Longitudinal analysis of spatially correlated data

• Published in: Stochastic environmental research and risk assessment Vol. 22; no. Suppl 1; pp. 49 - 57
• Main Authors: Militino, Ana F., Ugarte, M. Dolores, Ibáñez, Berta
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01.03.2008; Springer Nature B.V
• Subjects: Aquatic Pollution; Chemistry and Earth Sciences; Computational Intelligence; Computer Science; Earth and Environmental Science; Earth Sciences; Environment; Environmental science; Geology; Groundwater pollution; Math. Appl. in Environmental Science; Nitrates; Original Paper; Physics; Probability Theory and Stochastic Processes; Public concern; Statistical analysis; Statistics for Engineering; Stochastic models; Waste Water Technology; Water Management; Water Pollution Control; Ebro River Valley; Linear mixed model; Spatial linear model; Variogram; Nitrate concentration
• ISSN: 1436-3240; 1436-3259
• DOI: 10.1007/s00477-007-0158-6

Nowadays, the detection of areas with high nitrate concentration in groundwater is of public concern because an excess of these nitrogen compounds in any area represents serious environmental pollution. Hence, governmental agencies require geostatistical researchers to develop methods for assessing nitrate concentration. In this paper, we propose a linear mixed model which incorporates both spatial as well as longitudinal information with the particular objective of detecting areas with excess of nitrate in groundwater. The model extends in a natural way the traditional kriging approach, incorporating the longitudinal dimension. We illustrate the results using real data taken from wells pouring into the Ebro river and its tributaries in the province of Navarra, Spain.