Current soil- and land degradation seriously challenge our societies; it contributes to climate change, loss of biodiversity and loss of agricultural productions. Yet, soils are also seen as a major part of the solution, if maintained or restored to provide ecosystem services. Climate-smart sustainable management of soils can provide options for soil health maintenance and restoration. In the European Union, the resource management and sustainability challenge are addressed in the Green Deal that, among other goals, aspires towards a healthy climate-resilient agricultural sector that will produce sufficient products without damaging ecosystems and contribute to better biodiversity and mitigate climate change. The European Joint Programme (EJP) SOIL was set up to contribute to these goals by developing knowledge, tools and an integrated research community to foster climate-smart sustainable agricultural soil management that provides a diversity of ecosystem service, such as adapting to and mitigating climate change, allowing sustainable food production, and sustaining soil biodiversity. This paper provides an overview of the potential of climate-smart sustainable soil management research to the targets of the Green Deal that are related to soils most directly. The EJP SOIL EU-wide consultation (interviews and questionnaires) and literature analysis (national and international reports and papers) done in the first year (2020-2021) generated a wealth of data. This data showed that there are specific manners to do research that are essential for it to be effective and efficient and that can actively contribute to the Green Deal targets. We concluded that research needs to be: (i) interdisciplinary, (ii) long-term, (iii) multi-scaled, from plot to landscape, (iv) evaluating trade-offs of selected management options for ecosystem services and (v) co-constructed with key stakeholders. Research on climate-smart sustainable soil management should be developed (1) on plot scale when mobilizing soil processes and on landscape scale when addressing sediment and water connectivity and biodiversity management; and (2) address the enabling conditions through good governance, social acceptance and viable economic conditions. A guideline to European agricultural soil management: three layers for sustainable soil management: the biosphere: healthy soils and (bio)diverse landscapes (green bar); solutions: based on functioning of the natural system (yellow bar); enabling conditions: finding the social and economic enable conditions (blue bar).image

The soil properties characteristics are the object of the current study. Determination of the soil properties characteristics is a complex and responsible engineering and geological task. Reliability of engineering construction and its cost depend on the quality of solution of this task. The article presents the results of the study of the possibility of predicting the soil properties characteristics on the example of determining the sand deformation modulus. Based on the analysis of previous studies of correlation between the soil properties characteristics, the list of independent soil properties characteristics was determined: soil genesis, static normal stress, granulometric composition, initial density and humidity of the soil sample. The main disadvantages of existing methods of predicting the soil properties characteristics were identified. The possibility of using artificial neural network for predicting the soil properties characteristics was determined. The soil deformation modulus was selected as a response (dependent variable). The presence of not only numerical but also classification features among the independent characteristics did not allow predicting the soil properties characteristics within the framework of the classical regression model. A soil information model, based on an artificial neural network, was used to solve this problem because not only continuous quantitative but also discrete classification parameters (genesis) can be used among the independent parameters of the soil information model. Laboratory studies of 655 samples of alluvial sand of the Irtysh River floodplain were performed to confirm the possibility of using the soil information model. 5895 data vectors were obtained, including information on independent and response parameters. A detailed study of two granulometric compositions demonstrated limited possibilities for using known statistical methods for determining the soil properties characteristics. In 9 out of 20 cases, the results of the studies did not follow a normal distribution. The use of the soil information model allowed to solve this problem - the absolute percent error in determining the deformation modulus did not exceed 12.55 % (mean - 5.05 %), the coefficient of determination R-2 was at least 0.83 for unloaded sand samples, and at least 0.94 for loaded ones, for all datasets - 0.97. The performed studies confirmed the prospects of using the soil information model for predicting soil properties based on its known characteristics, which reduced the cost of engineering and geological surveys while ensuring the required accuracy of determining the soil characteristics.