The Journal of
the Korean Society on Water Environment

The Journal of
the Korean Society on Water Environment

Bimonthly
  • ISSN : 2289-0971 (Print)
  • ISSN : 2289-098X (Online)
  • KCI Accredited Journal

Editorial Office

References

1 
Abdi B., Bozorg-Haddad O., Loáiciga H. A., 2020, Analysis of the effect of inputs uncertainty on riverine water temperature predictions with a Markov chain Monte Carlo (MCMC) algorithm, Environmental Monitoring and Assessment, Vol. 192, No. 2, pp. 1-15Google Search
2 
Ahmadisharaf E., Camacho R. A., Zhang H. X., Hantush M. M., Mohamoud Y. M., 2019, Calibration and validation of watershed models and advances in uncertainty analysis in TMDL studies, 03119001., Journal of Hydrologic Engineering, Vol. 24, No. 7DOI
3 
Bayes T., 1763, An essay towards solving a problem in the doctrine of chances, Philosophical Transactions of the Royal Society of London, Vol. 53, pp. 370-418DOI
4 
Bishop C. M., 2006, Pattern recognition and machine learning, New York, Springer.Google Search
5 
Box G., Cox D., 1964, An analysis of transformations, Journal of the Royal Statistical Society: Series B (Methodological), Vol. 26, pp. 211-243DOI
6 
Camacho R. A., Martin J. L., MacAnally W., Días-Ramirez J., Rodriguez H., Sucsy P., Zhang S., 2015, A comparison of bayesian methods for uncertainty analysis in hydrauic and hydrodynamic modeling, Journal of the American Water Resources Association, Vol. 51, No. 5, pp. 1372-1393DOI
7 
Campbell E., Fox D., Bates B., 1999, A bayesian approach to parameter estimation and pooling in nonlinear flood event models, Water Resources Research, Vol. 35, pp. 211-220Google Search
8 
Carpenter T. M., Georgakakos K. P., 2004, Impacts of parametric and radar rainfall uncertainty on the ensemble streamflow simulations of a distributed hydrological model, Journal of Hydrology, Vol. 298, pp. 202-221DOI
9 
Choi H. S., Parameter estimation of SWAT model using SWAT-CUP in Seom-river experimental watershed, [Korean Literature], Journal of the Korean Society of Civil Engineers, Vol. 33, No. 2, pp. 529-536DOI
10 
Choi J., Kim R., Kim S., 2020, Development of distributed one-dimensional hydrologic model based on soil moisture simulation, [Korean Literature]., Journal of Korean Society on Water Environment, Vol. 36, No. 3, pp. 229-244DOI
11 
Chowdhury S., Sharma A., 2007, Mitigating parameter bias in hydrological modelling due to uncertainty in covariates, Journal of Hydrology, Vol. 340, pp. 197-204DOI
12 
Chung S. W., Gassman P. W., Kramer L. A., Williams J. R., Gu R. R., 1999, Validation of EPIC for two watersheds in southwest Iowa, Journal of Environmental Quality, Vol. 28, No. 3, pp. 971-979DOI
13 
Engeland K., Xu C. Y., Gottschalk L., 2005, Assessing Uncertainties in a conceptual water balance model using Bayesian methodology, Hydrological Sciences Journal, Vol. 50, No. 1, pp. 45-63Google Search
14 
Georgakakos K. P., Seo D. J., Gupta H., Schaake J., Butts M. B., 2004, Towards the characterization of streamflow simulation uncertainty through multimodel ensembles, Journal of Hydrology, Vol. 298, pp. 222-241DOI
15 
Green C. H., Tomer M. D., Di Luzio M., Arnold J. G., 2006, Hydrologic evaluation of the soil and water assessment tool for a lager tile-drained watershed in Iowa, Transactions of the American Society of Agricultural and Biological Engineers, Vol. 49, No. 2, pp. 413-422Google Search
16 
Gupta H. V., Kling H., Yilmaz K. K., Martinez Z. F., 2009, Decomposition of the mean squared error and NSE performance criteria: implications for improving hydrological modeling, Journal of Hydrology, Vol. 377, pp. 80-91DOI
17 
Han F., Zheng Y., 2016, Multiple-response Bayesian calibration of watershed water quality models with significant input and model structure errors, Advances in Water Resources, Vol. 88, pp. 109-123Google Search
18 
Harmon R., Challenor P., 1997, A markov chain monte carlo method for estimation and assimilation into models, Ecological Modeling, Vol. 101, pp. 41-59Google Search
19 
Hastings W. K., 1970, Monte carlo sampling methods using markov chains and their application, Biometrika, Vol. 57, pp. 97-109Google Search
20 
Hensen J. L. M., Lamberts R., 2012, Building performance simulation for design and operationGoogle Search
21 
Jia H., Xu T., Liang S., Zhao P., Xu C., 2018, Bayesian framework of parameter sensitivity, uncertainty, and identifiability analysis in complex water quality models, Environmental Modelling & Software, Vol. 104, pp. 13-26Google Search
22 
Comparing prediction uncertainty analysis techniques of SWAT simulated streamflow applied to Chungju dam watershed, [Korean Literature], Journal of Korea Water Resources Association, Vol. 45, No. 9, pp. 861-874DOI
23 
Joseph J. F., Guillaume J. H. A., 2013, Using a parallelized MCMC algorithm in R to identify appropriate likelihood functions for SWAT, Environmental modelling & software, Vol. 46, pp. 292-298DOI
24 
Kavetski D., Kuczera G., Franks S. W., 2006a, Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory, Water Resources Research, W03407., Vol. 42Google Search
25 
Kavetski D., Kuczera G., Franks S. W., 2006b, Bayesian analysis of input uncertainty in hydrological modeling: 2. Application, Water Resources Research, W03408., Vol. 42Google Search
26 
Kim J. K., Son K. H., Noh J. W., Lee S. U., 2008, Estimation of suspended sediment load in Imha-Andong watershed using SWAT model,, Korean Society of Environmental Engineers, Vol. 30, No. 12, pp. 1209-1217Google Search
27 
Kim M. H., Heo T. Y., Chung S. W., 2013, Uncertainty analysis on the simulations of runoff and sediment using SWAT-CUP, [Korean Literature], Journal of Korean Society on Water Environment, Vol. 29, No. 5, pp. 681-690Google Search
28 
Kim R., Won J., Choi J., Lee O., Kim S., 2020, Application of Bayesian approach to parameter estimation of TANK model: Comparison of MCMC and GLUE methods, [Korean Literature], Journal of Korean Society on Water Environment, Vol. 36, No. 4, pp. 300-313Google Search
29 
Kim S. M., 2017, Evaluation of applicability of SWAT-CUP program for hydrologic parameter calibration in hardware watershed, [Korean Literature], Journal of the Korean Soiety of Agricultural Engineers, Vol. 59, No. 3, pp. 63-70DOI
30 
Knighton J., Lennon E., Bastidas L., White E., 2016, Stormwater detention system parameter sensitivity and uncertainty analysis using SWMM, 05016014., Journal of Hydrologic Engineering, Vol. 21, No. 8DOI
31 
Korea Rural Development Administration (KRDA)., 2010, http://soil.rda.go.kr (accessed Sept. 2020)., Korean Soil Information System (KSIS)
32 
Kuczera G., 1983, Improved parameter inference in catchment models: 1. Evaluating parameter uncertainty, Water Resources Research, Vol. 19, pp. 1151-1162Google Search
33 
Kuczera G., Parent E., 1998, Monte Carlo assessment of parameter uncertainty in conceptual catchment models: the Metropolis algorithm, Journal of Hydrology, Vol. 211, pp. 69-85Google Search
34 
Kwon H. H., Kim J. G., Park S., 2013, Derivation of flood frequency curve with uncertainty of rainfall and rainfall-runoff model, [Korean Literature], Journal of Korea Water Resources Association, Vol. 46, No. 1, pp. 59-71DOI
35 
Kwon H. H., Kim J. G., Lee J. S., Na B. K., 2012, Uncertainty assessment of single event rainfall-runoff model using Bayesian model,, [Korean Literature], Journal of Korea Water Resources Association, Vol. 25, No. 5, pp. 505-516DOI
36 
Kwon H. H., Moon Y. I., Kim B. S., Yoon S. Y., 2008, Parameter optimization and uncertainty analysis of the NWS-PC rainfall-runoff model coupled with Bayesian Markov Chain Monte Carlo inference scheme, [Korean Literature], Journal of Korean Society Civil Engineering, Vol. 28, pp. 383-392Google Search
37 
Lee E., Seo D., 2011, Flow calibration and validation of Daechung lake watershed, Korea using SWAT-CUP,, [Korean Literature], Journal of Korea Water Resources Association,, Vol. 44, No. 9, pp. 711-720DOI
38 
Li Z., Shao Q., Xu Z., Cai X., 2010, Analysis of parameter uncertainty in semi-distributed hydrological models using bootstrap method: A case study of SWAT model applied to Yingluoxia watershed in northwest China, Journal of Hydrology, Vol. 385, No. 1-4, pp. 76-83DOI
39 
Liang S., Jia H., Xu C., Xu T., Melching C., 2016, A Bayesian approach for evaluation of the effect of water quality model parameter uncertainty on TMDLs: A case study of Miyun Reservoir, Science of the Total Environment, Vol. 560, No. 561, pp. 44-54DOI
40 
Lim J., Kwon H., Joo H., Wang W., Lee J., You Y., Kim H., 2019, Uncertainty analysis of stage-discharge curve using Bayesian and Bootstrap method, Journal of Wetlands Research, Vol. 21, No. 2, pp. 114-124Google Search
41 
Liu Y. R., Li Y. P., Huang G. H., Zhang J. L., Fan Y. R., 2017, A Bayesian-based multilevel factorial analysis method for analyzing parameter uncertainty of hydrological model, Journal of Hydrology, Vol. 553, pp. 750-762DOI
42 
Long D., Longuevergne L., Scanlon B., 2014, Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites, Water Resource Research, Vol. 50, pp. 1131-1151Google Search
43 
Makowski D., Wallach D., Tremblay M., 2002, Using a bayesian approach to parameter estimation; comparison of the GLUE and MCMC methods, Agronomie, Vol. 22, pp. 191-203DOI
44 
Marshall L., Nott D., Sharma A., 2007, Towards dynamic catchment modelling: a Bayesian hierarchical modelling framework, Hydrological Processes, Vol. 21, pp. 847-861Google Search
45 
Ministry of Envrionment (ME)., 2007, http://http://egis.me.go.kr (accessed Sept. 2020)., Environmental Geography Information System (EGIS)
46 
Nash J. E., Sutcliffe J. V., 1970, River flow forecasting through conceptual models: Part 1 – A discussion of principles, Journal of Hydrology, Vol. 10, pp. 282-290Google Search
47 
National Geographic Information Institute (NGII)., 2014, http://map.ngii.go.kr (accessed Sept. 2020)., National Territory Informaion Platform (NTIP)
48 
Patil S. D., Stieglitz M., 2015, Comparing spatial and temporal transferability of hydrological model parameters, Journal of Hydrology, Vol. 525, pp. 409-417DOI
49 
Raftery A. E., Lewis S. M., 1995, Implementing MCMC, Markov Chain Monte Carlo in Practice, pp. 115-130Google Search
50 
Refsgaard J. C., Storm B., 1996, Construction calibration and validation of hydrological models,, Distributed hydrological modelling, Water Science and Technology Library,, Kluwer Academic Publishers,, Vol. 22, pp. 41-54Google Search
51 
Ryu J., Kang H., Choi J., Kong D., Gum D., Jang C., Lim K., Application of SWAT-CUP for streamflow auto-calibration at Soyang-gang dam watershed, [Korean Literature], Journal of Korean Society on Water Environment, Vol. 28, No. 3, pp. 347-358Google Search
52 
Schoups G., Vrugt J. A., 2010, A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, W10531., heteroscedastic, and non-gaussian errors, Water Resources Research, Vol. 46Google Search
53 
2015, Uncertainty reduction and parameter estimation of a distributed hydrological model with ground and remot-sensing data, Hydrology and Earth System Sciences, Vol. 19, pp. 1727-1751DOI
54 
Sun M., Zhang X., Huo Z., Feng S., Huang G., Mao X., 2015, Uncertainty and sensitivity assessments of an agricultural–hydrological model (RZWQM2) using the GLUE method, Journal of Hydrology, Vol. 534, pp. 19-30DOI
55 
Sun N., Hall M., Hong B., Zhang L., 2012, Impact of SWMM catchment discretization: Case study in Syracuse, New York, Journal of Hydrologic Engineering, Vol. 19, No. 1, pp. 223-234DOI
56 
Swann A., Koven C., 2017, A direct estimate of the seasonal cycle of evapotranspiration over the Amazon basin, Journal of Hydrometeorology, Vol. 18, pp. 2173-2185Google Search
57 
Swiler L. P., 2006, Bayesian methods in engineering design problems, Sandia National Laboratories report, pp. 2005-3294Google Search
58 
Teweldebrhan A. T., Burkhart J. F., Schuler T. V., 2018, Parameter uncertainty analysis for an operational hydrological model using residual-based and limits of acceptability approaches, Hydrology and Earth System Sciences, Vol. 22, pp. 5021-5039DOI
59 
Todini E., 2007, Hydrological catchment modelling: Past, present and future, Hydrology and Earth System Sciences, Vol. 11, pp. 468-482DOI
60 
Zhang W., Li T., 2015, The influence of objective function and acceptability threshold on uncertainty assessment of an urban drainage hydraulic model with generalized likelihood uncertainty estimation methodology, Water Resources Management, Vol. 29, pp. 2059-2072Google Search
61 
Zhang W., Li T., Dai M., 2015, Uncertainty assessment of water quality modeling for a small-scale urban catchment using the GLUE methodology: a case study in Shanghai, China, Environmental Science and Pollution Research, Vol. 22, No. 12, pp. 9241-9249DOI
62 
Zhang Y., Pan M., Sheffield J., Siemann A., Fisher C., Liang M., Beck H., Wanders N., MacCracken R., Houser P., Zhou T., Lettenmaier D., Pinker R., Bytheway J., Kummerow C., Wood E., 2018, A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010, Hydrology and Earth System Sciences, Vol. 22, pp. 241-263Google Search