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http://dx.doi.org/10.5389/KSAE.2022.64.2.071

Development of Monthly Hydrological Cycle Assessment System Using Dynamic Water Balance Model Based on Budyko Framework  

Kim, Kyeung (Data Consulting Group, Samsung SDS)
Hwang, Soonho (Agricultural and biological engineering, University of Illinois at Urbana-Champaign)
Jun, Sang-Min (Convergence Major in Global Smart Farm, Seoul National University)
Lee, Hyunji (Department of Rural Systems Engineering, Seoul National University)
Kim, Sinae (Department of Rural Systems Engineering, Seoul National University)
Kang, Moon Seong (Department of Rural Systems Engineering, Research Institute of Agriculture and Life Sciences, Institute of Green Bio Science and Technology, Seoul National University)
Publication Information
Journal of The Korean Society of Agricultural Engineers / v.64, no.2, 2022 , pp. 71-83 More about this Journal
Abstract
In this study, an indicator and assessment system for evaluating the monthly hydrological cycle was prepared using simple factors such as the landuse status of the watershed and topographic characteristics to the dynamic water balance model (DWBM) based on the Budyko framework. The parameters a1 of DWBM are introduced as hydrologic cycle indicators. An indicator estimation regression model was developed using watershed characteristics data for the introduced indicator, and an assessment system was prepared through K-means cluster analysis. The hydrological cycle assessment system developed in this study can assess the hydrological cycle with simple data such as land use, CN, and watershed slope, so it can quickly assess changes in hydrological cycle factors in the past and present. Because of this advantage is expected that the developed assessment system can predict changes in the hydrological cycle and use an auxiliary tool for policymaking.
Keywords
Watershed management; hydrological cycle distortion; hydrological indicator; budyko curve; dynamic water balance model;
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1 Xu, X., W. Liu, B. R. Scanlon, L. Zhang, and M. Pan, 2013. Local and global factors controlling water-energy balances within the Budyko framework. Geophysical Research Letters 40(23): 6123-6129. doi:10.1002/2013GL058324.   DOI
2 Zhang, L., N. Potter, K. Hickel, Y. Zhang, and Q. Shao, 2008. Water balance modeling over variable time scales based on the Budyko framework-Model development and testing. Journal of Hydrology 360(1-4): 117-131. doi:10.1016/j.jhydrol.2008.07.021.   DOI
3 Relevant Ministerial Consortium., 2020. Third nonpoint source management comprehensive plan. 11-1480000-001720-13. Sejong Metropolitan Autonomous City: Ministry of Envioronment.
4 Schueler, T. R., L. Fraley-McNeal, and K. Cappiella, 2009. Is impervious cover still important? Review of recent research. Journal of Hydrologic Engineering 14(4): 309-315. doi: 10.1061/(ASCE)1084-0699(2009)14:4(309).   DOI
5 Schueler, T., 1994. The importance of imperviousness. Watershed protection techniques 1(3): 100-101.
6 Shin, H., Y. Choi, and J. Yi, 2019. Analysis of the local characteristics of flood damage vulnerability in an urban area: the Han river basin. Journal of the Korean Society of Hazard Mitigation 19(5): 293-303. doi:10.9798/KOSHAM.2019.19.5.293.   DOI
7 Vogel, R. M., 2011. Hydromorphology.
8 Wagener, T., M. Sivapalan, P. A. Troch, B. L. McGlynn, C. J. Harman, H. V. Gupta, and J. S. Wilson, 2010. The future of hydrology: An evolving science for a changing world. Water Resources Research 46(5). doi: 10.1029/2009WR008906.   DOI
9 Budyko, M. I., 1958. The heat balance of the earth's surface, US Dept. of Commerce. Weather Bureau, Washington, DC, USA.
10 Wang, C., S. Wang, B. Fu, and L. Zhang, 2016. Advances in hydrological modelling with the Budyko framework: A review. Progress in Physical Geography 40(3): 409-430. doi: 10.1177/0309133315620997.   DOI
11 Lee, J., H. Ha, M. Lee, M. Lee, T. Kim, Y. Cha, and J. Koo, 2020b. Assessment of water quality of major tributaries in seoul using water quality index and cluster analysis. Journal of Korean Society of Environmental Engineers 42(10): 452-462. doi:10.4491/KSEE. 2020.42.10.452.   DOI
12 Zhang, L., K. Hickel and Q. Shao, 2017. Predicting afforestation impacts on monthly streamflow using the DWBM model. Ecohydrology 10(2): e1821. doi:10.1002/eco.1821.   DOI
13 Bai, P., X. Liu, D. Zhang, and C. Liu, 2020. Estimation of the Budyko model parameter for small basins in China. Hydrological Processes 34(1): 125-138. doi: 10.1002/hyp.13577.   DOI
14 Donohue, R. J., M. L. Roderick, and T. R. McVicar, 2007. On the importance of including vegetation dynamics in Budyko's hydrological model. Hydrology and Earth System Sciences 11(2): 983-995. doi: 10.5194/hess-11-983-2007.   DOI
15 Huang, H., Y. Han, M. Cao, J. Song, and H. Xiao, 2016. Spatial-temporal variation of aridity index of China during 1960-2013. Advances in Meteorology 2016: 1-10. doi: 10.1155/2016/1536135.   DOI
16 Kim, K., H. Kim, H. Lee, S. M. Jun, S. Hwang, J. H. Song, and M. S. Kang, 2021. Development and assessment of watershed management indicators using the Budyko framework parameter. Sustainability 13(7): 3864. doi: 10.3390/su13073864.   DOI
17 Ministry of Environment, 2017. A study on the selection and building of a water cycle city through the introduction of low-impact development.
18 Oudin, L., B. Salavati, C. Furusho-Percot, P. Ribstein, and M. Saadi, 2018. Hydrological impacts of urbanization at the catchment scale. Journal of Hydrology 559: 774-786. doi: 10.1016/j.jhydrol.2018.02.064.   DOI
19 Pumo, D., E. Arnone, A. Francipane, D. Caracciolo, and L. V. Noto, 2017. Potential implications of climate change and urbanization on watershed hydrology. Journal of Hydrology 554: 80-99. doi:10.1016/j.jhydrol.2017.09.002.   DOI
20 Xing, W., W. Wang, S. Zou, and C. Deng, 2018. Projection of future runoff change using climate elasticity method derived from Budyko framework in major basins across China. Global and Planetary Change 162: 120-135. doi: 10.1016/j.gloplacha.2018.01.006.   DOI
21 Choi, W. H., J. W. Shin, H. J. Oh, M. H. Choi, and J. Y. Park, 2009. A study of index and method for estimating the rate of rehabilitated hydrological cycle. Korean society of civil engineers 2114-2117.
22 Hamel, P., A. J. Guswa, J. Sahl, and L. Zhang, 2017. Predicting dry-season flows with a monthly rainfall-runoff model: Performance for gauged and ungauged catchments. Hydrological Processes 31(22): 3844-3858. doi: 10.1002/hyp.11298.   DOI
23 Hu, S., C. Liu, H. Zheng, Z. Wang, and J. Yu, 2012. Assessing the impacts of climate variability and human activities on streamflow in the water source area of Baiyangdian Lake. Journal of Geographical Sciences 22(5): 895-905. doi: 10.1007/s11442-012-0971-9.   DOI
24 Kanungo, T., D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman, and A. Y. Wu, 2002. An efficient k-means clustering algorithm: Analysis and implementation. IEEE transactions on pattern analysis and machine intelligence 24(7): 881-892. doi:10.1109/TPAMI.2002.1017616.   DOI
25 Kim, J. H., J. C. Joo, C. M. Ahn, and D. H. Hwang, 2021. Water quality assessment of 14 reservoirs in geum river basin using multivariate statistical analysis. Journal of Korean Society of Environmental Engineers 43(3): 171-186. doi:10.4491/KSEE.2021.43.3.171.   DOI
26 Barnett, T. P., D. W. Pierce, H. G. Hidalgo, C. Bonfils, B. D. Santer, T. Das, and M. D. Dettinger, 2008. Humaninduced changes in the hydrology of the western United States. Science 319(5866): 1080-1083. doi: 10.1126/science.1152538.   DOI
27 Wang, D., and M. Hejazi, 2011. Quantifying the relative contribution of the climate and direct human impacts on mean annual streamflow in the contiguous United States. Water Resources Research 47(10). doi: 10.1029/2010WR010283.   DOI
28 Kuchment, L. S., 2004. The hydrological cycle and human impact on it. Water Resources Management, 40.
29 Black, A. R., J. S. Rowan, R. W. Duck, O. M. Bragg, and B. E. Clelland, 2005. DHRAM: a method for classifying river flow regime alterations for the EC Water Framework Directive. Aquatic Conservation: Marine and Freshwater Ecosystems 15(5): 427-446. doi: 10.1002/aqc.707.   DOI
30 Budyko, M. I., 1974. Climate and life (Vol. 508). New York: Academic press.
31 Lee, H. C., Y. J. Cho, B. Lim, and S. B. Kim, 2020a. Study on the association of casualties and classification of heat wave weather patterns in South Korea using K-means clustering analysis. Journal of the Korean Society of Hazard Mitigation 20(3): 11-18. doi: 10.9798/KOSHAM.2020.20.3.11.   DOI
32 Li, D., M. Pan, Z. Cong, L. Zhang, and E. Wood, 2013. Vegetation control on water and energy balance within the Budyko framework. Water Resources Research 49(2): 969-976. doi: 10.1002/wrcr.20107.   DOI
33 Milly, P. C. D., J. Betancourt, M. Falkenmark, R. M. Hirsch, Z. W. Kundzewicz, D. P. Lettenmaier, and R. J. Stouffer, 2008. Stationarity is dead: Whither water management?. Science 319(5863): 573-574. doi:10.1126/science.1151915.   DOI
34 Wang, X., 2014. Advances in separating effects of climate variability and human activity on stream discharge: An overview. Advances in Water Resources 71: 209-218. doi:10.1016/j.advwatres.2014.06.007.   DOI