Yaonan Zhang, Yingpin Long, Guohui Zhao, Yufang Min, Jianfang Kang, L. Luo, Zhenfang He, Yang Wang
{"title":"生态水文模拟研究的e-Science环境","authors":"Yaonan Zhang, Yingpin Long, Guohui Zhao, Yufang Min, Jianfang Kang, L. Luo, Zhenfang He, Yang Wang","doi":"10.1109/eScience.2013.37","DOIUrl":null,"url":null,"abstract":"Comprehensive integrated research on ecological and hydrological processes and the simulation of river basin environments are critical foundations for decision making by governments and river-basin managers. The demand for a holistic understanding of environmental systems such as river basins is increasing. Eco-hydrological research needs two types of monitoring platforms to access and collect data from basins: a modeling platform to support access, select, and run models online, and build new models with the collected data, and a manipulation platform to generate forcing data, run models, and visualize the results. Consequently, we developed an e-science environment framework comprising three platforms - a monitoring platform, a model platform, and a manipulation platform. The framework allows automatic data transmission, storage, management, analysis, model management, simulation, computing, and result visualization. The e-science environment integrates land surface models such as Simplified Simple Biosphere model, the Revised Simple Biosphere model and WRF, hydrological models such as SWAT and TOPMODEL, data assimilation filters including such as Kalman filter algorithm, and several tools and methods for dealing with data, principally artificial neural networks and Markov chains. We demonstrate the application of the framework that uses an SSIB land surface model ensemble Kalman filter to improve evapotranspiration, soil moisture, and ground temperature simulation in the Heihe inland river basin. The approach proves suitable for environmental simulation for inland river research.","PeriodicalId":325272,"journal":{"name":"2013 IEEE 9th International Conference on e-Science","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An e-Science Environment for Ecological and Hydrological Simulation Research\",\"authors\":\"Yaonan Zhang, Yingpin Long, Guohui Zhao, Yufang Min, Jianfang Kang, L. Luo, Zhenfang He, Yang Wang\",\"doi\":\"10.1109/eScience.2013.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Comprehensive integrated research on ecological and hydrological processes and the simulation of river basin environments are critical foundations for decision making by governments and river-basin managers. The demand for a holistic understanding of environmental systems such as river basins is increasing. Eco-hydrological research needs two types of monitoring platforms to access and collect data from basins: a modeling platform to support access, select, and run models online, and build new models with the collected data, and a manipulation platform to generate forcing data, run models, and visualize the results. Consequently, we developed an e-science environment framework comprising three platforms - a monitoring platform, a model platform, and a manipulation platform. The framework allows automatic data transmission, storage, management, analysis, model management, simulation, computing, and result visualization. The e-science environment integrates land surface models such as Simplified Simple Biosphere model, the Revised Simple Biosphere model and WRF, hydrological models such as SWAT and TOPMODEL, data assimilation filters including such as Kalman filter algorithm, and several tools and methods for dealing with data, principally artificial neural networks and Markov chains. We demonstrate the application of the framework that uses an SSIB land surface model ensemble Kalman filter to improve evapotranspiration, soil moisture, and ground temperature simulation in the Heihe inland river basin. 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An e-Science Environment for Ecological and Hydrological Simulation Research
Comprehensive integrated research on ecological and hydrological processes and the simulation of river basin environments are critical foundations for decision making by governments and river-basin managers. The demand for a holistic understanding of environmental systems such as river basins is increasing. Eco-hydrological research needs two types of monitoring platforms to access and collect data from basins: a modeling platform to support access, select, and run models online, and build new models with the collected data, and a manipulation platform to generate forcing data, run models, and visualize the results. Consequently, we developed an e-science environment framework comprising three platforms - a monitoring platform, a model platform, and a manipulation platform. The framework allows automatic data transmission, storage, management, analysis, model management, simulation, computing, and result visualization. The e-science environment integrates land surface models such as Simplified Simple Biosphere model, the Revised Simple Biosphere model and WRF, hydrological models such as SWAT and TOPMODEL, data assimilation filters including such as Kalman filter algorithm, and several tools and methods for dealing with data, principally artificial neural networks and Markov chains. We demonstrate the application of the framework that uses an SSIB land surface model ensemble Kalman filter to improve evapotranspiration, soil moisture, and ground temperature simulation in the Heihe inland river basin. The approach proves suitable for environmental simulation for inland river research.