Degree Type

Thesis

Date of Award

2014

Degree Name

Master of Science

Department

Natural Resource Ecology and Management

Major

Sustainable Agriculture

First Advisor

Lisa A. Schulte

Second Advisor

Matthew Helmers

Abstract

Predicting the hydrologic consequences of biomass cropping systems requires an understanding of how different crops and management practices affect soil hydraulic properties across space and time. To inform such predictions, I investigated the impacts of five biomass cropping systems on the hydraulic properties of soils across a landscape gradient in wet, dry, and average rainfall years. I used data from 2010 - 2012 on monthly volumetric soil moisture content and data from 2009 - 2013 on changes in saturated hydraulic conductivity to measure significant differences in mean soil moisture content among five cropping systems across five landscape positions. My results suggest moisture content was most broadly controlled by the amount of rainfall within a year, but there were also significant differences with landscape positions, cropping systems, cropping system by landscape position, and soil clay content; biomass yield was not a significant predictor of soil moisture. I also found a significant change in saturated hydraulic conductivity among cropping systems from 2009 to 2013, and different saturated conductivity among cropping systems at different landscape positions in 2013. Differences in hydraulic conductivity among cropping systems were commonly found at floodplain and footslope positions; there were very few significant differences among cropping systems at the summit, shoulder, and backslope positions. Changes over time within cropping systems are attributed to conversion to either perennial cropping systems or to no-till soil management in annual systems. My results support the hypothesis that different biomass cropping systems will have different hydrological impacts depending on landscape position. This knowledge can be used to parameterize or improve physically-based hydrologic models of biomass production and understand the potential environmental impacts bioenergy crop production.

DOI

https://doi.org/10.31274/etd-180810-1132

Copyright Owner

Usman Anwar

Language

en

File Format

application/pdf

File Size

123 pages

Included in

Agriculture Commons

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