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Communication Papers of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS)

Annals of Computer Science and Information Systems, Volume 41

Predictive System of the Water Deficit Analysis for the Black Sea Lowland (an example of the Kherson Region)

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DOI: http://dx.doi.org/10.15439/2024F1140

Citation: Communication Papers of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS), M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 41, pages 95–104 ()

Full text

Abstract. Developing a predictive system for water deficit analysis in the Black Sea Lowland, especially in climate change, involves integrating various data sources, modeling techniques, and technological tools to forecast water availability and demand. The analysis of the change in moisture deficit in the Kherson region is provided for the period from 1955 to 2022. The description of with temperature gradients across the Kherson region is provided. The distribution of precipitation throughout the years in terms of quantity and intensity is provided. As part of the Black Sea Lowland, the Kherson region is critically important for southern Ukraine's agriculture and water security. Given the region's reliance on irrigation and the challenges posed by climate change, developing a predictive system for water deficit analysis is essential. Such a system can help stakeholders make informed decisions to ensure sustainable water management and mitigate the adverse effects of water scarcity.

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