{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T08:13:52Z","timestamp":1770884032755,"version":"3.50.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2019,1,2]],"date-time":"2019-01-02T00:00:00Z","timestamp":1546387200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"crossref","award":["8184094"],"award-info":[{"award-number":["8184094"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"crossref"}]},{"name":"IWHR Research and Development Support Program","award":["JZ0145B022018"],"award-info":[{"award-number":["JZ0145B022018"]}]},{"name":"IWHR Research and Development Support Program","award":["JZ0145B022017"],"award-info":[{"award-number":["JZ0145B022017"]}]},{"DOI":"10.13039\/100006416","name":"Bone and Joint Injury Prevention and Rehabilitation Center, University of Michigan","doi-asserted-by":"crossref","award":["0628-136006104242"],"award-info":[{"award-number":["0628-136006104242"]}],"id":[{"id":"10.13039\/100006416","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100006416","name":"Bone and Joint Injury Prevention and Rehabilitation Center, University of Michigan","doi-asserted-by":"crossref","award":["JZ0205A432013"],"award-info":[{"award-number":["JZ0205A432013"]}],"id":[{"id":"10.13039\/100006416","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100006416","name":"Bone and Joint Injury Prevention and Rehabilitation Center, University of Michigan","doi-asserted-by":"crossref","award":["SLXMB200902"],"award-info":[{"award-number":["SLXMB200902"]}],"id":[{"id":"10.13039\/100006416","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Construction project of Shaanxi province medium and small river hydrological monitoring and forecast system\u2014construction of Guanzhong and north of Shaanxi flood forecast scheme","award":["JZ0205A112015"],"award-info":[{"award-number":["JZ0205A112015"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Engineering with Computers"],"published-print":{"date-parts":[[2020,1]]},"DOI":"10.1007\/s00366-018-0685-4","type":"journal-article","created":{"date-parts":[[2019,1,2]],"date-time":"2019-01-02T02:29:22Z","timestamp":1546396162000},"page":"75-96","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Heterogeneous parallel computing accelerated generalized likelihood uncertainty estimation (GLUE) method for fast hydrological model uncertainty analysis purpose"],"prefix":"10.1007","volume":"36","author":[{"given":"Guangyuan","family":"Kan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liuqian","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiren","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Hong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ke","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,1,2]]},"reference":[{"key":"685_CR1","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1016\/j.envsoft.2016.11.004","volume":"87","author":"E Barca","year":"2017","unstructured":"Barca E, Porcu E, Bruno D, Passarella G (2017) An automated decision support system for aided assessment of variogram models. Environ Model Softw 87:72\u201383","journal-title":"Environ Model Softw"},{"key":"685_CR2","first-page":"297","volume":"6","author":"K Beven","year":"1992","unstructured":"Beven K, Binley A (1992) The future of distributed models: model calibration and predictive uncertainty. Hydrol Process 6:297\u2013298","journal-title":"Hydrol Process"},{"key":"685_CR3","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/0309-1708(93)90028-E","volume":"16","author":"K Beven","year":"1993","unstructured":"Beven K (1993) Prophecy, reality and uncertainty in distributed hydrological modeling. Adv Water Resour 16:41\u201351","journal-title":"Adv Water Resour"},{"issue":"1\u20132","key":"685_CR4","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.jhydrol.2005.07.007","volume":"320","author":"K Beven","year":"2006","unstructured":"Beven K (2006) A manifesto for the equifinality thesis. J Hydrol 320(1\u20132):18\u201336","journal-title":"J Hydrol"},{"key":"685_CR5","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1016\/S0022-1694(99)00057-8","volume":"219","author":"D Cameron","year":"1999","unstructured":"Cameron D, Beven K, Tawn J, Blazkova S, Naden P (1999) Flood frequency estimation by continuous simulation for a gauged upland catchment (with uncertainty). J Hydrol 219:169\u2013187","journal-title":"J Hydrol"},{"key":"685_CR6","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/S0309-1708(00)00042-7","volume":"24","author":"D Cameron","year":"2001","unstructured":"Cameron D, Beven K, Tawn J (2001) Modelling extreme rainfalls using a modified random pulse Bartlett\u2013Lewis stochastic rainfall model (with uncertainty). Adv Water Resour 24:203\u2013211","journal-title":"Adv Water Resour"},{"issue":"1","key":"685_CR7","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1029\/1998WR900043","volume":"35","author":"E Campbell","year":"1999","unstructured":"Campbell E, Fox D et al (1999) A Bayesian approach to parameter estimation and pooling in nonlinear flood event models. Water Resour Res 35(1):211\u2013230","journal-title":"Water Resour Res"},{"issue":"3","key":"685_CR8","first-page":"221","volume":"23","author":"S Chen","year":"2003","unstructured":"Chen S, Kang E et al (2003) Review of the hydrological model researches. J Desert Res 23(3):221\u2013229 (in Chinese)","journal-title":"J Desert Res"},{"issue":"2","key":"685_CR9","doi-asserted-by":"publisher","first-page":"565","DOI":"10.15244\/pjoes\/75159","volume":"27","author":"S Chen","year":"2018","unstructured":"Chen S, Kan G, Li J, Ke H, Liang K (2018) Investigation of China urban air condition using big data, information theory and machine learning, 2018. Polish J Environ Stud 27(2):565\u2013578","journal-title":"Polish J Environ Stud"},{"key":"685_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.envsoft.2016.10.005","volume":"87","author":"Z Chen","year":"2017","unstructured":"Chen Z, Hartmann A, Goldscheider N (2017) A new approach to evaluate spatiotemporal dynamics of controlling parameters in distributed environmental models. Environ Model Softw 87:1\u201316","journal-title":"Environ Model Softw"},{"issue":"3","key":"685_CR11","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1007\/s00521-014-1727-5","volume":"26","author":"J Dong","year":"2015","unstructured":"Dong J, Zheng C, Kan G, Wen J, Zhao M, Yu J (2015) Applying the ensemble artificial neural network-based hybrid data-driven model to daily total load forecasting. Neural Comput Appl 26(3):603\u2013611","journal-title":"Neural Comput Appl"},{"key":"685_CR12","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.envsoft.2016.09.012","volume":"86","author":"YR Fan","year":"2017","unstructured":"Fan YR, Huang GH, Baetz BW, Li YP, Huang K, Li Z, Chen X, Xiong LH (2017) Parameter uncertainty and temporal dynamics of sensitivity for hydrologic models: A hybrid sequential data assimilation and probabilistic collocation method. Environ Model Softw 86:30\u201349","journal-title":"Environ Model Softw"},{"issue":"4","key":"685_CR13","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1029\/97WR03041","volume":"34","author":"S Franks","year":"1998","unstructured":"Franks S, Gineste P, Beven K, Merot P (1998) On constraining the predictions of a distributed model: the incorporation of fuzzy estimates of saturated areas into the calibration process. Water Resour Res 34(4):787\u2013797","journal-title":"Water Resour Res"},{"key":"685_CR14","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.envsoft.2016.09.009","volume":"86","author":"D Costa","year":"2017","unstructured":"Costa D, Burlando P, Liong SY (2017) Coupling spatially distributed river and groundwater transport models to investigate contaminant dynamics at river corridor scales. Environ Model Softw 86:91\u2013110","journal-title":"Environ Model Softw"},{"key":"685_CR15","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.envsoft.2016.10.008","volume":"87","author":"J Groeneveld","year":"2017","unstructured":"Groeneveld J, Muller B, Buchmann CM, Dressler G, Guo C, Hase N, Hoffmann F, John F, Klassert C, Lauf T, Liebelt V, Nolzen H, Pannicke N, Schulze J, Weise H, Schwarz N (2017) Theoretical foundations of human decision-making in agent-based land use models\u2014a review. Environ Model Softw 87:39\u201348","journal-title":"Environ Model Softw"},{"key":"685_CR16","first-page":"7","volume":"12","author":"GM Hornberger","year":"1981","unstructured":"Hornberger GM, Spear RC (1981) An approach to the preliminary analysis of environmental systems. J Environ Manag 12:7\u201318","journal-title":"J Environ Manag"},{"key":"685_CR17","doi-asserted-by":"publisher","first-page":"1345","DOI":"10.1007\/s00477-015-1040-6","volume":"29","author":"G Kan","year":"2015","unstructured":"Kan G, Yao C, Li Q, Li Z, Yu Z, Liu Z, Ding L, He X, Liang K (2015) Improving event-based rainfall-runoff simulation using an ensemble artificial neural network based hybrid data-driven model. Stoch Environ Res Risk Assess 29:1345\u20131370","journal-title":"Stoch Environ Res Risk Assess"},{"key":"685_CR18","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2200-4","author":"G Kan","year":"2015","unstructured":"Kan G, Li J, Zhang X, Ding L, He X, Liang K, Jiang X, Ren M, Li H, Wang F, Zhang Z, Hu Y (2015) A new hybrid data-driven model for event-based rainfall-runoff simulation. Neural Comput Appl. \nhttps:\/\/doi.org\/10.1007\/s00521-016-2200-4","journal-title":"Neural Comput Appl"},{"key":"685_CR19","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2534-y","author":"G Kan","year":"2016","unstructured":"Kan G, He X, Li J, Ding L, Zhang D, Lei T, Hong Y, Liang K, Zuo D, Bao Z, Zhang M (2016) A novel hybrid data-driven model for multi-input single-output system simulation. Neural Comput Appl. \nhttps:\/\/doi.org\/10.1007\/s00521-016-2534-y","journal-title":"Neural Comput Appl"},{"key":"685_CR20","doi-asserted-by":"publisher","first-page":"8483728","DOI":"10.1155\/2016\/8483728","volume":"2016","author":"G Kan","year":"2016","unstructured":"Kan G, Liang K, Li J, Ding L, He X, Hu Y, Amo-Boateng M (2016) Accelerating the SCE-UA global optimization method based on multi-core CPU and many-core GPU. Adv Meteorol 2016:8483728. \nhttps:\/\/doi.org\/10.1155\/2016\/8483728","journal-title":"Adv Meteorol"},{"key":"685_CR21","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2016.2575822","author":"G Kan","year":"2016","unstructured":"Kan G, Lei T, Liang K, Li J, Ding L, He X, Yu H, Zhang D, Zuo D, Bao Z,, Hu Y, Zhang M (2016) Mark Amo-boateng. A multi-core CPU and many-core GPU based fast parallel shuffled complex evolution global optimization approach. IEEE Trans Parallel Distrib Syst. \nhttps:\/\/doi.org\/10.1109\/TPDS.2016.2575822","journal-title":"IEEE Trans Parallel Distrib Syst"},{"key":"685_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2016.08.017","author":"G Kan","year":"2016","unstructured":"Kan G, Zhang M, Liang K, Wang H, Jiang Y, Li J, Ding L, He X, Hong Y, Zuo D, Bao Z, Li C (2016) Improving water quantity simulation and forecasting to solve the energy-water-food nexus issue by using heterogeneous computing accelerated global optimization method. Appl Energy. \nhttps:\/\/doi.org\/10.1016\/j.apenergy.2016.08.017","journal-title":"Appl Energy"},{"key":"685_CR23","doi-asserted-by":"publisher","DOI":"10.1007\/s11831-017-9224-5","author":"G Kan","year":"2017","unstructured":"Kan G, He X, Li J, Ding L, Hong Y, Zhang H, Liang K, Zhang M (2017) Computer aided numerical methods for hydrological model calibration: an overview and recent development. Arch Comput Methods Eng. \nhttps:\/\/doi.org\/10.1007\/s11831-017-9224-5","journal-title":"Arch Comput Methods Eng"},{"issue":"10","key":"685_CR24","doi-asserted-by":"publisher","first-page":"719","DOI":"10.3390\/w9100719","volume":"9","author":"G Kan","year":"2017","unstructured":"Kan G, He X, Ding L, Li J, Liang K, Hong Y (2017) Study on applicability of conceptual hydrological models for flood forecasting in humid, semi-humid semi-arid and arid basins in China. Water 9(10):719","journal-title":"Water"},{"issue":"11","key":"685_CR25","doi-asserted-by":"publisher","first-page":"904","DOI":"10.3390\/w9110904","volume":"9","author":"G Kan","year":"2017","unstructured":"Kan G, Tang G, Yang Y, Hong Y, Li J, Ding L, He X, Liang K, He L, Li Z, Hu Y, Cui Y (2017) An improved coupled routing and excess storage (CREST) distributed hydrological model and its verification in Ganjiang river basin, China. Water 9(11):904","journal-title":"Water"},{"issue":"7","key":"685_CR26","doi-asserted-by":"publisher","first-page":"1640","DOI":"10.2166\/wst.2017.322","volume":"76","author":"G Kan","year":"2017","unstructured":"Kan G, He X, Ding L, Li J, Liang K, Hong Y (2017) A heterogeneous computing accelerated SCE-UA global optimization method using OpenMP, CUDA and OpenACC. Water Sci Technol 76(7):1640\u20131651","journal-title":"Water Sci Technol"},{"issue":"2","key":"685_CR27","doi-asserted-by":"publisher","first-page":"51","DOI":"10.24850\/j-tyca-2017-02-05","volume":"8","author":"G Kan","year":"2017","unstructured":"Kan G, He X, Ding L, Li J, Hong Y, Ren M, Lei T, Liang K, Zuo D, Huang P (2017) Daily streamflow simulation based on improved machine learning method. Tecnologia y Ciencias del Agua 8(2):51\u201360","journal-title":"Tecnologia y Ciencias del Agua"},{"issue":"1","key":"685_CR28","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1080\/0305215X.2017.1303053","volume":"50","author":"G Kan","year":"2018","unstructured":"Kan G, He X, Ding L, Li J, Hong Y, Zuo D, Ren M, Lei T, Liang K (2018) Fast hydrological model calibration based on the heterogeneous parallel computing accelerated shuffled complex evolution method. Eng Optim 50(1):106\u2013449","journal-title":"Eng Optim"},{"key":"685_CR29","doi-asserted-by":"publisher","first-page":"787","DOI":"10.3390\/ijerph13080787","volume":"13","author":"C Li","year":"2016","unstructured":"Li C, Cheng X, Li N, Du X, Yu Q, Kan G (2016) A framework for flood risk analysis and benefit assessment of flood control measures in urban areas. Int J Environ Res Public Health 13:787. \nhttps:\/\/doi.org\/10.3390\/ijerph13080787","journal-title":"Int J Environ Res Public Health"},{"issue":"1","key":"685_CR30","doi-asserted-by":"publisher","first-page":"12","DOI":"10.3390\/w10010012","volume":"10","author":"K Li","year":"2018","unstructured":"Li K, Kan G, Ding L, Dong Q, Liu K, Liang L (2018) A novel flood forecasting method based on initial state variable correction. Water 10(1):12","journal-title":"Water"},{"issue":"10","key":"685_CR31","doi-asserted-by":"publisher","first-page":"04014019","DOI":"10.1061\/(ASCE)HE.1943-5584.0000958","volume":"19","author":"Z Li","year":"2014","unstructured":"Li Z, Kan G, Yao C, Liu Z, Li Q, Yu S (2014) An improved neural network model and its application in hydrological simulation. J Hydrol Eng 19(10):04014019","journal-title":"J Hydrol Eng"},{"key":"685_CR32","volume-title":"OpenCL heterogeneous parallel computing: from principle to practice","author":"W Liu","year":"2016","unstructured":"Liu W, Chen Y, Wu C (2016) OpenCL heterogeneous parallel computing: from principle to practice. China Machine Press, Beijing (in Chinese)"},{"key":"685_CR33","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.envsoft.2016.10.010","volume":"87","author":"T Locatelli","year":"2017","unstructured":"Locatelli T, Tarantola S, Gardiner B, Patenaude G (2017) Variance-based sensitivity analysis of a wind risk model\u2014model behavior and lessons for forest modelling. Environ Model Softw 87:84\u2013109","journal-title":"Environ Model Softw"},{"key":"685_CR34","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.agrformet.2003.09.009","volume":"122","author":"X Mo","year":"2004","unstructured":"Mo X, Beven K (2004) Multi-objective parameter conditioning of a three-source wheat canopy model. Agric For Meteorol 122:39\u201363","journal-title":"Agric For Meteorol"},{"key":"685_CR35","doi-asserted-by":"publisher","first-page":"212","DOI":"10.1016\/S0010-4655(01)00159-X","volume":"126","author":"M Ratto","year":"2001","unstructured":"Ratto M, Tarantola S, Saltelli A (2001) Sensitivity analysis in model calibration: GSA-GLUE approach. Comput Phys Commun 126:212\u2013224","journal-title":"Comput Phys Commun"},{"key":"685_CR36","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/S0048-9697(99)00282-X","volume":"236","author":"K Susan","year":"1999","unstructured":"Susan K, Beven K (1999) Equifinality, sensitivity and predictive uncertainty in the estimation of critical loads. Sci Total Environ 236:191\u2013214","journal-title":"Sci Total Environ"},{"key":"685_CR37","first-page":"8","volume":"5","author":"B Tan","year":"1996","unstructured":"Tan B (1996) Comparison and analysis of hydrological model parameter automatic optimization methods. J China Hydrol 5:8\u201314 (in Chinese)","journal-title":"J China Hydrol"},{"key":"685_CR38","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.envsoft.2003.12.006","volume":"20","author":"S Uhlenbrook","year":"2005","unstructured":"Uhlenbrook S, Sieber A (2005) On the value of experimental data to reduce the prediction uncertainty of a process-oriented catchment model. Environ Model Softw 20:19\u201332","journal-title":"Environ Model Softw"},{"key":"685_CR39","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.envsoft.2016.09.015","volume":"86","author":"YP Wu","year":"2017","unstructured":"Wu YP, Liu SG, Qiu LJ, Sun YZ (2017) SWAT-DayCent coupler: An integration tool for simultaneous hydro-biogeochemical modelling using SWAT and DayCent. Environ Model Softw 86:81\u201390","journal-title":"Environ Model Softw"},{"key":"685_CR40","volume-title":"Watershed hydrological model-Xinanjiang model and Northern Shaanxi model","author":"R Zhao","year":"1983","unstructured":"Zhao R (1983) Watershed hydrological model-Xinanjiang model and Northern Shaanxi model. Water Resources and Electric Power Press, Beijing"},{"key":"685_CR41","volume-title":"Anthology of hydrological forecasting","author":"R Zhao","year":"1994","unstructured":"Zhao R (1994) Anthology of hydrological forecasting. Water Resources and Electric Power Press, Beijing"}],"container-title":["Engineering with Computers"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00366-018-0685-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00366-018-0685-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00366-018-0685-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,1,10]],"date-time":"2020-01-10T00:37:00Z","timestamp":1578616620000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00366-018-0685-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,2]]},"references-count":41,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,1]]}},"alternative-id":["685"],"URL":"https:\/\/doi.org\/10.1007\/s00366-018-0685-4","relation":{},"ISSN":["0177-0667","1435-5663"],"issn-type":[{"value":"0177-0667","type":"print"},{"value":"1435-5663","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,1,2]]},"assertion":[{"value":"8 February 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 December 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 January 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}