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Date Permissions Signed

9-9-2015

Date of Award

Spring 2007

Document Type

Masters Thesis

Degree Name

Master of Science (MS)

Department

Geology

First Advisor

Mitchell, Robert J. (Geologist)

Second Advisor

Bittman, Shabtai (Scientist)

Third Advisor

Homann, Peter S., 1953-

Fourth Advisor

Babcock, R. Scott (Randall Scott)

Abstract

The Abbotsford-Sumas aquifer is a shallow, unconfined aquifer in northern Whatcom County, WA and southern British Columbia, Canada that is contaminated with nitrates due to agricultural land use. Currently, conservation managers rely on Post-Harvest Soil Nitrate Tests (PHSNTs) to predict nitrate leaching potential to the aquifer. However, these tests have limitations as an assessment tool because of their inaccuracy. Therefore, US and Canadian government agencies are considering the NLEAP on STELLA (NLOS) leaching model as an additional tool for assessing nutrient management strategies. NLOS is an adaptation of the Nitrogen Leaching and Economic Analysis Package (NLEAP) model. I examined the applicability of the model by calibrating it to an agricultural field plot in southern British Columbia. NLOS was calibrated to an agricultural field in Agassiz, BC for this study, but I expect it will perform similarly in the Abbotsford-Sumas aquifer due to similar soil types and climatic conditions.

NLOS incorporates fertilizer application events, climatic data, and soil properties, to simulate one-dimensional water flow and nitrogen fate and transport. Field data from a trial of silage corn located at the Pacific Agri-Foods Research Centre in Agassiz, BC (PARC Agassiz) was used to calibrate the model. Monthly sampling included soil, soil pore water, nitrous oxide emissions, and groundwater chemistry parameters. The field soil (a silt loam) was subjected to a nutrient loading and crop management scenario comparable to regional farming practices.

The ability of NLOS to predict water and nitrate transport during seasonal precipitation events was examined by comparing simulations to monthly field data. NLOS was found to be useful for predictions of soil nitrate and ammonium in the upper 12 inches of the soil profile, and nitrate leaching from the 36-inch depth. Model predictions accounted for 84% of the observed variability in nitrate leached from 24 to 36 inches deep. Simulated soil nitrate and ammonium in the upper 12 inches of the soil profile accounted for 84% and 87%, respectively, of the variability in the observed values. NLOS also produced adequate predictions of nitrate leaching from 12 to 24 inches deep (R2 = 0.63), and soil water from 0 to 36 inches deep (average R2 for all layers = 0.52). Field observations and model simulations indicate that nutrients in the soil and soil pore water fluctuated in direct response to fertilizer applications, crop events, and precipitation. Although the model performed reasonably well, more frequent field data collection is recommended for further model calibration and validation.

The calibrated model was also used to assess various nutrient-loading scenarios and to recommend the timing of the PHSNT. Hypothetical scenarios suggest that timing fertilizer application to rainfall events is the most effective way to reduce nitrate leaching. Field observations and model simulations also indicate that conducting the PHSNT concurrent with crop harvesting would provide the most accurate assessment of nitrate leaching potential.

Type

Text

DOI

https://doi.org/10.25710/je5r-7611

Publisher

Western Washington University

OCLC Number

182548616

Subject – LCSH

Soils--Nitrate content--British Columbia--Agassiz--Testing; Soils--Leaching--British Columbia--Agassiz--Testing; Groundwater--Pollution--British Columbia--Agassiz; Nitrates--Environmental aspects--British Columbia--Agassiz

Geographic Coverage

Agassiz (B.C.)

Format

application/pdf

Genre/Form

masters theses

Language

English

Rights

Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this thesis for commercial purposes, or for financial gain, shall not be allowed without the author's written permission.

2007hirschheatherthesissuppfiles.xls (618 kB)
Raw Data, April 2007

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