Physical Sciences and Mathematics Commons^™

Agricultural Irrigation Induced Evaporation In A Temperate Study Area: A Stable Isotope Approach, Lincoln Grevengoed

Masters Theses

In regions where groundwater is used for irrigation, significant water losses take place due to evaporation. Previous studies demonstrated the utility of stable oxygen and hydrogen isotopes in estimating evaporative water loss experienced during return flow back to an aquifer. Unlike arid regions where the other studies took place, this study examined the region around Kalamazoo, Michigan, the United States, which experiences a more temperate climate. Irrigation in the Kalamazoo area primarily uses center-pivot systems supplied by wells, unlike flood irrigation in previous study areas. Water samples were taken periodically from wells close to center-pivot irrigation systems. Water losses due …

Irrigation Design In Montana: Accommodating Varying Water Accessibility Across The Continental Divide., John Garrett Lampson

Biological and Agricultural Engineering Undergraduate Honors Theses

The design work performed in this project was conducted over two summers (2018, 2019) of internship experience with the Natural Resources Conservation Service (NRCS) across the state of Montana. The first summer’s design work was based out of Glendive, MT, in Dawson County, approximately 50 kilometers from the North Dakota border. The second summer was in Missoula, MT, in Missoula County, near the Idaho border. The two areas differ significantly in topography, weather, and water availability with the main separating geographic influence being the Rocky Mountains.

This paper focuses on the design process and requirements for two farms located outside …

A Deep Learning Approach To Mapping Irrigation: U-Net Irrmapper, Thomas Henry Colligan Iv

Graduate Student Theses, Dissertations, & Professional Papers

Accurate maps of irrigation are essential for understanding and managing water resources in light of a warming climate. We present a new method for mapping irrigation and apply it to the state of Montana over the years 2000-2019. The method is based on an ensemble of convolutional neural networks that only rely on raw Landsat surface reflectance data. The ensemble of networks method learns to mask clouds and ignore Landsat 7 scan-line failures without supervision, reducing the need for preprocessing data or feature engineering. Unlike other approaches to mapping irrigation, the method doesn't use other mapping products like the Cropland …