The Kansas Water Institute is proud to support innovative research faculty from different universities in Kansas. Using funds awarded by USGS from the Water Resources Research Act, KWI supports 2-year projects that focus on high-priority water topics identified by the Kansas state water plan. These projects put a special emphasis on the work of early-career scientists and funding for student research (both graduate and undergraduate). Take a look at the KWI info sheet for more information about how we ensure that Kansas water is our focus.
Funding opportunities with KWI/next-gen/key-initiatives/interdisciplinary-institutes/water-institute/funding/index.html
Investigating management techniques for irrigation with contaminated waters in the closed-basin Arkansas River region of western Kansas
In arid western Kansas, water is a limited resource. In the face of this, some agricultural systems irrigate with contaminated waters that can negatively affect the land. This study is working to assess the impacts of different levels of irrigation water contamination on corn production and exploring different management methods. These include extra water applications to a crop to maintain appropriate salinity in the root zone, or irrigating several times daily rather than all at once. The team used special devices to measure water movement in the soil to test different approaches to these methods. This is an ongoing study and the research team hopes to present final recommendations after year 2.
Herbal medicine for sick ponds: Are native aquatic macrophytes a cheap and easy way to mitigate HABs?
This project examines the potential for native aquatic plants to control harmful algal blooms. At the University of Kansas Biological Field station, the team created cyanobacteria blooms in large fiberglass tanks into which they launched floating islands containing 20 plants of either arrow leaf, mud plantain, or water primrose. The team are examining the resulting water quality and how the algal blooms respond on a weekly basis. Results of this two-year project are preliminary but intriguing; some tanks with aquatic plants did have lower algae concentrations. Over the next year, the team will continue to collect data from all water samples and to run statistical analysis on the results.
Unraveling spatiotemporal patterns in watershed nutrient and sediment loads under conditions of ongoing rapid crop conversion using direct sampling and remote sensing observations
Northeastern Kansas is rapidly converting land use from grassland to corn-soybean rotation, but the effects on sediment and nutrient loads to rivers and reservoirs in the region is unknown. This project hopes to identify the conditions under which land use conversion has resulted in higher nutrient and sediment loads and will track how this might affect streambank erosion in northeastern Kansas. The research team is using a combination of direct water sampling, geospatial data analysis and remote sensing data for the Delaware River watershed to answer these questions. This knowledge can help to protect water quality and reservoir storage by directing management interventions to the locations that are most stressed by land conversion patterns.
Forecasting streamflow and groundwater depletion with deep learning models to sustain Kansan water resources
This project will develop improved methods for estimating groundwater and surface water depletion to improve the sustainability of Kansas water resources. The project has three objectives: the first is to use already existing models to simulate groundwater and streamflow depletion. After this, the team will develop and benchmark deep-learning models of groundwater and streamflow depletion. These will predict future groundwater and streamflow depletion by forecasting climate and water demand scenarios into the deep learning model. This project aims to create accurate forecasts of groundwater and streamflow depletion under different climate and management scenarios, including “business-as-usual”, groundwater conservation, and groundwater exploitation.
Water Resources Research Act Program National Competitve Grants
This competitive grant program focuses on water problems and issues of a regional or interstate nature beyond those of concern only to a single state and which relate to specific program priorities identified jointly by the U.S. Secretary of the Interior and the Water Resources Research Institutes. KWI currently supports two projects funded under these grants.
Integrated data science: mechanistic modeling framework to predict cyanoHABS in contrasting freshwater systems
Harmful algal blooms (HABs) are increasing in frequency all over Kansas and can pose health risks for people, pets, livestock, and wildlife in Kansas. Although scientists understand some of the underlying causes of, it’s not possible to predict when and where they will occur. The overall goal of this project is to develop a flexible modeling framework for predicting HABs, as well as to give insight to how toxic blooms form. The research team is collecting observational cyanoHAB monitoring data from two different freshwater systems and using this to develop models to predict cyanoHAB occurrences.
Mapping and modeling of interbasin water transfers within the United States
Do you ever wonder how water travels, and where it goes? The primary goal of this research is to advance understanding of the role interbasin water transfers (IBTs) play in shaping water availability across the nation. This project will create a centralized, publicly accessible database and visualization of IBTs within the United States and harness this data to understand the impact of IBTs on society and the environment. Results from this project will help explain how IBTs impact water resources model how these impacts may evolve under changing climate, population shifts, and land use changes.
In arid western Kansas, water is a limited resource. In the face of this, some agricultural systems irrigate with contaminated waters that can negatively affect the land. This study is working to assess the impacts of different levels of irrigation water contamination on corn production and exploring different management methods. These include extra water applications to a crop to maintain appropriate salinity in the root zone, or irrigating several times daily rather than all at once. The team used special devices to measure water movement in the soil to test different approaches to these methods. This is an ongoing study and the research team hopes to present final recommendations after year 2.
This project examines the potential for native aquatic plants to control harmful algal blooms. At the University of Kansas Biological Field station, the team created cyanobacteria blooms in large fiberglass tanks into which they launched floating islands containing 20 plants of either arrow leaf, mud plantain, or water primrose. The team are examining the resulting water quality and how the algal blooms respond on a weekly basis. Results of this two-year project are preliminary but intriguing; some tanks with aquatic plants did have lower algae concentrations. Over the next year, the team will continue to collect data from all water samples and to run statistical analysis on the results.
Northeastern Kansas is rapidly converting land use from grassland to corn-soybean rotation, but the effects on sediment and nutrient loads to rivers and reservoirs in the region is unknown. This project hopes to identify the conditions under which land use conversion has resulted in higher nutrient and sediment loads and will track how this might affect streambank erosion in northeastern Kansas. The research team is using a combination of direct water sampling, geospatial data analysis and remote sensing data for the Delaware River watershed to answer these questions. This knowledge can help to protect water quality and reservoir storage by directing management interventions to the locations that are most stressed by land conversion patterns.
Harmful algal blooms (HABs) are increasing in frequency all over Kansas and can pose health risks for people, pets, livestock, and wildlife in Kansas. Although scientists understand some of the underlying causes of, it’s not possible to predict when and where they will occur. The overall goal of this project is to develop a flexible modeling framework for predicting HABs, as well as to give insight to how toxic blooms form. The research team is collecting observational cyanoHAB monitoring data from two different freshwater systems and using this to develop models to predict cyanoHAB occurrences.