Developing a cloud-based toolbox for sensitivity analysis of a water quality model
暂无分享,去创建一个
Kyung Hwa Cho | Jung Min Ahn | Sang-Soo Baek | Mayzonee Ligaray | Yong Sung Kwon | Joong-Hyuk Min | Soobin Kim | Jong Cheol Pyo | K. Cho | J. Ahn | Mayzonee Ligaray | Sang-Soo Baek | J. Pyo | J. Min | Y. Kwon | Soobin Kim
[1] Andrew Parker,et al. Integrated hydrodynamic and water quality modeling system to support nutrient total maximum daily load development for Wissahickon Creek, Pennsylvania , 2006 .
[2] Zongxue Xu,et al. Prediction of algal blooming using EFDC model: Case study in the Daoxiang Lake , 2011 .
[3] Jiyoung Lee,et al. Harmful algal blooms and liver diseases: focusing on the areas near the four major rivers in South Korea , 2019, Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews.
[4] P. Ashton,et al. Agricultural impacts on water quality and implications for virtual water trading decisions , 2009 .
[5] K. Abbaspour,et al. Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT , 2007 .
[6] E. Marañón,et al. Nutrient limitation suppresses the temperature dependence of phytoplankton metabolic rates , 2018, The ISME Journal.
[7] Modelling of suspended sediment in a weir reach using EFDC model. , 2016, Water science and technology : a journal of the International Association on Water Pollution Research.
[8] A. Howard,et al. Modelling the growth and movement of cyanobacteria in river systems. , 2006, The Science of the total environment.
[9] Xiao Ma,et al. Assessment and analysis of non-point source nitrogen and phosphorus loads in the Three Gorges Reservoir Area of Hubei Province, China. , 2011, The Science of the total environment.
[10] Raghavan Srinivasan,et al. A parallelization framework for calibration of hydrological models , 2012, Environ. Model. Softw..
[11] J. R. Kramer,et al. Evaluating modelling uncertainty for model selection , 2001 .
[12] T. J. Lah,et al. The Four Major Rivers Restoration Project of South Korea , 2015 .
[13] Jun Xia,et al. An efficient integrated approach for global sensitivity analysis of hydrological model parameters , 2013, Environ. Model. Softw..
[14] D. Anderson,et al. Progress in understanding harmful algal blooms: paradigm shifts and new technologies for research, monitoring, and management. , 2012, Annual review of marine science.
[15] R. Vogel,et al. Optimal Location of Infiltration-Based Best Management Practices for Storm Water Management , 2005 .
[16] Hyuk Lee,et al. Optimizing low impact development (LID) for stormwater runoff treatment in urban area, Korea: Experimental and modeling approach. , 2015, Water research.
[17] Francesca Pianosi,et al. A Matlab toolbox for Global Sensitivity Analysis , 2015, Environ. Model. Softw..
[18] Yiping Li,et al. Parameter uncertainty and sensitivity analysis of water quality model in Lake Taihu, China , 2018 .
[19] E. Roberts,et al. The influence of changes in nitrogen:silicon ratios on diatom growth dynamics. , 2004 .
[21] Amir Sadeghian,et al. Improving in-lake water quality modeling using variable chlorophyll a/algal biomass ratios , 2018, Environ. Model. Softw..
[22] Michel Coste,et al. Seasonal succession of diatoms and Chlorophyceae in the drainage network of the Seine River: Observation and modeling , 1995 .
[23] J. Grobbelaar,et al. The influence of nitrogen and phosphorus on algal growth and quality in outdoor mass algal cultures , 1987 .
[24] Y. Lim,et al. Suspended sediment source tracing at the Juksan Weir in the Yeongsan River using composite fingerprints , 2019, Quaternary International.
[25] Carl F. Cerco,et al. Three‐Dimensional Eutrophication Model of Chesapeake Bay , 1993 .
[26] C. Reynolds. Phytoplankton assemblages and their periodicity in stratifying lake systems , 1980 .
[27] Yang Hong,et al. Fast hydrological model calibration based on the heterogeneous parallel computing accelerated shuffled complex evolution method , 2018 .
[28] V. L. Johnson,et al. Comparative impacts of stormwater runoff on water quality of an urban, a suburban, and a rural stream , 2009, Environmental monitoring and assessment.
[29] M. Kim,et al. A convolutional neural network regression for quantifying cyanobacteria using hyperspectral imagery , 2019, Remote Sensing of Environment.
[30] R. Srinivasan,et al. A global sensitivity analysis tool for the parameters of multi-variable catchment models , 2006 .
[31] Jonathan L. Goodall,et al. Calibration of watershed models using cloud computing , 2012, 2012 IEEE 8th International Conference on E-Science.
[32] D. Seo,et al. Analysis and modeling of algal blooms in the Nakdong River, Korea , 2018 .
[33] D. Seo,et al. Algal bloom prediction of the lower Han River, Korea using the EFDC hydrodynamic and water quality model , 2017 .
[34] A. Stephen McGough,et al. Flood modelling for cities using Cloud computing , 2013, Journal of Cloud Computing: Advances, Systems and Applications.
[35] José Ferrer,et al. An improved sampling strategy based on trajectory design for application of the Morris method to systems with many input factors , 2012, Environ. Model. Softw..
[36] Francesca Pianosi,et al. Global Sensitivity Analysis of environmental models: Convergence and validation , 2016, Environ. Model. Softw..
[37] David Michael King,et al. Morris method of sensitivity analysis applied to assess the importance of input variables on urban water supply yield – A case study , 2013 .
[38] M. Nguyen,et al. Phosphorus runoff from agricultural land and direct fertilizer effects: a review. , 2004, Journal of environmental quality.
[39] R. Hecky,et al. Nutrient limitation of phytoplankton in freshwater and marine environments: A review of recent evidence on the effects of enrichment1 , 1988 .
[40] L. May,et al. The phosphorus budget of the Thame catchment, Oxfordshire, UK: 1. Mass balance. , 2002, The Science of the total environment.
[41] S. Tarantola,et al. Reduced‐complexity modeling of braided rivers: Assessing model performance by sensitivity analysis, calibration, and validation , 2013 .
[42] Cheng Wang,et al. Applications integration in a hybrid cloud computing environment: modelling and platform , 2013, Enterp. Inf. Syst..
[43] Jim W. Hall,et al. Sensitivity analysis of environmental models: A systematic review with practical workflow , 2014, Environ. Model. Softw..
[44] Enrique Campbell,et al. Cloud-based decision making in water distribution systems , 2014 .
[45] Hans-Georg Frede,et al. Comparison of two different approaches of sensitivity analysis , 2002 .
[46] J. Passarge,et al. Modelling vertical migration of the cyanobacterium Microcystis , 1997, Hydrobiologia.
[47] Willy Bauwens,et al. Multi-variable sensitivity and identifiability analysis for a complex environmental model in view of integrated water quantity and water quality modeling. , 2012, Water science and technology : a journal of the International Association on Water Pollution Research.
[48] R. Evert,et al. Photosynthesis, Light, and Life , 2013 .
[49] P J A Kleinman,et al. A model for phosphorus transformation and runoff loss for surface-applied manures. , 2007, Journal of environmental quality.
[50] Pei Zhao,et al. Bayesian framework of parameter sensitivity, uncertainty, and identifiability analysis in complex water quality models , 2018, Environ. Model. Softw..
[51] Max D. Morris,et al. Factorial sampling plans for preliminary computational experiments , 1991 .
[52] Chen Sun,et al. Global sensitivity analysis and calibration of parameters for a physically-based agro-hydrological model , 2016, Environ. Model. Softw..
[53] Colin S. Reynolds,et al. Towards a functional classification of the freshwater phytoplankton , 2002 .
[54] Yakov A. Pachepsky,et al. Simulating seasonal variability of phytoplankton in stream water using the modified SWAT model , 2017, Environ. Model. Softw..
[55] Srikumar Venugopal,et al. On the Efficiency of Executing Hydro-environmental Models on Cloud☆ , 2016 .
[56] Anthony M. Castronova,et al. Calibration of SWAT models using the cloud , 2014, Environ. Model. Softw..
[57] S. Fried,et al. Nitrate and phosphate levels positively affect the growth of algae species found in Perry Pond , 2012 .
[58] Huaicheng Guo,et al. Global sensitivity analysis of a three-dimensional nutrients-algae dynamic model for a large shallow lake , 2016 .
[59] C. Gobler,et al. The rise of harmful cyanobacteria blooms: The potential roles of eutrophication and climate change , 2012 .
[60] Peter A. Vanrolleghem,et al. Sensitivity analysis for hydrology and pesticide supply towards the river in SWAT , 2005 .
[61] Zhou Zuhao,et al. Analysis of SWAT 2005 Parameter Sensitivity with LH-OAT Method , 2010 .
[62] Francesca Pianosi,et al. Matlab/R workflows to assess critical choices in Global Sensitivity Analysis using the SAFE toolbox , 2019, MethodsX.
[63] Priyanka Singh,et al. Effect of temperature and light on the growth of algae species: A review , 2015 .
[64] A. Weerts,et al. Ensemble data assimilation methods for improving river water quality forecasting accuracy. , 2019, Water research.
[65] Stefan Kollet,et al. Introduction of a web service for cloud computing with the integrated hydrologic simulation platform ParFlow , 2012, Comput. Geosci..
[66] Andrea Saltelli,et al. An effective screening design for sensitivity analysis of large models , 2007, Environ. Model. Softw..
[67] Karl-Erich Lindenschmidt,et al. The effect of complexity on parameter sensitivity and model uncertainty in river water quality modelling , 2006 .
[68] Patrick M. Reed,et al. Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models , 2013 .
[69] S. Liang,et al. Spatiotemporal variability and environmental factors of harmful algal blooms (HABs) over western Lake Erie , 2017, PloS one.
[70] Zhu Ji. Impact of Rapid Urbanization on Water Quality and Related Mitigation Options in Taihu Lake Area , 2003 .
[71] M. Temimi,et al. Monitoring HABs in the shallow Arabian Gulf using a qualitative satellite-based index , 2016 .
[72] Emanuele Borgonovo,et al. Model emulation and moment-independent sensitivity analysis: An application to environmental modelling , 2012, Environ. Model. Softw..