Volume 9 Issue 1
Identification of Apple Leaf Diseases Based on Deep Convolutional Neural Networks
Bin Liu, Yun Zhang, DongJian He and Yuxiang Li
1Water Problems Institute, Russian Academy of Sciences, Gubkina Street, 3, Moscow 119333, Russia
2Pacific Institute of Geography, Far East Branch, Russian Academy of Sciences; Radio, 7, Vladivostok 690041, Russia
3Far Eastern Regional Hydrometeorological Research Institute, Fontannaya Street, 24, Vladivostok 690600, Russia
*Author to whom correspondence should be addressed.
Abstract
This paper considers the main principles and technologies used in developing the operational modeling system for the Ussuri River Basin of 24,400 km2 based on the automated system of hydrological monitoring and data management (ASHM), the physical-mathematical model with distributed parameters ECOMAG (ECOlogical Model for Applied Geophysics) and the numerical mesoscale atmosphere model WRF (Weather Research and Forecasting Model). The system is designed as a freely combined tool that allows flexible changing of the forecasting and informational components. The technology of inter-model and cross-platform interoperability is based on the use of the Simple Object Access Protocol (SOAP) web services and the Open Geospatial Consortium Open Modelling Interface (OGC OpenMI) standard. The system demonstrates good performance in short-term forecast of rainfall floods and reproduces complex spatio-temporal structure for the runoff formation during extreme rainfall.
Keywords:hydrological forecasting; flash flood; hydrological monitoring system; flood awareness; ECOMAG model