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Research: Hydrologic Modeling/Monitoring
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I am interested
in
developing, testing, and comparing various methods and tools for
monitoring hydroclimatic
conditions, in general, and droughts, in particular. While the
impacts of droughts are well
documented, a uniform method for defining, monitoring, and quantifying
the
severity of drought conditions does not exist.
Drought is a complex phenomenon that is difficult to accurately
describe
because its definition is both spatially variant and context
dependent. My research addresses the spatial, temporal,
and context issues that arise when attempting to objectively quantify
drought
onset and drought severity. This work
involves analyzing meteorological and satellite data, and utilizing
agricultural, hydrological, and soil moisture models. The main
goal of this research is to provide a
better understanding of severe hydrologic events in order to facilitate
the
adoption of appropriate adaptation, mitigation, and avoidance
strategies. As
part of my Masters thesis I evaluated four
agricultural drought indices to determine which
is the most suitable for quantifying and monitoring agricultural
drought on the
Canadian prairies (Agricultural
and Forest Meteorology 2003). I developed
a real-time agricultural drought monitoring system for the State of
Delaware that provides
agricultural producers with detailed soil moisture information at a
relatively
high spatial resolution for my dissertation (Publications in Climatology
2004; Agricultural and Forest Meteorology 2008). During my first
two years at Texas A&M I
worked with colleagues from Atmospheric Sciences (Dr. Nielsen-Gammon),
Agriculture
(Dr. Miller), and the Spatial Sciences Lab (Dr. Srinivasan) on a
project funded
by the Texas Water Development Board (TWDB) to develop suitable methods
and
tools for monitoring drought at the local level within Texas.
I reviewed a large number of existing drought indices to identify their
strengths and weaknesses and then evaluated these drought indices using
both
quantitative and qualitative approaches to determine which are the most
appropriate for monitoring drought in Texas
(Geography Compass 2009). One of my MS students (S. Ganesh)
contributed
to this project by evaluating the utility of the satellite-based
Vegetation
Condition Index (VCI) for monitoring drought in Texas (Agricultural
and Forest Meteorology in preparation). Lei Meng (PhD student)
helped extend my
doctoral work by comparing the performance of three different soil
moisture
models. We demonstrated that the
Variable Infiltration Capacity (VIC) model is the most suitable for
simulating
soil moisture, but model performance varies significantly over space
and time
due to variations in climatic and edaphic conditions (Journal of
Hydrometeorology 2008).
In the fourth paper arising from the TWDB project I introduced a new
method
for developing appropriate operational drought thresholds (Journal of
Applied Meteorology and Climatology submitted). Ongoing
research projects include a follow up to our recent Journal of
Hydrometeorology paper that uses soil moisture data from
the Oklahoma Mesonet (supplied by my collaborators at the Oklahoma
Climatological Survey (Dr. Basara and Mr. Illston)) and an
investigation of
soil moisture conditions during the recent drought in the southeastern
US (with
Dr. Mahmood (Western Kentucky University)). The following links provide more information on this research: |