Подсистема автономного программно-аппаратного комплекса для индуктивного долгосрочного прогноза осредненных значений метеопараметров

The research of the inductive method of long-term (forestalling to 0,5 year) prognosis of average decade air s temperature on the basis of principle of analogies was executed and it s sufficient was shown. The research of the offered approach was also conducted: in the base of spatial models without principle of analogies; in the polynomial harmonic base; the analysis of middle quality of the inductive prognostic method for cases of the analogue principle usage and without it

Integrated Solutions for the Water-Energy-Land Nexus: Are Global Models Rising to the Challenge?

Increasing human demands for water, energy, food and materials, are expected to accentuate resource supply challenges over the coming decades. Experience suggests that long-term strategies for a single sector could yield both trade-offs and synergies for other sectors. Thus, long-term transition pathways for linked resource systems should be informed using nexus approaches. Global integrated assessment models can represent the synergies and trade-offs inherent in the exploitation of water, energy and land (WEL) resources, including the impacts of international trade and climate policies. In this study, we review the current state-of-the-science in global integrated assessment modeling with an emphasis on how models have incorporated integrated WEL solutions. A large-scale assessment of the relevant literature was performed using online databases and structured keyword search queries. The results point to the following main opportunities for future research and model development: (1) improving the temporal and spatial resolution of economic models for the energy and water sectors; (2) balancing energy and land requirements across sectors; (3) integrated representation of the role of distribution infrastructure in alleviating resource challenges; (4) modeling of solution impacts on downstream environmental quality; (5) improved representation of the implementation challenges stemming from regional financial and institutional capacity; (6) enabling dynamic multi-sectoral vulnerability and adaptation needs assessment; and (7) the development of fully-coupled assessment frameworks based on consistent, scalable, and regionally-transferable platforms. Improved database management and computational power are needed to address many of these modeling challenges at a global-scale

Human and climate impacts on global water resources

Over past decades, terrestrial water fluxes have been affected by humans at an unprecedented scale and the fingerprints that humans have left on Earth’s water resources are turning up in a diverse range of records. In this thesis, a state-of-the-art global hydrological model (GHM) and global water demand model were developed and eventually coupled to quantify and distinguish human and climate impacts on surface freshwater and groundwater resources. The thesis is composed of three major parts: Part 1. Human and climate impacts on surface freshwater resources; Part 2. Global assessment of groundwater resources; Part 3. Integrated modeling and indicators of global water resources. The thesis first explores the human and climate impacts on seasonal surface freshwater resources by forcing the global hydrological model PCR‐GLOBWB with daily meteorological fields and by calculating global monthly water demands with the effects of socio-economic and land use change. Increased water demand was found to be a decisive factor for heightened water stress in various regions, while climate variability is often a main determinant of extreme events. Over Europe, North America and Asia, severe hydrological drought conditions are driven by increasing consumptive water use rather than to be merely induced by climate variability; the magnitude of droughts intensified by 10-500%. Next, the thesis assesses global groundwater resources by estimating groundwater recharge and abstraction. Global groundwater depletion was found to triple in size over the last 50 years, and contributes ~20% to irrigation water supply. Groundwater stress was then assessed using newly developed indicators considering groundwater contribution to environment. The global groundwater footprint was found to be 3.5 times the actual area of aquifers driven by a few heavily overexploited aquifers. The aquifer stress indicator revealed that ~8% of transboundary aquifers are currently stressed due to human overexploitation. Importantly, groundwater depletion was found to be an important contributor to sea-level rise and is likely to dominate over those of other terrestrial water sources. The contribution of groundwater depletion to sea-level increased by more than ten-fold over 1900-2000, and is projected to increase further by 2050. In the final part of this thesis, an improved modeling framework that dynamically simulates daily water use per source per sector was developed. Human impacts on terrestrial water storage signals were evident in the validation with GRACE satellite observation, altering the seasonal and inter-annual variability over heavily regulated and intense irrigated basins. The newly developed model together with other six state-of-the-art GHMs was applied to simulate future irrigation water demand using the latest CMIP5 climate projections. The increase in irrigation demand varies substantially depending on the degree of global warming and associated regional precipitation changes. GHM dominates the uncertainty throughout the century, but GCM uncertainty substantially increases from the mid-century. To comprehensively assess global water resources, an improved approach was introduced. The Green Water Stress Index is capable of reproducing varying degrees of green water stress conditions, reflecting a multi-decadal climate variability. The Blue Water Sustainability Index revealed an increasing trend of water consumed from nonsustainable surface water and groundwater resources (~30%) worldwide

Weet wat je meet en meet wat je niet weet

We can only relate individual measurements meaningfully if we have a model of the system where the measurements come from. This can be a simple conceptual model, (is the groundwater dynamics a smooth slow progress as at the Veluwe, or can the groundwater level be quite different from week to week), it can be a statistical model, where assumptions are made on probability distributions and correlation in space and time, but also a complex numerical model can describe the relationship between the observations. Without prior knowledge of the system, it is not possible to create a adequate monitoring. So we must have some knowledge about the system we monitor: KNOW WHAT YOU OBSERVE

Dynamic visualisation of spatial and spatio-temporal probability distribution functions

In this paper we will present and demonstrate aguila, a tool for interactive dynamic visual analysis of gridded data that come as spatial or spatio-temporal probability distribution functions. Probability distribution functions are analysed in their cumulative form, and we can choose to visualize exceedance probabilities given a threshold value, or its inverse, the quantile values. Threshold value or quantile level can be modified dynamically. In addition, classified probabilities in terms of (1-alpha)x100% (e.g. 95%) confidence or prediction intervals can be visualized for a given threshold value. Different modelling scenarios can be compared by organizing maps in a regular lattice, where individual maps (scenarios) are shown in panels that share a common legend and behave identically to actions like zooming, panning, and identifying (querying) cells. Variability over time is incorporated by showing sets of maps as animated movies. We will demonstrate this tool using sea floor sediment quality predictions under different spatial aggregation scenarios (block sizes), covering the Dutch part of the North Sea. The tool is freely available in binary and source code form; source code is distributed under the Gnu GPL; grid maps are read from disc through the GDAL library, or from memory as e.g. in an R session

Towards integrated inundation modelling: Development, testing, and application of a framework for model coupling across scales

Globally, various models have been developed to simulate flood events, with each having its specific advantages and disadvantages. This can have significant impact on the accuracy of model output. To advance the state of current global flood modelling and move towards more integrated approaches, I have developed a computational framework allowing for coupling a suite of models, model components, and processes. Even though the framework merely focuses on riverine flooding at the moment, it is designed in a modular way and therefore it is possible to add even more models. This way, it will be possible to move even further towards integrated inundation modelling