPR) model achieved the highest protein prediction accuracy (R² = 0.64). These results demonstrate that multi-temporal multispectral features can capture yield potential and protein variability across N rates and cultivars, advancing highthroughput phenotyping in winter wheat.

Presented by

Kaden Spencer

Institution

Kansas State University

Crop Predictive Modeling of Changing Precipitation Dynamics in Western Kansas

Isaac Smith, Xuan Xu, Micah Cameron-Harp

Abstract

The Bartlett-Lewis Rectangular Pulse Model (Onof & Wang, 2020) is a stochastic framework for simulating rainfall intensity, accounting for the characteristics of individual rain cells and storm patterns through a Poisson cluster point process, including storm rate, cell rate, storm duration, cell duration, and cell intensity. Finney County, KS, located within the Ogallala Aquifer region and Groundwater Management District 3, was selected for this study due to its abundant historical crop data. Analysis of the past 40 years revealed a significant decrease in storm rates and an increase in storm cell duration, while annual precipitation remained unchanged. Using parameters generated from the model, we evaluated the impact of storm characteristics on multiple crop yields with Random Forest and Long Short-Term Memory (LSTM) networks. During training, Random Forest outperformed LSTM when modeling all crops together (RMSE = 3.860, R² = 0.937 vs. RMSE = 12.335, R² = 0.356). Both models showed decreased performance on the held-out test set, with LSTM losing most predictive power, whereas Random Forest maintained reasonable predictive ability (RMSE = 9.010, R² = 0.521). When modeling crops individually, both models captured winter wheat yields within 95% confidence intervals but struggled with sorghum and corn. These results indicate that Random Forest generalizes better under limited data conditions, a key consideration for regions with small datasets such as Finney County. Using simulated future parameters from the Bartlett-Lewis Model, we can use the Random Forest framework to forecast yield for Finney County and more.

Presented by

Isaac Smith

Institution

Kansas State University

Onsite Microplastic Testing Device for Kansas Water

Gwyneth VanLeeuwen, Scott Fan

Abstract

Micro- and nanoplastics are major environmental issues found in tap water, bottled water, ponds, and lakes, posing multiple ecological and physical health concerns. The available technology is minimal, with current technologies including Fourier Transform Infrared Spectroscopy (FTIR), Stimulated Raman Scattering, and very large microscopes. This technology is effective in analyzing microplastics, but it is complex, expensive, and not easily accessible. This research aims to combine a microfluidic chip with dielectrophoresis (DEP) to quantify, collect, and detect microplastics in Kansas water samples as an on-site testing device. A microfluidic chip will be designed and tested at various voltages and frequencies to generate movement within the droplet, called DEP. This method will manipulate the Polystyrene particles to condense on the patterned electrodes on the chip. Multiple patterns, frequencies, and voltages will be tested to optimize results. Voltages from 40-72 V and frequencies of 1-9 kHz were tested. Results showed that as the voltage increased, the particles concentrated more rapidly onto the patterned electrodes. The voltage and frequency that showed the highest concentration were 64 V and 1 kHz. This research will continue to explore pre-processing methods for large water samples, design new chip patterns, experiment with DEP and flow rate to sort other types of plastic particles, and test particle-detection approaches using an electric sensor.

Presented by

Gwyneth VanLeeuwen

Institution

Kansas State University

FHSU Western Kansas Regional Water Quality Study

Gunnar Wainscott, Jonothan Owusu, Connor Stanton, Abby Bird

Abstract

The project's objective is to evaluate the general quality of groundwater and surface water across western Kansas, southern Nebraska, and eastern Colorado. Water quality across the High Plains region is created by complex interactions between natural geology, agriculture, and climate. The quality of this resource is fundamental for irrigation, livestock, and domestic use, making the monitoring of water resources throughout the area crucial. This research will analyze the chemical composition of both groundwater and surface water samples collected from accessible land and participating landowners throughout the region. Field measurements, including pH and ORP, were taken on-site, and laboratory testing conducted for sixteen chemical parameters, including alkalinity, arsenic, lead, nitrate, and others. Preliminary results indicate that most samples fall within expected water quality ranges, though localized spikes in nitrate, lead, and arsenic warrant further investigation. Ongoing analysis aims to refine these findings to create a map of changing water quality parameters across the entire region of study, and promote broader participation in water testing to support sustainable resource management.

Presented by

Gunnar Wainscott

Institution

Fort Hays State University

Spatio-temporal trend of irrigation water pumping and its response to water conservation policy (LEMA) in Kansas

Govinda Khanal, Musabbir Turjo, Jeeban Panthi

Abstract

Groundwater depletion in western Kansas has accelerated over recent decades due to intensive irrigation from the Ogallala Aquifer, threatening agricultural and economic sustainability. To address this, Kansas implemented Locally Enhanced Management Areas (LEMAs) that promote community-driven reductions in groundwater use. This study examines the spatio-temporal dynamics of irrigation water pumping across Kansas from 1994 to 2023 using individual irrigation wells pumping data from the Kansas Geological Survey. Trend analysis was conducted using the Mann–Kendall test and Sen’s slope estimator, while policy impacts were quantified through a Difference-in-Differences (DiD) approach comparing treatment (LEMA) and control areas before and after implementation. Results show widespread declines in groundwater use across western Kansas, with decreasing trends most evident in major agricultural counties. The Sheridan County LEMA achieved a statistically significant reduction in pumping (~0.09 AF acre⁻¹ yr⁻¹, p = 0.04), demonstrating measurable water savings. Preliminary results from the Wichita County LEMA also indicate a downward trend (−0.05 AF acre⁻¹ yr⁻¹) though with limited statistical strength due to shorter records. Weather variability, especially growing-season precipitation, remains a key short-term driver of irrigation demand. Overall, findings highlight the effectiveness of local groundwater management programs and their potential to enhance long-term aquifer sustainability in Kansas.

Presented by

Govinda Khanal

Institution

Kansas State University

Mapping of High-Resolution Crop Evapotranspiration Using Fused Remote Sensing Imagery: Validation Against OpenET

Gloria Ramos, Vaishali Sharda

Abstract

Accurate estimation of crop evapotranspiration (ETa) is essential for ensuring sustainable agricultural productivity in response to escalating climate variability and water resource limitations. While remote sensing (RS) platforms, such as Unmanned Aerial Systems (e.g., UAVs) and satellites (e.g., PlanetScope), have emerged as powerful alternatives to overcome the challenges of traditional field-based methods, each platform presents distinct trade-offs. UAVs provide fine spatial detail but have limited coverage and are weather-dependent, while PlanetScope offers near-daily high temporal resolution and high scalability at coarser spatial resolution. The primary objective is to enhance the resolution of PlanetScope and bridge the observation gaps between UAV flights. Combining the spatial and temporal advantages of these data could yield products that enable more accurate ETa mapping by leveraging time-series continuous data with high spatial and temporal resolution. The Swin SpatioTemporal Fusion Model (SwinSTFM), which has demonstrated superior performance across various remote sensing fusion tasks, will be implemented for the data fusion. The fused imagery output is then integrated with meteorological data from nearby weather stations using the High-Resolution Mapping of Evapotranspiration (HRMET) model to generate high-resolution ETa maps. The generated maps are compared against the OpenET-METRIC data to evaluate the accuracy of the outputs. The results are improved RS images and high-resolution ETa time series maps that capture the highly nonlinear, day-to-day variability in crop water use. By combining advanced remote sensing, machine learning, and energy balance modeling approaches, this study provides detailed field-level information on time for precision irrigation management, particularly relevant in water-scarce regions.

Presented by

Gloria Ramos

Institution

Kansas State University

Farm ponds as nutrient modulators

Gift Manyonga, Amy Hansen, Edward Peltier

Abstract

Agricultural runoff is a major source of non-point pollution in Midwestern watersheds, contributing excess nitrogen and phosphorus to downstream water bodies such as Perry Lake, Kansas. These nutrient loads accelerate eutrophication, degrading aquatic ecosystems and reducing reservoir lifespan. Farm ponds, ubiquitous across agricultural landscapes, may function as natural bioreactors that intercept and transform nutrients before they reach larger water systems. This study investigates the nutrient-modulation capacity of 10 farm ponds within the Delaware River Watershed, representing varying land-use contexts: 5 with high agricultural intensity and 5 dominated by pasture. Synoptic sampling was conducted during an 8.2% exceedance probability rainfall event, with samples analyzed for nitrate (NO₃⁻), soluble reactive phosphorus (SRP), and total phosphorus (TP). Concentration-based removal efficiencies were calculated under steady-state assumptions. Preliminary results indicate that ponds in highly agricultural settings received higher nutrient loads but achieved greater nitrate reductions than those in pasture-dominated systems. Phosphorus responses were more variable, suggesting land use and hydrologic context play key roles in regulating P dynamics. These findings highlight the dual potential of farm ponds as nutrient sinks or sources depending on management and landscape setting. Ongoing work aims to integrate biotic indicators and hydrologic modeling to better quantify nutrient transformation processes and guide sustainable watershed management strategies.

Presented by

Gift Manyonga

Institution

University of Kansas

Mapping the Kansan Anthropocene at Hidinginplainssight.org

Georg N. Schaefer, Brian Holmes

Abstract

This project presents an interactive mapping platform that visualizes the long-term anthropocenic transformation of social and natural systems in western Kansas. Building on interdisciplinary research and archival work, the tool integrates land-use change, groundwater extraction, and agricultural infrastructure to trace how irrigation, feedlots, and industrial supply chains have reshaped the High Plains region since the mid-20th century.

The platform links public datasets—ranging from USGS and KGS well records to satellite-based land-cover data—with additional layers and case studies that highlight political and economic drivers, including Groundwater Management Districts, corporate ownership networks, and large-scale livestock and processing facilities. By situating biophysical change within its institutional context, the map seeks to support research, public understanding, and informed discussion about the future of water in Kansas.

Presented by

George N. Schaffer

Institution

Max Planck Institute of Geoanthropology, Germany

Urban Tree Transpiration in the Context of Urban Runoff Reduction

Forough Torabi, Alireza Monavarian, Alireza Nooraei Beidokhti, Vaishali Sharda, Trisha Moore

Abstract

Urban trees are increasingly viewed as nature-based infrastructure to manage stormwater, yet quantitative guidance on how species traits and site context shape transpiration remains fragmented. We conducted a systematic metadata analysis of urban tree transpiration studies with the objective of synthesizing existing data on the effects of wood anatomy, soil type, and planting configuration on individual tree transpiration. A comprehensive literature search was conducted to identify field studies using comparable heat-pulse methods to measure daily tree transpiration in urban settings. The reported scale and units of measure from the resulting seven studies were harmonized to units of sap flow density across the active sapwood (Js, g H2O/m²/s) by converting reported stand transpiration and the outer two cm of sapwood sap flux to the complete sapwood with established radial functions for angiosperms and gymnosperms. We then summarized distributions of daily sap flux and tested for differences with Kruskal–Wallis and Dunn post-hoc comparisons among groupings by wood anatomy, soil texture, and planting configuration. Conifers exhibited significantly lower Js than angiosperms, while the ring-porous and diffuse-porous groups had similar distributions overall. Soil texture effects were consistent with expected moisture availability: Js was generally lower in sandy loam soils relative to loam or silt loam for conifers and diffuse-porous species. Across wood anatomies, single trees planted in isolation transpired more than clustered trees or closed canopies. These results provide actionable ranges and contrasts to inform species selection and planting design for urban greening and runoff reduction, while highlighting data gaps for future research.

Presented by

Forough Torabi

Institution

Kansas State University

Flood History and Future Flood Prediction of Big Creek, Hays (Kansas)

Fama Dia

Abstract

Flooding is one of the most frequent and damaging natural hazards around the world. In small river systems like Big Creek in Hays, Kansas, that flows next to the FHSU campus, it is particularly vulnerable to intense rainfall events causing floods. Understanding the frequency of such flood events is vital for developing effective local mitigation strategies. In recent years, the High Plains region has experienced increased variability in precipitation and more frequent extreme weather events. Combined with land-use changes, such as urban expansion near floodplains, these factors have amplified surface runoff and flood potential in the Big Creek watershed.

Major floods in Hays occurred in 1947,1951, 1957, 1965, 1993 and 2019 with discharge peaks often exceeding 70cfs, The 1951 flood remains one of the highest historical peaks, causing widespread inundation around FHSU area With a discharge of 238.2 cfs ( cubic feet per second) The latest flood event that occurred was in 2019 with a discharge of 110 cfs ( cubic feet per second) . However, the variability of rainfall makes the occurrence of the next flood uncertain. By analyzing previous discharge data, we to predict future flood event in order to anticipate and better prepare for it.

In this study, we will examine flood events between 1947 and 2024 by organizing discharge data from this period, identifying the recurrence intervals of significant floods, and generating a flood frequency curve. The flood frequency curve will help us predict future flood occurrences around the university, allowing for better event planning and improved mitigation strategies.

Presented by

Fama Dia

Institution

Fort Hays State University

Aquatic communities in Kickapoo Ponds, Trophic Status, Algae, Zooplankton

Evan La Cour, Ted Harris, Chris Frazier, Rachel Bowes

Abstract

Sustaining healthy aquatic ecosystems is critical for supporting cultural well-being, food sovereignty, and local resource management for the Kickapoo Tribe of Kansas. Community members have recently reported fish deformities in reservation ponds, prompting concerns about whether these systems remain safe and reliable sources of subsistence and recreational fishing. To provide a scientifically informed foundation for Tribal decision-making, this study investigates water quality, trophic structure, and fish health in two high-priority ponds—Dog Pond and Picnic Pond—across spring and fall sampling periods.

Field methods included YSI multiprobe profiling of temperature, dissolved oxygen, and pH; nutrient analysis of discrete water samples; characterization of algal biomass using a bbe-Fluoroprobe; and zooplankton community assessments through net hauls and microscopic identification. Fish communities were evaluated using electroshocking surveys, followed by measurements of species composition, size structure, and external condition metrics.

Both ponds exhibited mesotrophic nutrient concentrations and seasonal stratification. Dog Pond consistently supported higher phytoplankton biomass, and its bluegill population appeared skewed toward smaller individuals, while Picnic Pond displayed a more even size distribution. Across both systems, observations of fin deformities and black spot disease suggest underlying ecological stressors.

These early findings warrant further investigation into contaminant pathways and parasite dynamics. Continued collaboration with the Kickapoo Tribe will guide management approaches that protect fish safety, improve ecological resilience, and uphold Tribal fishing traditions essential to cultural identity and long-term food sovereignty.

Presented by

Evan La Cour

Institution

University of Kansas

How Does Woody Plant Encroachment Impact Soil Water Chemistry and Hydraulic Conductivity?

Emma Tyndall, Saranya Puthalath, Jesse Nippert

Abstract

Woody plant encroachment (WPE) threatens the sustainability of Kansas rangelands and native grasslands. WPE can alter all aspects of the hydrological cycle, including infiltration, evaporation, and groundwater recharge. Here, we used a Mini Disk Infiltrometer to measure the rate at which water flows through the soil in unsaturated conditions. Our goal was to determine whether woody plants are changing water infiltration rates in prairie soils. At Konza Prairie Biological Station, I conducted four mini-disk infiltrometer runs at 14 experimental shelters. Shelters 1–7 are burned annually, while shelters 8–14 are burned every four years, enabling comparison of infiltration under different fire regimes to study the effects of woody encroachment. I did tests in the grassy area and in the shrubby area measuring the pressure at four different tensions: -6, -4, -2, and -0.5. For each tension, I measured the water infiltration for an average of 10 minutes. At Konza prairie, woody encroachment alters soil infiltration rates, which are critical in determining water availability to native grasses, influencing soil moisture dynamics and regulating groundwater recharge. We found that grassy vegetation exhibits higher mean K values than shrubby vegetation, with statistically significant differences observed at tensions of -4 and –2, grass soils conducting more water. Previous studies indicate WPE enhances K through deeper root systems, but this study focused on the surface layer where both woody and grassy roots are abundant.

Presented by

Emma Tyndall

Institution

Kansas State University

Potential of Eggshell Nanoparticles as a Natural Pesticide Against the Red Flour Beetle

Charlie Gumienny, Audrey Empkey, Michael Aikins, Amie Norton, and Thomas Phillips

Abstract

Agricultural waste management presents a growing environmental and economic challenge, with the United States producing approximately six billion kilograms of eggshell waste each year—ranked by the EPA as the fifteenth most significant food-related pollutant. Eggshells are composed primarily of calcium carbonate (CaCO₃), a benign and mineral-rich material suitable for reuse. By applying nanotechnology, eggshell waste can be converted into CaCO₃ nanoparticles with enhanced surface area and reactivity, transforming a disposal burden into a high-value agricultural input. Objective: This study aims to develop and evaluate CaCO₃ nanoparticles derived from eggshell waste as a natural, sustainable, and effective control method for Tribolium castaneum (red flour beetle), a major pest of stored grains and milled products. The approach integrates nanomilling optimization, particle characterization (size, zeta potential, morphology), and bioassays to assess efficacy against adult and larval beetles under storage-relevant conditions. Impact and Relevance: Converting eggshell waste into functional nanoparticles represents a circular, low-carbon innovation that addresses multiple sustainability goals: reducing food industry waste, reducing reliance on chemical pesticides, and enhancing the resilience of grain storage systems. As pesticide resistance increases and fumigant options decline, this natural nanoparticle approach offers a safe, biodegradable, and cost-effective alternative for producers and millers. Broader adoption could reduce landfill waste streams and support integrated pest management strategies aligned with agricultural water, food security, and environmental stewardship priorities.

Presented by

Charlie Gumienny

Institution

Kansas State University

Event-driven shifts in river and reservoir sediment sources: Cottonwood River and John Redmond Reservoir, USA

Cayden Lloyd, Anthony L. Layzell, Abigail Percich, Ted D. Harris, Michael Ketterer, Admin Husic

Abstract

Reservoir sedimentation is a global issue. In the United States, reservoir storage capacity over the past 30 years has continually declined due to sedimentation and, in Kansas, multiple large reservoirs are expected to become more than 50% infilled over the coming decades. Regionally, it is understood that streambank erosion is the main source of sediment to downstream reservoirs. Hence, streambank stabilization projects have received considerable attention as a management solution. Here, we conduct a sediment fingerprinting study to identify the relative contribution of streambank, cropland, and grassland sediment sources to the Cottonwood River and John Redmond Reservoir. We collected three types of samples, representing various flow intensities.

Lakebed sediment is most representative of material transported during large, infrequent flood events and our results indicate that this sediment is primarily derived from cropland sources (40%) not streambanks (29%). Discrete sampling of moderately sized storm events, which occur multiple times per year, indicated a drop in the relative proportion of cropland sediment (36%) and an increase in bank material (35%). Time-integrated traps, which collect sediment during storm events as well as low-flow periods, were found to have the lowest cropland (30%) and greatest bank (47%) contributions.

The shift from in-channel bank-dominated sourcing, for time-integrated traps, to cropland-dominated sediment sourcing, for lakebed material, reflects the enhanced connectivity of upland sources during high-magnitude, out-of-bank floods. In particular, the valley floor of the Cottonwood River is heavily cultivated, thus cropland sediment is likely entrained from floodplain chutes that create erosional pathways during out-of-bank events.

Presented by

Cayden Lloyd

Institution

University of Kansas

Analyzing Nitrate Pollution in Domestic Wells Across Western Kansas

Carter Will, Augustus Peine, Jeanne Sumrall, Richard Lisichenko

Abstract

Rural homes across Western Kansas have historically relied on the use of well water for drinking. These wells draw upon many different sources of water but usually remain relatively shallow at less than 100 feet (Buchanan et al., 2023). Domestic wells typically draw from alluvial aquifers, but some may tap into the Ogallala or Dakota aquifer at much greater depths, ~400 feet or less (Buchanan et al., 2023), or ~2,000 feet or less, respectively (Macfarlane, 1995). To access these sources, wells are drilled into various rock layers. These range from the unconsolidated sand and gravel of the alluvial and Ogallala aquifers to the deeper sandstone formations of the Dakota aquifer (Buchanan et al., 2023). These domestic wells are privately owned and thus are not subject to routine tests and regulations like public water systems. This  leads to an increased risk of unknown contamination. Common potential contaminants include nitrates, which routinely get into wells through septic systems and agricultural drainage (Young & Townsend, 1999). High levels of nitrates can cause serious health defects, especially to young children and pregnant women (Sedgwick County Health Department, n.d.). Solving this issue requires regular testing of the water, better management of the land around the well, and an increase in public knowledge. To stop the potential harmful effects of excess dissolved nitrates, well owners must understand the danger nitrates pose and implement regular water testing habits, filtration systems, or alternate sources of clean, safe drinking water.

Presented by

Carter Will

Institution

Fort Hays State University

Irrigation Impacts on Future Groundwater Levels in the Kansas River Alluvial Aquifer

Camden Hatley, Erin Seybold, Sam Zipper

Abstract

In the coming decades, irrigated agriculture may expand across the Kansas River Alluvial Aquifer as an adaptation to an aridifying climate. To understand the potential consequences of this on future groundwater availability, we modeled groundwater levels at five locations across the aquifer using transfer function-noise models, which are able to separately simulate the individual impacts of recharge and irrigation on groundwater. Models (test KGE = 0.65-0.96) indicate that the impact of irrigation on groundwater levels varies by location but is consistently less than the impact of recharge. Variance of irrigation impact across locations is not explained by the amount of irrigation pumping that occurs near each site, but by local geologic conditions with coarser sediments reducing irrigation impact. Groundwater models at each location were projected to year 2099 using an ensemble of global climate models (RCPs 4.5 and 8.5) and irrigation inputs based on current irrigation-climate relationships. No significant trends in groundwater levels were predicted for any location or climate scenario. The lack of significant trends was produced in the models by a balance of trends in irrigation and recharge impacts. While irrigation impacts had significant negative trends in many locations, they were offset by significant positive trends in recharge impacts. Given that irrigation projections used current irrigation-climate relationships, any changes to these relationships (e.g. irrigation expansion throughout the aquifer) could alter the balance between irrigation and recharge impacts and lead to long-term declines in groundwater levels. Areas with low-conductivity sediments may be particularly sensitive to any such changes.

Presented by

Camden Hatley

Institution

University of Kansas

Analyzing Nitrate Pollution in Domestic Wells Across Western Kansas

Augustus Peine, Carter Will, Jeanne Sumrall, Richard Lisichenko

Abstract

Rural homes across Western Kansas have historically relied on the use of well water for drinking. These wells draw upon many different sources of water but usually remain relatively shallow at less than 100 feet (Buchanan et al., 2023). Domestic wells typically draw from alluvial aquifers, but some may tap into the Ogallala or Dakota aquifer at much greater depths, ~400 feet or less (Buchanan et al., 2023), or ~2,000 feet or less, respectively (Macfarlane, 1995). To access these sources, wells are drilled into various rock layers. These range from the unconsolidated sand and gravel of the alluvial and Ogallala aquifers to the deeper sandstone formations of the Dakota aquifer (Buchanan et al., 2023). These domestic wells are privately owned and thus are not subject to routine tests and regulations like public water systems. This leads to an increased risk of unknown contamination. Common potential contaminants include nitrates, which routinely get into wells through septic systems and agricultural drainage (Young & Townsend, 1999). High levels of nitrates can cause serious health defects, especially to young children and pregnant women (Sedgwick County Health Department, n.d.). Solving this issue requires regular testing of the water, better management of the land around the well, and an increase in public knowledge. To stop the potential harmful effects of excess dissolved nitrates, well owners must understand the danger nitrates pose and implement regular water testing habits, filtration systems, or alternate sources of clean, safe drinking water.

Presented by

Augustus Peine

Institution

Fort Hays State University

Detection of Nitrate and Nitrite using a Micro Silica Sensor

Audrey Empkey, Amie Norton

Abstract

Nitrate and nitrite contamination in drinking and surface waters pose critical public health and environmental challenges. Elevated levels of these anions are linked to methemoglobinemia (“blue baby syndrome”) and increased gastric cancer risk in elderly humans. Environmentally, nitrate and nitrite contribute to eutrophication, algal blooms, and soil acidification, disrupting aquatic ecosystems and agricultural productivity. Major sources of nitrate include agricultural fertilizer runoff, livestock operations, and industrial discharge. Current U.S. Environmental Protection Agency (EPA) analytical methods for nitrate and nitrite rely on laboratory-based instrumentation that requires complex sample preparation, trained personnel, and significant turnaround times. This project proposes a proof-of-concept for a portable, low-cost, and rapid colorimetric sensor that integrates the Griess reagent with a vanadium(III) reduction step immobilized on a porous silica substrate. The Griess+V(III) platform enables sequential detection of both nitrite and nitrate under ambient field conditions without the need for laboratory instrumentation. Silica immobilization enhances reagent stability and reproducibility. The anticipated outcome is a deployable in-field sensor for real-time water quality monitoring. This innovation could significantly improve response times in agricultural and municipal water testing programs, strengthen nitrate management strategies, and help safeguard drinking water quality and environmental health across rural and agricultural regions.

Presented by

Audrey Empkey

Institution

Kansas State University

The Ultimate Future of Wastewater Treatment: Harnessing nature’s remedy to Tackle the Untreatable

Asmita Mahara, Mark Wilkins

Abstract

Hydrothermal liquefaction wastewater (HTCWW), a toxic by-product from biofuel production industries that is rich in recalcitrant organics and nitrogenous compounds, poses a major bottleneck for the industrial-scale implementation of hydrothermal liquefaction, as its poor biodegradability demands specialized treatment strategies. In this study, three HTCWWs derived from coconut shell, walnut shell, and pasta were biologically treated at dilution factors of 10X, 8X, and 6X, respectively. Individual microbial organisms (fungi and protists) were first evaluated under marine conditions, where fungi exhibited robust growth and achieved over 50% chemical oxygen demand (COD) removal within 12 days, while protists alone failed to establish growth. To enhance treatment efficiency, combinations of fungi and marine protists were tested. The consortium of Aspergillus terreus, Schizochytrium sp. ATCC 20888, and Thraustochytrium striatum demonstrated the highest COD reduction, achieving up to 79% in coconut shell, 71% in walnut shell, and 57% in pasta HTCWW. Fermentation optimization revealed that nitrogen, phosphorus, and iron were critical nutrients, while glucose supplementation supported initial microbial growth without influencing overall COD removal. Notably, inhibitory compounds such as phenol, furfural, and catechol were reduced to near zero, with unidentified peaks in HPLC chromatograms declining by over 90%. Biomass accumulation reached 3.7 g/L, and the harvested biomass remained viable in sterile water for sequential batch fermentation. These findings highlight the potential of fungal-protist consortia as an effective biological treatment strategy for detoxifying HTCWW while simultaneously generating biomass for future applications.

Presented by

Asmita Mahara

Institution

Kansas State University

ROOTS, BACTERIA, AND WATER: A SUSTAINABLE WAY TO HELP SOIL HOLD WATER

Asad Zaman, Moises Gutierrez, Silvio Liu, and Ryan Hansen

Abstract

The Ogallala Aquifer, which is essential for Kansas agriculture, faces a severe threat: we're using its water much faster than nature can refill it. This non-renewable resource has dropped by an enormous volume since 1935, jeopardizing the future of irrigation and farming in the state. One promising approach to extending water availability is to conserve soil moisture by minimizing evaporation. A significant barrier to this strategy is soil water repellency, which limits how efficiently soils absorb and hold water. Surfactin—a natural surfactant produced by Bacillus subtilis—offers a sustainable solution. Surfactin helps soils stay wet, reduce evaporation, and even supports healthier plants by fighting disease, triggering plant defenses, and helping beneficial bacteria stick to roots. The research shows that the nitrogen-based fertilizer farmers already use to feed their crops also help to boost the growth of B. subtilis and Surfactin production. Furthermore, plants naturally release root exudates in soil that feed bacteria. Interestingly, when plants experience mild drought stress, they release exudate more, which in turn accelerates the growth of the bacteria and the synthesis of Surfactin. By strategically combining standard fertilizer with a reduced irrigation schedule, we can create a powerful natural cycle, which can enhance the soil's ability to hold water right around the plant roots, reduce drought stress, and enhance the plant's natural defense system.

Presented by

Asad Zaman

Institution

Kansas State University

Hybrid AI Framework for Soil Moisture Forecasting: Towards Sustainable Water Use in Agriculture

Amirsalar Bagheri, Davood Pourkargar

Abstract

Efficient agricultural water depends on accurate prediction of soil water content (SWC), a key driver of irrigation scheduling and drought resilience. Traditional physics-based models, such as the Richards equation, are often computationally intensive and require detailed soil characterization, while purely data-driven approaches may struggle to generalize under shifting environmental and climatic conditions. This study introduces a hybrid time-series and physics-informed machine learning framework that integrates hydrological modeling with artificial intelligence to improve SWC forecasting. Using Kansas Mesonet data from 45 monitoring stations, two complementary strategies were developed: (1) a hybrid uncertainty quantification (UQ) approach, in which machine learning models learn the residuals between a modified antecedent precipitation index (API) model and observed SWC; and (2) physics-informed neural networks (PINNs) that embed soil-water balance equations directly into the training objective. Across all stations, the hybrid and physics-informed models consistently outperformed standalone hydrological and purely data-driven baselines, yielding lower normalized root-mean-square errors (NRMSEs) and reduced biases. The LSTM-based hybrid model provided the most accurate forecasts, effectively capturing nonlinear and temporal dependencies while remaining aligned with physical constraints. The resulting framework offers a scalable and adaptive solution for real-time soil moisture prediction, enabling more innovative irrigation scheduling, reduced groundwater extraction, and improved resilience to drought.

Presented by

Amirsalar Bagheri

Institution

Kansas State University

Efficient Water Use: Utilizing Water Captured by an Alternative Forage - Failed Wheat/Kochia/Palmer Amaranth

Adam King, Dr. Keith Harmoney, Dr. Jim Drouillard, Dr. Emma Briggs

Abstract

In 2023, 29% of Kansas wheat fields were unharvested, leaving 2.35 million acres of abandoned fields (USDA-NASS, 2024) infested with invasive species. This study evaluated whether failed wheat with kochia and Palmer amaranth could serve as forage for finishing rations in the Great Plains. Treatments contained failed wheat/kochia (WHT-KCHA) and sorghum-sudan (SOR-SUD; control), fed at 7% of the diet for 148 days. Angus cross steers [n = 300; body weight (BW) = 833 lbs ± 22 lbs] were housed in 20 pens with 10 pens per treatment. Data were analyzed in SAS 9.4 using MIXED procedure for intake, gain, and carcass data, and GLIMMIX for liver abscesses. No differences were found for BW, hot carcass weight, dressing percentage, marbling, ribeye area, yield grade, or liver scores. Early average daily gain (ADG; P = 0.011) was 0.2 lbs/head higher for WHT-KCHA, while late ADG (P ≤ 0.001) was 0.45 lbs/head higher for SOR-SUD. Total ADG (P = 0.036) was 0.1 lbs/head higher in SOR-SUD. Daily dry matter intake (DMI; P ≤ 0.001) was 1 lb/head higher for SOR-SUD. Early feed-to-gain ratio (F:G; P = 0.005) was 0.28 higher for SOR-SUD, while WHT-KCHA had 0.34 higher late F:G (P = 0.027). Total F:G was similar across whole feeding period. While WHT-KCHA showed some slight variations in ADG and DMI, overall F:G and carcass performance were comparable. Water captured by growth of weedy species in failed crop rotations may still be useful to add protein and value to animal agriculture.

Presented by

Adam King <adamking@ksu.edu>

Institution

Kansas State University

THE FUTURE OF CORN IN KANSAS MAPPING HOW CHANGING WEATHER WILL SHAPE OUR HARVESTS

Alireza Monavarian, Vaishali Sharda

Abstract

Corn is a cornerstone of global food security, but its production is increasingly threatened by future climate conditions, through altered temperature and precipitation patterns. While large-scale models of crop suitability exist, there is a critical need for high-resolution analysis focused on key agricultural regions like Kansas, tracking suitability changes across multiple future periods and climate scenarios. This study addresses this gap by forecasting corn cultivation suitability across Kansas for mid-century and late-century under two distinct Shared Socioeconomic Pathways (SSPs). We employed a presence-only Maximum Entropy (MaxEnt) modeling approach, correlating known corn occurrence data with high-resolution bioclimatic variables from the CHELSA dataset to predict suitable cultivation regions. Our model identifies shifts in the geographic distribution of suitable cultivation areas. We further pinpoint the primary bioclimatic variables that will limit future production. The resulting spatially explicit suitability maps provide a vital tool for regional stakeholders, aiding in the development of targeted climate adaptation strategies—including irrigation planning and crop diversification—to ensure the long-term sustainability of corn farming in Kansas. Our model uses precipitation as a primary variable to forecast shifts in crop suitability, effectively mapping future agricultural drought vulnerability across the state. The resulting suitability maps are intended as a key tool for "irrigation planning", a critical component of groundwater management and water utility strategy. By identifying where cultivation suitability will decline due to moisture stress, this study provides actionable data for stakeholders managing Kansas's vital groundwater resources, such as the Ogallala Aquifer, ensuring that agricultural water use remains sustainable under future climate stress.

Presented by

Alireza Monavarian

Institution

Kansas State University

Rule Mining for Deoxygenation in Non-Perennial Kansas Catchments

Alexi Sommerville, Erin C. Seybold, Kristin L. Underwood, Donna Rizzo

Abstract

Dissolved oxygen (DO) is a key indicator of stream ecosystem health and biogeochemical activity, yet predicting DO dynamics in non-perennial streams remains difficult due to their alternating wet and dry phases. This study applies a machine learning-driven evolutionary computation approach to identify the dominant hydrologic and climatological controls on DO variability in intermittent catchments. TEVA evolves human-interpretable rules using conjunctive and disjunctive logic to uncover multiple, coexisting pathways leading to hypoxic and oxic conditions. Results reveal that hypoxic states are consistently governed by hydrologic controls, particularly low discharge, reduced velocity, and increased groundwater influence, highlighting flow connectivity as a central driver of oxygen depletion. In contrast, oxic states emerge through more diverse processes, including high water velocity sustaining reaeration or strong photosynthetically active radiation (PAR) supporting oxygen replenishment via primary production. These findings demonstrate clear equifinality among oxygenation drivers, emphasizing that maintaining flow continuity alone is not always sufficient for recovery. Integrating TEVA-derived features into DO forecasting frameworks may provide an interpretable and scalable method for anticipating low-oxygen events, offering practical value for watershed monitoring, restoration design, and adaptive water quality management in increasingly intermittent systems.

Presented by

Alexi Sommerville

Institution

University of Kansas

How macrophyte beds in a shallow freshwater system influence diel vertical and horizontal migration of mesozooplankton taxa

Alexandra Coveney, Ted Harris, Christopher Frazier

Abstract

Zooplankton are indicators of water quality, informing researchers of the link between algal abundance and fish predation. While previous studies have investigated the influence of macrophyte beds on mesozooplantkon diel migration (3,5,6), few studies have been conducted in small waterbodies, despite their importance in our ecosystems. Being the most abundant freshwater environment, small waterbodies play an important role in maintaining biodiversity, water quality, and carbon cycling (2). The goal of this project is to determine the primary diel migration pattern of different mesozooplankton taxa in Arrowhead Pond, a 0.5-to-2-meter freshwater pond located at the University of Kansas Field Station (KUFS). Mesozooplankton samples were collected in periods of ample light (noon) and no light (midnight) (1) to examine whether macrophyte beds, present in the littoral zone of Arrowhead Pond, are utilized as shade and refuge for mesozooplankton taxa from visual predation. Samples were also taken across both littoral and limnetic zones of the pond and different seasons to explore whether migration patterns shift spatially and with seasonal conditions. My findings indicate that the abundance of taxa for noon versus night samples is statistically different for March (p=0.02) and July (p=0.003). We found more mesozooplankton per site in the summer (July 2025) and substantially more migration during the summer given proportionally more taxa were observed at night. My findings contribute to expanding our understanding of zooplankton habitat preference and migration patterns in a shallow pond system, improving the accuracy of assessments linking habitat conditions, algal abundance, and fish vitality in small waterbodies.

Presented by

Alexandra Coveney

Institution

University of Kansas