Price: 0
Number of applications: 2
14.03.25 (inclusive)
Interaction and involvement in case management
MVP
ICT tasks
Agriculture
Digital Security Technologies
Purpose and description of task (project)
Annual floods pose a serious threat to the population, agriculture, infrastructure and the environment. Traditional forecasting methods often do not take into account all factors, which leads to inaccurate forecasts, lack of timely measures and significant losses. The purpose of the case is to develop a tool for flood forecasting and modeling their consequences using modern data processing, modeling, and machine learning technologies. Tasks: 1. Flood forecasting: • Build a model to predict the probability of flooding in given geographical locations. • Take into account meteorological data (temperature, precipitation, snow cover, etc.). • Take into account hydrological data (river level, flow velocity, reservoir volume, etc.). 2. Impact modeling: • Simulate flood zones in case of flooding, taking into account the terrain. • Assess the impact of floods on the population, roads, buildings, and agricultural land. 3. Development of an alert system: • Create an interface or tool to display the forecast and risk areas. • Provide notification for various user groups (authorities, public, enterprises).
Mobile app
Data: • Meteorological data: average annual temperatures, precipitation, snow cover data, weather forecast. • Hydrological data: river levels, current velocity, reservoir volumes, and flood data from previous years. • Geographical data: terrain, topographic maps, population density, infrastructure. • Socio-economic data: data on population distribution, infrastructure facilities, and economic losses from past floods. Expected results 1. Predictive model: • Forecast of flood probability for the coming weeks/months. • The level of forecast accuracy (model evaluation metrics: RMSE, Precision, Recall, etc.). 2. Map of risk zones: • Visualization of potential flooding areas. • Threat level by category: low, medium, high. 3. Prototype of the system: • An easy-to-use platform or application. • The ability to configure parameters (for example, region, time period). • Notification system. Evaluation criteria 1. Accuracy of the forecasting model (30%). 2. Efficiency of modeling flood zones (25%). 3. Functionality and usability of the prototype system (20%). 4. Quality of data analysis and consideration of risk factors (15%). 5. Innovative approach and applicability of the solution (10%). You can use any libraries and tools for data analysis (Python, R, GIS systems, etc.). For models, you can use machine learning algorithms, as well as physical and mathematical approaches.
Flood forecasting
Kustavletov Sanzhar Maratovich
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