The statistical analysis of salinity data from
samples collected yearly from genetic soil horizons of 69 points of the
Hungarian Soil Information and Monitoring System between 1992 and 2000 showed
changes in time. There is a strong atmospheric control over the groundwater
level and the resulting soil salinity. Weak statistical association was
established between either the pattern of yearly soil salinity changes in the
second (10-20 cm) and third (30-40 cm) genetic horizon and the groundwater
observation stations or the soil types. In the area of Kecskemét there was a
tendency of decreasing soil salinity patterns, while around Békéscsaba a
tendency of increasing soil salinity patterns, as illustrated by the
correspondence biplot. Regarding soil types, the solonetzic meadow soil showed
a tendency of increasing salinity. It was concluded that the statistical
analyses of the monitored data must be carefully planned in order to provide
the optimal background data as independent data from all those available to
accompany the monitored soil data as dependent variable.
Authors:A. Makó, B. Tóth, H. Hernádi, Cs. Farkas, and P. Marth
The Hungarian Detailed Soil Hydrophysical Database, called MARTHA ver2.0 has been developed to collect information on measured soil hydraulic and physical characteristics in Hungary. Recently this is the largest detailed national hydrophysical database, containing controlled information from a total of 15,005 soil horizons. Two commonly used pedotransfer functions were tested to evaluate the accuracy of the predictions on the MARTHA data set, representative for Hungarian soils. In general, the application of both examined pedotransfer functions (Rajkai,
et al., 1999) was not very successful, because these PTFs are representative for other soil groups. The classification tree method was used to evaluate the effect of soil structure on the goodness of estimations. It was found that using the soil structure data the inaccuracies of soil water retention predictions are more explainable and the structure may serve as a grouping variable for the development of class PTFs.
Authors:Brigitta Tóth, A. Makó, K. Rajkai, G. Sz. Kele, T. Hermann, and P. Marth
According to the Hungarian Soil Information and
Monitoring System's (HSIMS) database a group estimation method was developed to
predict the mean soil hydrophysical properties. The estimation efficiency of
the worked out prediction procedures was controlled on a test database, and on
a dataset of a study area. It can be established that the water retention and
the hydraulic conductivity of soils are sufficiently predictable from the
category data of soil maps. The 10-digit map codes of the PWW mapping method were
created by different estimation methods, and as a result the PWW map was drawn.
However, it is not always possible to estimate the necessary soil hydrophysical
properties from the available map information for preparing the PWW map.
Sometimes the knowledge gained from the field reports is needed as well.
Further studies are planned for integrating these morphological information
into our estimations.