Application of Statistical Quality Control Charts and Geostatistics to Soil Quality

Assessment in a Semi-Arid Environment of South-Central Iran

A. Moameni and J. A. Zinck

International Institute for Aerospace

Survey and Earth Sciences (ITC),

Enschede, the Netherlands

(SQC 22)

Abstract

The research concerns the semi-arid area of Marvdasht in the Fars Province, South central Iran. The area, one of the most productive in Iran, is very susceptible to land degradation due to soil, climatic, topographic, hydrological, and biological conditions.

The purpose was to apply control charts to soil quality assessment in particular and to land evaluation in general. The research was carried out taking advantage of an existing full data set, that allowed to test how efficiently control charts can be used to assess the sustainability of land management systems in a semi-arid environment where irrigated wheat has been practiced as a monoculture for centuries. Patterns of variation and distribution of soil variables are analyzed using classical statistics.

Statistical quality control charts (SQC) are used to investigate variability in soil properties and control the mean of soil variables. The spatial features are pictured through kriging, a weighted moving average interpolation technique, based on computation, interpretation and modeling of variograms of soil variables. Data layers created by the application of SQC and geostatistics are integrated in a GIS to determine changes in soil qualities. The sustainability of the soil resource is assessed on the basis of the information obtained from the analysis of the changes in soil qualities. In conclusion, statistical quality control charts proved to be efficient for assessing selected soil properties. Control charting can be used in conjunction with geostatistics to map the spatial variation of land qualities in a GIS environment.

Soil quality changes over time. Changes can be identified from variations in soil properties caused by human activities. Data on management-dependent soil properties must be properly analyzed to determine if land management practices and land use have been successful and to decide on future actions. It is through the analysis of such data that management activities can be evaluated and strategies to sustain the use of soil resources can be selected.

Statistical methods such as regression and analysis of variance have been used extensively to analyze soil data and model their variations. However, assessing soil quality may require the use of more than one technique to analyze patterns of variation in its components. Quality control charts are statistical tools that allow such analysis.

They are commonly used in controlling the process variability in manufactured goods and services industry. The statistical basis for their use is well established and several software packages have been developed that allow their construction to be done by computer (Ryan, 1989). Larson and Pierce (1994) suggested that quality control charts could be appropriate statistical tools for assessing changes in soil quality.

The purpose of this study was to apply control charts to soil quality assessment in particular and land evaluation in general. The research mobilized a large data set that allowed to test the efficiency of control charts in assessing the sustainability of land management systems in a semi-arid area of Iran, where irrigated wheat has been practiced as monoculture for centuries.