UTSA UNIVERSITY OF TEXAS AT SAN ANTONIO
Hydrologic Modeling and GIS Laboratory
http://www.utsa.edu/hydroGIS Developed and Maintained by: Dr. Kyle Murray

Linda Daniele
Linda Daniele
Ph.D. Candidate
Universidad de Almería, Spain
e-mail: ldaniele@ual.es

Visiting Scientist in:
Department of Earth and Environmental Science
University of Texas at San Antonio
One UTSA Circle
San Antonio, TX 78249-0663

M.S., Geology
University of Naples, Italy 2000



My research focuses on understanding the ground-water chemistry of multiple aquifers in Campo de Dalíias, Spain. These aquifers underly an area of great economic strength in the province of Almería, as consequence of the continuous improvement in the cultivation techniques, and of the climatic characteristics that allow full time cultivation. All that has spoiled the development of the intensive greenhouse's agriculture, and at the same time, the urban and economic development of the province. The area under plastic cover occupies more than 20.000 ha. In the study area the agricultural activities are very important and are acknowledged as non-point source (NPS) pollution. Our Research Group is focused on characterizing the ground-water chemistry and understanding the relationships between the water chemistry and greenhouse activities.

As part of my research I collected nearly 450 ground-water samples, measured standard field parameters and analyzed the samples for concentrations of inorganic and isotopic compounds. I began data processing of the analytical results by means of traditional hydrogeochemical technical (diagrams of Piper, Schoeller, Durov, ionic relationships, graphics X-Y,...). The relationships among the variables have been studied by means of multivariant statistical analysis (PCA and Cluster) and geostatistics (factorial analysis and Kriging).

I arrived at UTSA in September of 2004 under a scholarship from the Spanish government to study with Dr. Murray for three months. During my visit, Dr. Murray is assisting me with: reorganization of the ground-water data into a relational geodatabase, analysis of the spatial and temporal relationships between water quality parameters and greenhouse activities, and comparisons of continuous data with discrete information.


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Last Updated: June 2006