Research: Hydrologic Modeling/Monitoring

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:
  • Quiring, S. M. (2004) Developing a Real-time Agricultural Drought Monitoring System for Delaware.  Publications in Climatology, 57(1), 104 pp.