## 1 Introduction  
In recent decades, climate change has led to an increase in the number of natural disasters both around the world and in East Kazakhstan [1, 2, 3]. These processes increase the risk of avalanches in winter and floods in spring, which requires new solutions for their monitoring. Thus, an automated avalanche hazard monitoring system is being created for Eastern Kazakhstan. The initial data for modeling and their results for flood forecasting can be included in the existing database as a development and continuation of the project [4]. Monitoring the flood situation along with avalanche monitoring can complement the regional system for monitoring natural disasters. According to statistics from the Department of Emergency Situations of the East Kazakhstan region for 2023 [5], the level of potential flood threats has decreased in a number of areas. In total, there are about 71 settlements in East Kazakhstan that are prone to flooding. In 15 settlements, the threat has been completely removed and minimized in 46. Despite this, floods, as a natural disaster, remain a pressing problem. During the flood period, increased attention is paid to the following areas of the East Kazakhstan region due to the high amount of danger: Altai, Glubokoe, Ulan, Shemonaikha, Tarbagatai, Katon-Karagay, and Zaysan. Taking into account the freezing of the soil and the height of the snow cover, with a sharp increase in temperature and heavy precipitation, the flood situation may worsen. The flood hazard monitoring system helps to minimize losses from seasonal floods [5], and it is also planned to integrate the flood hazard system and the snow monitoring system. At the same time, the problems of managing and monitoring river systems have become especially relevant due to the increasing anthropogenic load and increasing demand for water resources. Effective management of river flows requires complex information and analytical systems capable of promptly processing and providing data for decision-making. The basis of such systems is modeling tools that allow for highly accurate predictions of the behavior of river flows under various conditions. Due to the widespread occurrence of the danger of floods in almost every country with the necessary scientific and technical potential, the territory of which is exposed to this danger, there are teams or even entire institutes working purposefully to study and forecast river flows and design and build protective engineering structures. Currently, methods of numerical modeling of river flows based on various mathematical models are widely used. Many researchers determine the flood zone based on hydrodynamic modeling using modern HEC-RAS 5.0 software. In [6], a model based on satellite data on precipitation was used, while hydrodynamic modeling in RAS 5.0.5 and HEC-HMS 5.0 software is used, which allows for simulating flow regimes and hydrological characteristics. The modeling results made it possible to predict the increase in the water level in two river tributaries within the Citarum River watershed. In the work by the authors [PERSON], [PERSON], [PERSON] et al. [7], for flood modeling, HEC-RAS 5.0 with Q25y and Q50y is also used, and a model is built on the basis of data obtained as a result of an analysis of precipitation data from 9 observation stations. In a study by the authors [PERSON] and [PERSON]. [8], methods of hydrological modeling of watersheds are also applied for flood forecasting. In addition, a digital elevation model (DEM) is considered as an input variable, which, due to the resolution (in the range of 30 m to 500 m), significantly affects the accuracy of flood modeling. The modeling is based on a hydrological and hydraulic analysis using the HEC-RAS 4.1.0 program. Researchers from Indonesia [9] studied precipitation (rain) data obtained from Pengelolaan Number Daya Air (PSDA) and the spatial data of Brebes County from 2009 to 2018, and by normalizing these data (using lognormal distribution), the probability of flooding of the county was calculated.