Ashu, A.B., and Lee, S.-I. (2023). “Multi-Site calibration of hydrological model and Spatio-temporal assessment of water balance in a monsoon watershed.” Water, Vol. 15, No. 2, 360.
10.3390/w15020360Bai, R., Sun, J., Yu, E., and Yu, S. (2022). “Performance of the weather research and forecasting model in simulating climate over northern Asia.” International Journal of Climatology, Vol. 42, No. 16, pp. 10285-10307.
10.1002/joc.7898Bao, D., Xue, Z.G., and Warner, J.C. (2024). “Quantifying compound and nonlinear effects of hurricane-induced flooding using a dynamically coupled hydrological-ocean model.” Water Resources Research, Vol. 60, No. 7, e2023WR036455.
10.1029/2023WR036455Bazargan, J., and Norouzi, H. (2018). “Investigation the effect of using variable values for the parameters of the linear Muskingum method using the Particle Swarm Algorithm (PSO).” Water Resources Management, Vol. 32, No. 14, pp. 4763-4777.
10.1007/s11269-018-2082-6Chen, Y., Wen, J., Meng, X., Zhang, Q., Li, X., Zhang, G., and Chen, R. (2024). “An assessment of the coupled weather research and forecasting hydrological model on streamflow simulations over the source region of the Yellow River.” Atmosphere, Vol. 15, No. 4, 468.
10.3390/atmos15040468Choi, S., Jang, C., and Kim, H. (2016). “Analysis of short-term runoff characteristics of CAT-PEST connected model using different infiltration analysis methods.” Journal of the Korea Academia-Industrial cooperation Society, Vol. 17, No. 11, pp. 26-41.
10.5762/KAIS.2016.17.11.26Doherty, J. (2025). Calibration and uncertainty analysis for complex environmental models: PEST: Complete theory and what it means for modelling the real world. Second edition. Watermark Numerical Computing, Brisbane, Australia.
Franco, A.C.L., Oliveira, D.Y. de and Bonumá, N.B. (2020). “Comparison of single-site, multi-site and multi-variable SWAT calibration strategies.” Hydrological Sciences Journal, Vol. 65, No. 14, pp. 2376-2389.
10.1080/02626667.2020.1810252Gochis, D.J., Barlage, M., Cabell, R., Casali, M., Dugger, A., FitzGerald, K., McAllister, M., McCreight, J., RafieeiNasab, A., and Read, L. et al. (2020). The WRF-Hydro® modeling system technical description, Version 5.1.1. NCAR Technical Note, National Center for Atmospheric Research, Boulder, CO, U.S., p. 108.
Homa, M.G., Mengistu Tsidu, G., and Lofton, E.N. (2025). “Hydrological modelling and multisite calibration of the Okavango River Basin: Addressing catchment heterogeneity and climate variability.” Water, Vol. 17, No. 10, 1442.
10.3390/w17101442Kilicarslan, B.M., Yucel, I., Pilatin, H., Duzenli, E., and Yilmaz, M.T. (2021). “Improving WRF-Hydro runoff simulations of heavy floods through the sea surface temperature fields with higher spatio-temporal resolution.” Hydrological Processes, Vol. 35, No. 9, e14338.
10.1002/hyp.14338Kim, B., Lee, G., Lee, Y., Kim, S., and Noh, S.J. (2024). “Assessment of the impact of spatial variability on streamflow predictions using high-resolution modeling and parameter estimation: Case study of Geumho River catchment, South Korea.” Water, Vol. 16, No. 4, 591.
10.3390/w16040591Lahmers, T.M., Kumar, S.V., Rosen, D., Dugger, A., Gochis, D.J., Santanello, J.A., Gangodagamage, C., and Dunlap, R. (2022). “Assimilation of NASA’s airborne snow observatory snow measurements for improved hydrological modeling: A case study enabled by the coupled LIS/WRF-Hydro system.” Water Resources Research, Vol. 58, No. 3, e2021WR029867.
10.1029/2021WR029867Lee, J., Choi, J., Seo, J., Won, J., and Kim, S. (2023). “Exploring climate sensitivity in hydrological model calibration.” Water, Vol. 15, No. 23, 4094.
10.3390/w15234094Lee, J., Kim, Y., and Chae, Y. (2020). “Projecting future hydrological and ecological droughts with the climate and land use scenarios over the Korean peninsula.” Journal of Korea Water Resources Association, Vol. 53, No. 6, pp. 427-436.
10.3741/JKWRA.2020.53.6.427Lee, Y., Kim, B., and Noh, S.J. (2025). “High-resolution ensemble streamflow predictions using WRF-Hydro and LDAPS: A case study of the Geumho River catchment.” Journal of Korea Water Resources Association, Vol. 58, No. 3, pp. 263-275.
10.3741/JKWRA.2025.58.3.263Lu, C., Ji, K., Wang, W., Zhang, Y., Ealotswe, T.K., Qin, W., Lu, J., Liu, B., and Shu, L. (2021). “Estimation of the interaction between groundwater and surface water based on flow routing using an improved nonlinear Muskingum-Cunge method.” Water Resources Management, Vol. 35, No. 8, pp. 2649-2666.
10.1007/s11269-021-02857-9Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D., and Veith, T.L. (2007). “Model evaluation guidelines for systematic quantification of accuracy in watershed simulations.” Transactions of the ASABE, Vol. 50, No. 3, pp. 885-900.
10.13031/2013.23153Noh, S.J., Choe, Y.S., Choe, C.G., and Kim, G.T (2013). “Parameter Estimation of a distributed hydrologic model using parallel PEST: Comparison of Impacts by Radar and Ground Rainfall Estimates.” Journal of Korea Water Resources Association, Vol. 46, No. 11, pp. 1041-1052.
10.3741/JKWRA.2013.46.11.1041Perumal, M., and Sahoo, B. (2008). “Volume conservation controversy of the variable parameter Muskingum-Cunge method.” Journal of Hydraulic Engineering, Vol. 134, No. 4, pp. 475-485.
10.1061/(ASCE)0733-9429(2008)134:4(475)Ponce, V.M. (2023). Why is the Muskingum-Cunge the best flood routing method? San Diego State University Online Publications, San Diego, CA, U.S., pp. 1-9.
Raney, A., Maghami, I., Feng, Y., Mandli, K., Cohen, S., and Goodall, J. (2022). “An open-source Python library for varying model parameters and automating concurrent simulations of the national water model.” JAWRA Journal of the American Water Resources Association, Vol. 58, No. 1, pp. 75-85.
10.1111/1752-1688.12973Rummler, T., Arnault, J., Gochis, D., and Kunstmann, H. (2019). “Role of lateral terrestrial water flow on the regional water cycle in a complex terrain region: investigation with a fully coupled model system.” Journal of Geophysical Research: Atmospheres, Vol. 124, No. 2, pp. 507-529.
10.1029/2018JD029004Sofokleous, I., Bruggeman, A., and Camera, C. (2024). “The role of parameterizations and model coupling on simulations of energy and water balances - Investigations with the atmospheric model WRF and the hydrologic model WRF-Hydro.” Journal of Geophysical Research: Atmospheres, Vol. 129, No. 8, pp. e2023JD040335.
10.1029/2023JD040335Sthapit, E., Lakhankar, T., Hughes, M., Khanbilvardi, R., Cifelli, R., Mahoney, K., Currier, W.R., Viterbo, F., and Rafieeinasab, A. (2022). “Evaluation of snow and streamflows using Noah-MP and WRF-Hydro models in Aroostook River Basin, Maine.” Water, Vol. 14, No. 14, 2145.
10.3390/w14142145Taylor, K.E. (2001). “Summarizing multiple aspects of model performance in a single diagram.” Journal of Geophysical Research: Atmospheres, Vol. 106, No. D7, pp. 7183-7192.
10.1029/2000JD900719Wang, S., Zhang, Z., Sun, G., Strauss, P., Guo, J., Tang, Y., and Yao, A. (2012). “Multi-site calibration, validation, and sensitivity analysis of the MIKE SHE Model for a large watershed in northern China.” Hydrology and Earth System Sciences, Vol. 16, No. 12, pp. 4621-4632.
10.5194/hess-16-4621-2012Xiang, T., Vivoni, E.R., Gochis, D.J., and Mascaro, G. (2017). “On the diurnal cycle of surface energy fluxes in the North American monsoon region using the WRF-Hydro modeling system.” Journal of Geophysical Research: Atmospheres, Vol. 122, No. 17, pp. 9024-9049.
10.1002/2017JD026472Yang, Z.-L., Cai, X., Zhang, G., Tavakoly, A.A., Jin, Q., Meyer, L.H., and Guan, X. (2011). The community noah land surface model with multi-parameterization options (Noah-MP): Technical description. Center for Integrated Earth System Science, The University of Texas at Austin, Austin, TX, U.S.
- Publisher :KOREA WATER RESOURECES ASSOCIATION
- Publisher(Ko) :한국수자원학회
- Journal Title :Journal of Korea Water Resources Association
- Journal Title(Ko) :한국수자원학회 논문집
- Volume : 59
- No :6
- Pages :575-587
- Received Date : 2026-01-30
- Revised Date : 2026-03-31
- Accepted Date : 2026-04-23
- DOI :https://doi.org/10.3741/JKWRA.2026.59.6.575


Journal of Korea Water Resources Association









