A5075467957- Hydrology and Watershed Management Studies
- Flood Risk Assessment and Management
- Hydrological Forecasting Using AI
- Environmental Monitoring and Data Management
- Scientific Research Methodologies and Applications
- Research Data Management Practices
- Cryospheric studies and observations
- Water Resources and Management
Institute of Water Problems
2017-2021
With more machine learning methods being involved in social and environmental research activities, we are addressing the role of available information for model training performance. We tested abilities several models short-term hydrological forecasting by inferring linkages with all predictors or only those pre-selected a hydrologist. The used this study were multivariate linear regression, M5 tree, multilayer perceptron (MLP) artificial neural network, long memory (LSTM) model. two river...
This paper considers the main principles and technologies used in developing operational modeling system for Ussuri River Basin of 24,400 km2 based on automated hydrological monitoring data management (ASHM), physical-mathematical model with distributed parameters ECOMAG (ECOlogical Model Applied Geophysics) numerical mesoscale atmosphere WRF (Weather Research Forecasting Model). The is designed as a freely combined tool that allows flexible changing forecasting informational components....
The paper addresses prospects for short-term (from 1 to 7 days) forecasting of river streamflow runoff based on several machine learning methods: multiple linear regression (LM) model, a multilayer perceptron (MLP) artificial neural network, and recurrent network with long memory (LSTM). Methods expanding the set predictors model construction are proposed, possibility random shuffling time-series calibration verification assessed. object study is small Central Russia – Protva (Spas-Zagorie...