Modern technologies make it possible to obtain a lot of diverse information about the soil properties using satellite images, but field studies are also required to create or refine digital soil maps. To create a digital soil map scaled 1:25 000 in 2016, a classical field study was conducted with the laying of soil sections in places with the same coordinates as in the mapping of 1982. It allowed to carry out retrospective monitoring of transformation of morphogenetic and agrochemical properties of soils of the southern forest-steppe of the Republic of Bashkortostan (Russia) for the 34-year period of farm use. Thus, the correction and digitization of the soil map allowed to establish that arable land occupies 69.792 ha (67.9%) in the structure of agricultural land (102 811 ha). The monitoring showed deterioration of the main characteristics of arable soil fertility: the diminishing of humus-accumulative horizons, significant decrease of humus content (p ≤ 0.05), a small but reliable acidification of the medium reaction and reducing labile phosphorus. Losses of organic matter occurred mainly in the most fertile soils; their proportion decreased from 55.9% of the total area of agricultural land to 12.4%.

In this paper, the regression analysis technique is applied to a large water quality dataset for the Sitnica River in Kosovo. It has been done to assess the correlation between water quality parameters. The data are generated by a wireless sensors network deployed in Sitnica. A regression analysis is applied to four water quality parameters: temperature, dissolved oxygen, pH, and electrical conductivity. The correlation between each pair of parameters has been assessed by using the WEKA software package, which is a popular time-saving tool for data analysis in distinct domains. The data are pre-processed to exclude out-of-range values and then the assessment of correlation for the pairs of parameters is applied. In comparison to other pairs of water quality parameters, the results show that dissolved oxygen and electrical conductivity correlate particularly closely with temperature. Regression equations of these two pairs of parameters may provide inferred information on dissolved oxygen and electrical conductivity about the Sitnica River. Such information may otherwise not be available to resource managers in Kosovo. Moreover, due to its easy to use and availability as an open-source software, WEKA may aid decision-makers on the management providing almost real-time information about surface water quality within the basin. This can be particularly useful especially in the case of continuous observation of water quality and a huge dataset gathered by using wireless sensors.