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The relevance of the study is determined by the demand for a physically adequate mathematical description of the interactions of water in the soil to develop a model of soil moisture dynamics as the intellectual core of resource-saving technologies for precise irrigation farming. The aim of the work is theoretical substantiation and mathematical formulation of the hydrophysical functions of the soil, taking into account hysteresis. A description of three systems of soil hydrophysical functions is given. To verify and compare the systems, computational experiments were carried out using both the package of original software and “3305 Ida silt loam (> 15 cm)” soil data from the authoritative literary source – the Mualem catalogue. The parameters of the functions were identified by the method of point approximation of the experimental data on the main branches of the hysteretic water-retention capacity. Using these parameters, we calculated (i) predictive estimates for the values of the function of relative hydraulic conductivity; (ii) scanning branches of the hysteretic water-retention capacity; (iii) precise irrigation rate. The hysteresis phenomenon is not typical for the hydraulic conductivity as a function of the volumetric water content in the soil. The original functions of System 3 are recommended for use. The advantages of the proposed method for calculating the precise irrigation rate are shown. The benefit of each system is that the functions forming this system, namely the water-retention capacity and the relative hydraulic conductivity of the soil, have a common set of parameters. For the type of soil considered, in case of using the identical value of pre-irrigation soil moisture (179 [cm3 · cm-3]), both for calculating the precision irrigation rate and according to the “traditional” method, when moistening 50 cm soil layer, the total unproductive water consumption at irrigation rate 555 [m3 · ha-1] can reach 0.029 [cm3 · cm-3] or 140 [m3 · ha-1] in the calculated layer. At the same time, when applying precision standards, an excess of free moisture is not formed. It shows additional opportunities not only to save water during irrigation, especially in arid regions, but also to reduce the leaching of nutrients and agrochemicals outside the calculated soil layer and, accordingly, to reduce the additional environmental load on the surrounding area.

Data on soil moisture reserves are the basis for decision-making in the agricultural boghara system, because it determines the development of agricultural crops potential, terms of top-dressing and additional fertilizing, and makes it possible to predict yield of agricultural crops. In this article the influence of relief morphometric characteristics on the distribution of precipitation over the territory was studied. The research area is the land of the eastern part of Klepininsky rural settlement of Krasnogvardeysky district, the central part of Crimean Peninsula. The article considers approaches, divided into 2 main categories (according to the type of data used), based on the use of GIS capabilities and remote sensing data, to analyze the soil water content (SWC) using the example of research area and relationship of this parameter to the terrain relief. It was established that the morphometric characteristics of relief affect the amount of soil moisture.

Investigation and management of the productivity of agricultural landscapes in regional scale play a significant role in solving the most important problems of sustainable development of the region under interest. A modern wide-distributed and powerful scientific tool for analysis, monitoring, and decision support in agronomy and agroecology is crop simulation modelling. At the same time, the simplest calculation methods (empirical regression models) are traditionally used for the predictive estimation of the productivity of agroecosystems over rather large areas (region-wide). The article intends to fill such gap, presenting the author’s view on the specifics of using dynamic models for regional (mesoscale) calculations. The issues of information support of models in the regional projects as well as the aspects of program implementation of the infrastructure of corresponding computer experiments are considered. We also discuss several prospective use cases for crop-model-based regional projects and propose the methods of processing and presentation the obtained results in a GIS-environment. The practical applicability of the described methodology is demonstrated on the example of calculations of spring barley production processes in the Republic of Crimea.

An agricultural landscape is a section of a region shaped by its natural landscape features primarily involving agricultural land use and land management. Intensive anthropogenic activities have left a permanent mark on agricultural landscapes, which have been developed over hundreds of years. Agricultural landscapes constitute a spatiotemporal structure. Hence they represent a complex system in which a large number of processes occur continuously that, due to their temporal dynamics, lead to constant changes in the state of the system. Traditional experiments are inappropriate for the impact assessment of anthropogenic and naturally occurring changes in agricultural landscapes. The only option here is to conduct virtual landscape experiments at the computer level. To this end, a relevant set of spatial, quantifiable landscape indicators is defined that can be used to map the landscape on the computer. Building on the extensive expertise in agricultural landscape research, indicators can be mapped using validated and robust models and their dynamics described involving temporal aspects. Various model types can be used in this process. Special simulation environments involving the use of spatial data and accounting for possible land use and global changes enable forward-looking scenario simulations to provide answers to the question of the sustainability of agricultural land use systems. Decision support systems (DSS) that exploit the latest possibilities offered by information technology, statistics and artificial intelligence provide the framework for integrating models, spatial data concerning the state of the landscape and scenario data, simulation techniques as well as tools for interpreting and visualising results. Such DSS are also the basis for quantifying the complex impact of site conditions, changes in land use or management, and of potential climate change on individual landscape parameters or landscape indicators. A number of examples show how indicator-based models of different types can be used to assess the impact and sustainability of land use systems on a landscape scale. As a prerequisite for the development and validation of integrated dynamic landscape models, more long-term ecological studies and monitoring systems are required. This also means that more resources are necessary to support these activities. The use of models and virtual simulation experiments within a DSS framework at the computer is a very promising way of finding suitable site-specific complex measures for the adaptation of agriculture to climate change.

Purpose of research was to develop technological basis for obtaining related remote sensing data and ground-based observations of high-level accuracy and reliability with its subsequent introduction into the monitoring system of agricultural lands state. Introduction of digital technologies will improve the quality of agricultural lands monitoring and accuracy of criterion assessments of parameters of crop condition and fertility levels, including capacity to localize and map degraded soil processes. The prerequisites for the transition to digital technologies in agriculture were studied. Existing systems for monitoring and forecasting the condition of crops are considered. The structure of the system of digital agricultural production, its components and relations between them are determined.

Requirements for the infrastructure and functionality of dynamic models of the production process of agricultural plants, which are necessary for building computer systems to support long-term solutions in agriculture and land management, are described. The extent to which domestic and foreign developments meet these requirements is shown.

Current intensification and changes in agricultural land use practices increase environmental impact that can be reduced by bridging the gap between socio-economic demands and scientific justification of sustainable agricultural land use. This can be achieved by replacing the goal of maximum crop yields with the goal of minimal environmental impact. This paper presents results of integrated crop simulation system development for analysis of alternative planning strategies in agricultural land use, with focus on the crop rotation influence on environmental sustainability. The effective tools used in analysis include (1) long-term analysis of changes in agricultural land using a dynamic crop model with daily time step; (2) justification of arbitrary crop rotation scheme of different agro-technologies and sparing measures; and (3) analysis of modern farming management methods using model-oriented approach. The results of study also include estimation of two alternative practices of crop harvesting including remaining or removing whole crop residues from the agricultural field and their influence on basic parameters of soil fertility. In addition, we analyzed comparative efficiency of different agricultural measures neglecting the negative influence of possible climate changes in long-term consequences. Corresponding efficiency rating is the following: organic fertilizer, green manure legume sparing harvesting, winter catch crop, and rotation scheme.

Basic principles of the multidisciplinary approach to arctic marine transport systems (MTS) design and analysis are described in the article. The main idea of the approach is to synthesize geographic information system (GIS) technologies, different shipbuilding disciplines, fleet planning instruments and agent-based dynamic simulation models in an integrated software framework on the basis of object-oriented programming. Vessel operation is described as the movement and interaction of independent ships in GIS environment within the framework of the simulation model. MTS operation combines vessel operation itself (routing, determination of speed and fuel consumption, icebreaker escort, etc.) with plenty of external entities (port infrastructure, ice channel freezing process, offshore platform operation, etc.) that could be described as systems with comprehensive logic and physical behavior. Such integration provides a new quality of MTS simulation that allows considering complex interconnection of various subsystems and all the important details of each MTS project. The outline of the program framework to realize such an approach is given, and two case studies are described to demonstrate its capabilities and feasibility.

Some problems of decision support systems in computer aided agriculture are discussed. The main focus is made on collaborative model development, including model decomposition issues and implementation of generic frameworks for polyvariant model use. A current state and prospective ideas for improvement of modeling infrastructure suitable to perform multi-factor computer experiments with existing crop simulation models are presented.

An original and convenient (from a practical point of view) method to estimate the supply of productive moisture in the soil is offered. The method is based on a physically adequate mathematical model of the soil hydrological properties considering the hysteresis of the water-retention capacity. The computation of the irrigation rates, which is based on such estimates, minimizes the water wastage if the excess of the gravitational water is formed and this water percolates out of the moisturized soil profile under watering conditions. The practical applying of the method is able to optimize the crop irrigation techniques, eliminates any inefficient losses of irrigation water and nutrients (and other agricultural chemicals), promotes the rational usage of the water resources as well as provides developing effective solutions of urgent problems of the land ecological management.

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, andwater (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models’ responses to CTW changes (R¨otter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012)...

Typical use cases of the crop simulation models consist of such operations as parametric identification, yield forecast and optimization, analysis of different technologies etc. All these tasks relate to multiple running of the model with several variants of input parameters and can be automated by means of polyvariant crop simulation framework which allows performing the multiple running in the batch mode. Such framework has been developed in our laboratory. It makes it possible to register any crop simulation model in the database and to perform several typical operations with it. As a result we present the wide-functional computer system for planning and automation of multi-factor computer experiment with arbitrary dynamic crop models.

We examine the influence of noise on the propagation of harmonic signals with two frequencies through discrete bistable media. We show that random fluctuations enhance propagation of this kind of signals for low coupling strengths, similarly to what happens with purely monochromatic signals. As a more relevant finding, we observe that the frequency being propagated with better efficiency can be selected by tuning the intensity of the noise, in such a way that for large noises the highest frequency is transmitted better than the lower one, whereas for small noises the reverse holds. Such a noise-induced frequency selection can be expected to exist for general multifrequency harmonic signals.