Nurbek Saparkhojayev
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Nurbek Saparkhojayev has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Irina Dyomina
School of Digital Technologies and Artificial Intelligence, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk 070000, Kazakhstan
1 shared publication - Natalya Denissova
Department of Information Technology, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk 070000, Kazakhstan
1 shared publication - Olga Petrova
D. Serikbayev East Kazakhstan technical university, Ust-Kamenogorsk, Kazakhstan
1 shared publication - Ruslan Chettykbayev
School of Digital Technologies and Artificial Intelligence, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk 070000, Kazakhstan
1 shared publication
Latest Publications
- Open Access
- 19 July 2025
- Published by MDPI AG in Applied Sciences
- Vol. 15 (14) , 8050
Integration of Space and Hydrological Data into System of Monitoring Natural Emergencies (Flood Hazards)
Flood hazards have increasingly threatened the East Kazakhstan region in recent decades due to climate change and growing anthropogenic pressures, leading to more frequent and severe flooding events. This article considers an approach to modeling and forecasting river runoff using the example of the small Kurchum River in the East Kazakhstan region. The main objective of this study was to evaluate the numerical performance of the flood hazard model by comparing simulated flood extents with observed flood data. Two types of data were used as initial data: topographic data (digital elevation models and topographic maps) and hydrological data, including streamflow time series from stream gauges (hourly time steps) and lateral inflows along the river course. Spatially distributed rainfall forcing was not applied. To build the model, we used the software packages of HEC-RAS version 5.0.5 and MIKE version 11. Using retrospective data for 3 years (2019–2021), modeling was performed, the calculated boundaries of possible flooding were obtained, and the highest risk zones were identified. A dynamic map of depth changes in the river system is presented, showing the process of flood wave propagation, the dynamics of depth changes, and the expansion of the flood zone. Temporal flood inundation mapping and performance metrics were evaluated for each individual flood event (2019, 2020, and 2021). The simulation outcomes closely correlate with actual flood events. The assessment showed that the model data coincide with the real ones by 91.89% (2019), 89.09% (2020), and 95.91% (2021). The obtained results allow for a clarification of potential flood zones and can be used in planning measures to reduce flood risks. This study demonstrates the importance of an integrated approach to modeling, combining various software packages and data sources.
- 19 July 2025
- Published by MDPI AG in Applied Sciences
- Vol. 15 (14) , 8050
Open AccessIntegration of Space and Hydrological Data into System of Monitoring Natural Emergencies (Flood Hazards)
Flood hazards have increasingly threatened the East Kazakhstan region in recent decades due to climate change and growing anthropogenic pressures, leading to more frequent and severe flooding events. This article considers an approach to modeling and forecasting river runoff using the example of the small Kurchum River in the East Kazakhstan region. The main objective of this study was to evaluate the numerical performance of the flood hazard model by comparing simulated flood extents with observed flood data. Two types of data were used as initial data: topographic data (digital elevation models and topographic maps) and hydrological data, including streamflow time series from stream gauges (hourly time steps) and lateral inflows along the river course. Spatially distributed rainfall forcing was not applied. To build the model, we used the software packages of HEC-RAS version 5.0.5 and MIKE version 11. Using retrospective data for 3 years (2019–2021), modeling was performed, the calculated boundaries of possible flooding were obtained, and the highest risk zones were identified. A dynamic map of depth changes in the river system is presented, showing the process of flood wave propagation, the dynamics of depth changes, and the expansion of the flood zone. Temporal flood inundation mapping and performance metrics were evaluated for each individual flood event (2019, 2020, and 2021). The simulation outcomes closely correlate with actual flood events. The assessment showed that the model data coincide with the real ones by 91.89% (2019), 89.09% (2020), and 95.91% (2021). The obtained results allow for a clarification of potential flood zones and can be used in planning measures to reduce flood risks. This study demonstrates the importance of an integrated approach to modeling, combining various software packages and data sources.