Water Resources Research Act (WRRA)
The Water Resources Research Act Program is a Federal-State partnership that plans, facilitates, and conducts research that helps resolve State and regional water problems; promotes technology transfer; promotes dissemination and application of research; trains scientists through participation in research; and awards competitive grants under the Water Resources Research Act.
Annual Base Grants
Water-use efficient sorghum development for Kansas through high-throughput molecular marker discovery and deployment
This project focuses on creating and refining sorghum varieties that conserve soil moisture and enhance crop production in drought-prone Kansas. By identifying and developing high-throughput molecular markers associated with water-regulation genes, the research team will ensure reliable application across various breeding programs. The project aligns with the Kansas Water Plan's goals to conserve the High Plains Aquifer and reduce vulnerability to extreme events. Specific objectives are to advance water-use efficient entries of the DropXL population, develop stable molecular markers, and validate these markers in diverse breeding populations.
PI: Terry Felderhoff, Department of Agronomy, Kansas State University
Playa recharge characterization by nuclear magnetic resonance profiling
The High Plains aquifer in Kansas has received more water recharge than previously thought. A possible explanation for this larger-than-expected recharge is the widespread presence of playas in western Kansas that may produce significant capture of surface runoff during precipitation events. This project will use a newly developed field method, nuclear magnetic resonance (NMR) profiling, to estimate recharge rates under playas. NMR can accurately measure how much water is present and how that water is distributed among underground materials of different grain sizes. Results from this project will improve groundwater management and support better policy decisions regarding irrigated agriculture and other groundwater-dependent activities in the High Plains region.
PI: Gaisheng Liu, Kansas Geological Survey, University of Kansas
Optimizing variety maturity and deficit-irrigation strategy for thermally-limited cotton production in Kansas
Because of declining water supplies for irrigation in southwest Kansas and the High Plains, many producers are reassessing their crop selection for their irrigated acreage. Cotton may be a good drought tolerant alternative crop for the region. However, improved recommendations are needs for pairing variety maturity class to deficit irrigation strategy. Because early varieties are more determinant in their growth habit, they may not be as tolerant of delayed irrigation as more indeterminant early-medium varieties. The objective is to determine the effect of variety maturity selection and deficit irrigation strategy on seed and lint yield, lint quality, and yield formation factors on the northern edge of the Cotton Belt.
PI: Logan Simon, Southwest Research-Extension Center, Kansas State University
Early detection of harmful algal blooms in Kansas lakes and reservoirs using satellite remote sensing
Harmful Algal Blooms (HABs) are common worldwide, threatening water ecosystems, public health, and the economy. Kansas lakes and reservoirs are especially affected due to high nutrient levels from agricultural runoff, wastewater discharges, urban growth, and worsened by hot summers and heavy rains. Existing remote sensing methods for detecting algae do not work well in Kansas' murky waters. This project aims to develop a model using satellite data and mathematical models to estimate chlorophyll levels, a sign of HABs. This will help detect harmful blooms early, improving understanding and management of these events by state agencies.
PI: Jeeban Panthi, Department of Biological and Agricultural Engineering, Kansas State University
National Competitve Grants
USGS also funds national competitive grants as part of WRRA. There are three types of 104(g) grants: general, aquatic invasive species (AIS), and per-and polyfluoroalky substances (PFAS).
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, 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.
PI: Trisha Moore, Department of Biological and Agricultural Engineering, Kansas State University