Natural Resources Management

TECHNOLOGIES AND MODELING FOR IMPROVED CROP WATER MANAGEMENT IN IRRIGATED AND NONIRRIGATED AGRICULTURE- There is a need to improve the management of water in North Dakota's irrigated and nonirrigated agriculture. Water quantities and water quality are both impacted by agriculture. Technologies such as sensors for on-site measurement, as well as remote sensing, of the water status of crops holds the potential to assist with the development of improved crop production practices which can improve crop water use efficiency and minimize adverse environmental impacts. This project will use field experimentation, lab work, and modeling studies to assess and develop improved crop production practices that will affect water quantity and quality. The project will reach farmers, peer scientists and engineers, students, and the public.

WATER MANAGEMENT TO IMPROVE WATER QUALITY AND CROP PRODUCTIVITY- This project is designed to improve crop production and natural resource conservation with proper drainage water management. Scientific advancements, necessary engineering designs, and management recommendations derived from this project aim to improve farmers' profitability while simultaneously helping to secure the public's interest in more efficient use of water resources, minimizing water quality problems, and maintaining high quality soil systems and natural resources. For the ten counties in eastern ND, among the total 6.9 million acres of farmland, there are about 0.7 million acres tile drained. With an average 10% yield increase for sugarbeet (0.1 million acres), corn (0.3 million acres), and soybean (0.3 million acres), the economic gain is $40 million in 2016 alone based on ND Ag Statistics at $3.15/bu for corn, $9.05/bu for soybean, and $45/ton for sugarbeet.

MODELING THE EFFECTS OF BEST MANAGEMENT PRACTICES ON STREAM WATER QUALITY AT THE WATERSHED SCALE - Best Management Practices (BMPs) control the delivery of nonpoint source (NPS) pollutants to receiving water bodies by minimizing pollutant generation at source, retarding pollutant transport, and reducing pollutant concentration through biogeochemical transformation. Although various BMPs have been shown by many field studies to be able to provide on-site benefits of improving water quality at the field and farm scales, their effectiveness to collectively provide off-site benefits of improving downstream water quality at the watershed scale is almost impossible to quantify by merely conducting field studies. This is because the success of NPS control by the combinations of BMPs installed in a watershed is affected by many factors such as weather, land uses, soils, types and placement of adopted BMPs. The Minnesota Buffer Law requires farmers to establish perennial vegetative buffers along public waterways and drainage ditches by 2017-2018. The vegetative buffers, also known as riparian filter strips, are expected to improve water quality for streams, rivers, lakes, and wetlands by reducing loads of sediment and nutrients from the farmlands to these surface water bodies. However, the effectiveness of implementing the Minnesota Buffer Law in improving the water quality of the Red River of the North remains to be seen because the drainage areas of the Red River are approximately evenly split between the states of Minnesota and North Dakota, while the latter does not have similar laws in place. Therefore, the main objective of this project is to model the effects of BMP in improving downstream water quality at the watershed scale. Two specific objectives are 1) to evaluate the effectiveness of riparian buffer zones in improving stream water quality in the Red River Basin; and 2) to develop optimization tools for the selection and placement of best management practices in an agriculture-dominated watershed. As a result, the watershed-scale models and optimization tools will be developed and applied to evaluate BMP's long-term performance in reducing NPS from agricultural watersheds and to make watershed management recommendations for farmers and resources managers.


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