## 1 Introduction
The authors of [18] digitized the maps of their study area using the AutoCAD Civil 3D 2020 program, and cross-sections were made by obtaining digital elevation models of the region. The obtained cross-sections were defined in the HEC-RAS software, and the floodplain channel's hydraulic characteristics and water surface profiles for the Q25, Q50,Q100, and Q500 recurring floods were determined, and a one-dimensional analysis of the Tigris River floodplain was carried out. Thus, many studies show a variety of approaches to solving problems, but no single solution has been developed. Most researchers only consider meteorological data and river topology, but when modeling a particular region of the world, it is necessary to consider broader datasets. This study is among the first to integrate spatial remote sensing data (Sentinel-1 and Sentinel-2) with hydrodynamic modeling based on the Saint-Venant equations for East Kazakhstan. This integration significantly improves the accuracy and timeliness of flood risk predictions and enhances the capabilities of the regional flood hazard monitoring system. In this study, we applied a subset of these data, including satellite imagery (Sentinel-1 and Sentinel-2), digital elevation models, topographic maps, and streamflow data from gauging stations. Snow storage and meteorological data were collected and maintained in the avalanche hazard monitoring subsystem, which is part of the integrated regional monitoring system. The objective of this study was to evaluate the numerical performance of the flood hazard model by comparing simulated flood extents with observed flood data based on space monitoring data and hydrodynamic modeling of river flows using the MIKE software package, with subsequent scaling of the obtained results to assess flood risks in a larger river network of the East Kazakhstan region. This study simulated flooding on one typical small river and extrapolated the obtained modeling results to a larger river network. This approach is feasible and important, because small rivers can serve as representative models for hydrodynamic processes in the region. Their simpler geometry and relatively better availability of data allow for robust calibration and validation of the model, which can then be efficiently scaled to larger and more complex river systems, particularly in regions where hydrological and topographical data for large networks are limited. The relevance of this work lies in the study conducted to forecast and model the river runoff of the small Kurchum River in the East Kazakhstan region and the extension of the obtained data to the river network, and it is shown how the integration of various data allows for more accurate modeling of flood developments and clarifications of flooded areas. Modeling flood risks for small rivers is a complex task, since the amount of input data is limited. The researchers of [19] were engaged in solving similar problems using the example of a small river (the Tarna River) from 1990 to 2019. Their assessment focused on modeling, as well as model calibration and validation using event-based time series data under poor data conditions. The authors of [19] did not consider the problem of extending their model to a river network. Two types of data were considered and applied to model the river flow: topographic data (digital elevation models (DEMs), topographic maps, a hydrographic network, floodplain zones, and adjacent areas) and hydrological data, including streamflow time series from stream gauges with an hourly time step, flood hydrographs, and lateral inflow data. Spatially distributed rainfall forcing was not applied. At the same time, flood mapping is required to determine flood characteristics such as flow velocity, flood depth, and degree of flooding; this is a prerequisite for flood management planning. Using HEC-RAS version 5.0.5 and an example of flood calculations for one river allowed for analyzing flooding as a result of a model flood.