Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize-Soybean Rotation in Nebraska

Authors

Tanessa Morris, University of Nebraska-LincolnFollow

First Advisor

Trenton E. Franz

Date of this Version

5-2024

Citation

A thesis presented to the faculty of the Graduate College at the University of Nebraska in partial fulfillment of requirements for the degree of Master of Science

Major: Natural Resource Sciences

Under the supervision of Professor Trenton E. Franz

Lincoln, Nebraska, May 2024

Comments

Copyright (c) 2024, Tanessa C. Morris. Used by permission

Abstract

The precise measurement of soil water content (SWC) is crucial for effective water resource management. This study utilizes the Cosmic Ray Neutron Sensor (CRNS) for area-averaged SWC measurements, emphasizing the need to consider all hydrogen sources, including the time-variable ones like plant biomass and water content. Chapter 1 presents a background on soil moisture estimation, CRNS technology, and an overview of the study. It discusses various soil moisture measurement techniques, highlights the gap in knowledge addressed by CRNS technology, explains CRNS functionality and advancements, and outlines the study's motivations and methods.

Chapter 2 reports a study conducted near Mead, Nebraska, at three field sites (CSP1, CSP2, and CSP3) growing a maize-soybean rotation that has been monitored for 5 (CSP1 and CSP2) and 13 years (CSP3). Data collection includes biomass water equivalent (BWE) biweekly with destructive sampling, epithermal neutron counts, atmospheric meteorological variables, and point-scale SWC from a sparse Time Domain Reflectometry (TDR) network (4 locations and five depths). In 2023, dense gravimetric SWC surveys were collected eight times in fields CSP1 and CSP2 and nine times in CSP3 over the growing season (April to October). The N₀ parameter, presented in Desilets et al. (2010) as the transformation function between epithermal neutron counts and SWC, exhibits a linear relationship with BWE, suggesting a straightforward vegetation correction factor is suitable (f_b). Results from the 2023 gravimetric surveys and long-term TDR data indicate a neutron count rate reduction of about 1% for every 1 kg m^-2 (or mm of water) increase in BWE. This reduction factor aligns with existing shorter-term row-crop studies but nearly doubles the value previously reported for forests. This long-term study contributes valuable insights into the vegetation correction factor for CRNS, helping resolve a long-standing issue within the CRNS community. Chapter 3 discusses further CRNS limitations, study limitations, and potential future directions. These include novel biomass estimation approaches, addressing other hydrogen pools, and integrating the f_b correction into open-source scripts.

Advisor: Trenton E. Franz