Home > Research & Projects > Projects > Recently Completed Projects > Water Resources Engineering
Recently Completed Water Resources Engineering Research Projects
Kuwahara, Sara -- M.S. 2002
Efficacy of an Ozone-Ultraviolet Light Reactor in the Disinfection of Micorbial Populations in Secondary Effluent
Colaizzi, Paul -- Ph.D. 2001
Remote
Sensing and in situ soil moisture measurements interfaced with
simulation models for real time irrigation management in precision
agriculture
Haberland, Julio -- Ph.D. 2001
AgIIS, Agricultural Irrigation Imaging System, Design and Application
Kostrzewski, Micheal -- Ph.D. 2000
Determing
the Fesasibility of Collecting High-Resolution Ground-Based Remotely
Sensed Data and Issues of Scale for Use in Agriculture
Salazar, Raquel -- Ph.D. 2000
Surface Water Management Optimization in a Irrigation District in Mexico
Kuwahara, Sara -- M.S. 2002
Advisor: Dr. Joel Cuello
Efficacy of an Ozone-Ultraviolet Light Reactor in the Disinfection of Micorbial Populations in Secondary Effluent
ABSTRACT:
Ozone and ultraviolet
(UV) light have been shown to be effective in treating emerging
pathogens that are affected by the current standard treatment of
chlorine. The hypothesis of this study was that a combined treatment of
UV light and ozone would result in greater pathogen reduction compared
with a large dose of either one individually. In the one-way study for
ozone and UV light, the ozone treatments took at least twice as long as
the UV treatments to achieve the same extent of reduction in micorbial
population. Specifically, 60 min for ozone and 30 min for UV light for
a 4-log reduction in heterotropic plate counts (HPC's); 10 min for
ozone and 3 min for UV light for a 3-log reduction in total coliforms
and total fecal coliforms; and, 6 min for ozone and 3 min for UV light
for a 2-log reduction in coliphage. The ozone treatments, however
unlike the UV treatments, resulted in no positive re-growth in bacteria
after treatment. Ozone and UV light acting simultaneously exhibited not
merely additive, but synergistic interactive effects in reducing
micorbial populations, with the exception of the case where both
factors assumed low levels (2 min UV and 1 min ozone). Specifically,
the following treatment combinations yielded the maximum micorbial
reductions: low level of UV (1 min) and high level of ozone (4 min) for
HPS's; high level of UV (2 min) and high level of ozone (4 min) for
bacteria; and either one of the foregoing treatments for overall
microbial population. The synergistic interactive effects between UV
light and ozone when acting simultaneously allowed for lower UV and
ozone levels to achieve the same extent of micorbial reduction achieved
by either factor acting separately. Thus, 2 min of ozone and 2 min of
UV light applied simultaneoulsy was just as effective as 6-8 min of
ozone only or 2.5 min of UV light only. If UV light and ozone were to
be applied successively, the most effective sequence of application
would be ozone first followed by UV light.
Colaizzi, Paul -- Ph.D. 2001
Advisor: Dr. Chris Choi
Remote
Sensing and in situ soil moisture measurements interfaced with
simulation models for real time irrigation management in precision
agriculture
ABSTRACT:
Pressurized irrigation
systems (e.g., sprinkler or drip) allow water, fertilizer, and
pesticide delivery to be controlled at temporal and spatial resolutions
that account for variations in crop, soil, and pest conditions over a
given area. Effective irrigation management of pressurized systems
requires timely information on soil and crop water status at spatial
resolutions that are compatible with the delivery system; such
information must be both sampled and modeled. Sampling methods such as
in situ soil moisure sensors, air and satellite based remote sensing
platforms, and hand held infrared thermometers presently do not meet
this criteria. A modular, ground based remote sensing system aboard a
linear move sprinler set was developed to address this need, where
multispecral and thermal sampling of crop canopies is possible daily at
a one meter spatial resolution. Correlations between the remotely
sensed data and in situ soil moisture measurements are presntly under
investigation. The remotely sensed data is intended to be interfaced
with soil water balance models to provide real time feedback and
prediction at spatial and temporal resolutions required for irrigation
management in precision agriculture.
Haberland, Julio -- Ph.D. 2001
Advisor: Dr. Waller
AgIIS, Agricultural Irrigation Imaging System, Design and Application
ABSTRACT:
Remote sensing is a
tool that is increasingly used in agriculture for crop management
purposes. A ground-based remote sensing data acquisition system was
designed, constructed and implemented, in order to collect high spatial
and temporal resolution data in irrigated agriculture. The system was
composed of a rail that mounts on a linear move irrigation machine, and
a small cart that runs back and forth on the rail. The cart was
equipped with reflectance sensors. A global positioning system and
triggers on the rail indicated cart position. The sensor package
collected reflectance data in the visible, near infra red and thermal
bands. The data was postprocessed in order to generate vegetation maps,
nitrogen and water status maps and other indices relevant for site-
specific crop management. A geographic information system (GIS) was
used to generate images of the field on any desired day. The system was
named AgIIS (Agricultural Irrigation Imaging System). This ground based
remote sensing acquisition system was developed at the Agricultural and
Biosystems Engineering Department at the University of Arizona in
conjunction with the U.S. Water Conservation Laboratory in Phoenix, as
part of a cooperative study primary founded by the Idaho National
Environmental and Engineering Laboratory.
A second phase of the study utilized data acquired
with AgIIS during the 1999 cotton growing season to model petiole
nitrate (PNO3?) and total leaf N. A Latin square experimental design
with optimal and low water and optimal and low nitrogen was used to
evaluate nitrogen status under water and no water stress conditions.
Multivariable models were generated with neural networks (NN) and
multilinear regression (MLR). Single variable models were generated
from Chlorophyll meter readings (SPAD) and from the Canopy Chlorophyll
Content Index (CCCI). All models were evaluated against observed PNO3?
and total leaf N levels. The NN models showed the highest correlation
with PNO3? and total leaf N.
AgIIS was a reliable and efficient data acquisition
system for research and also showed potential for use in commercial
farming systems.
Kostrzewski, Micheal -- Ph.D. 2000
Advisor: Dr. Waller
Determining
the Feasibility of Collecting High-Resolution Ground-Based Remotely
Sensed Data and Issues of Scale for Use in Agriculture
ABSTRACT:
A ground based remote
sensing system (AgIIS, Agricultural Irrigation Imaging System) was
attached to a linear move irrigation system. The system was used to
develop images of a 1-hectare field at 1 x 1 meter resolution to
address issues of spatial scale and to test the ability of a ground
based remote sensing system to separate water and nitrogen stress using
the coefficient of variation (CV) for water and nitrogen stress
indices. A 2 x 2 Latin square water and nitrogen experiment with 4
replicates was conducted on cotton for this purpose. Treatments
included optimal and low nitrogen with optimal and low water. ANOVA was
not an adequate method to assess the statistical variation between
treatments due to the large number of data points. In general, the
coefficient of variation of water and nitrogen stress indices increased
with water and nitrogen stress. In fact, the coefficient of variation
of stress indices was a more reliable measurement of water and nitrogen
status than the mean value of the indices. Differences in coefficient
of variation of stress indices between treatments were detectable at 3
m grid resolution and finer for water stress and at 7 m grid resolution
and finer for nitrogen stress.
Salazar, Raquel -- Ph.D. 2000
Advisor: Dr. Yakowitz
Surface Water Management Optimization in a Irrigation District in Mexico
ABSTRACT:
The Alto Rio Lerma
Irrigation District (ARLID) has problems related to economics,
environment and water use. Producers need to increase their net income
but at the same time to reduce the environmental concerns such as
nutrients and pesticides losses in percolation and runoff, which are
related to water, management and can cause groundwater contamination.
In first term, this research will estimate the amount of nutrients and
pesticides losses in percolation and runoff for the most representative
cropping pattern in the ARLID (10 crops) using GLEAMS (Groundwater
Loading Effects for Agricultural Management Systems), a water depth for
each crop will be suggested to reduce runoff and percolation but at the
same time satisfying the crop requirements. Using the 10 crops optimal
cropping patterns will be generated for different water availability
scenarios using linear programming. The Range of Value Method
(ROVM)(Multiple Objective Technique) will be applied to measure the
performance of each scenario in Economical, Environmental and Water Use
objectives. Therefore, an indicator for optimal water management in
ARLID will be estimated for each scenario: net income, water, Nitrogen,
Phosphorus, and pesticides in runoff and percolation. In addition, a
modification of the Range of Value Multiple Objective Method will be
made in order to consider an Lp distance=2, instead of 1, this change
will generate a nonlinear hierarchy optimization that will be compared
with the results obtained in ROVM.
|
