Study on Spatial Variability of Rainfall–Runoff and Rainstorm–Flood Relationships in Mountainous Area of the Daqing River Basin
Publication: Journal of Hydrologic Engineering
Volume 27, Issue 7
Abstract
Spatial variability of rainfall–runoff and rainstorm–flood relationships are very important to water planning and utilization. Taking the mountainous area of Daqing River basin as the studied area, this paper reveals the variability point and inconsistency characteristics of rainfall–runoff and rainstorm–flood and presents a new approach using a copula function and geostatistical method to show spatial variability of rainfall–runoff and rainstorm–flood with the proposed virtual runoff and virtual flood. The results demonstrate that rainfall–runoff and rainstorm–flood relationships exist during great changes before and after variation point. Especially after the variation point, rainfall–runoff and rainstorm–flood relationships show more inconsistency with moderate and strong spatial variability, which are mostly in the northern area of the basin. Meanwhile, spatial variability in the rainfall–runoff relationship is similar to that in the rainstorm–flood relationship.
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Data Availability Statement
The measured data of runoff and precipitation, topographic data, and hydrometeorological data used during the study were provided by a third party. Direct request for these materials may be made to the provider as indicated in the Acknowledgments.
Acknowledgments
This research is supported by the National Key R&D Program of China (Grant No. 2021YFC3200205), Scientific and Technologic Research Program of Henan Province (192102310508), The Open Grants of the State Key Laboratory of Severe Weather (2021LASW-A15), and the Natural Sciences Foundation of Henan Province (212300410404).
References
Chang, C.-M., and H.-D. Yeh. 2018. “Spectral analysis of temporal non-stationary rainfall-runoff processes.” J. Hydrol. 559 (Apr): 84–88. https://doi.org/10.1016/j.jhydrol.2018.02.017.
Das, J., S. Jha, and M. K. Goyal. 2020. “Non-stationary and copula-based approach to assess the drought characteristics encompassing climate indices over the Himalayan states in India.” J. Hydrol. 580 (Jan): 124356. https://doi.org/10.1016/j.jhydrol.2019.124356.
Debele, S. E., E. Bogdanowicz, and W. G. Strupczewski. 2017. “Around and about an application of the GAMLSS package to non-stationary flood frequency analysis.” Acta Geophys. 65 (4): 885–892. https://doi.org/10.1007/s11600-017-0072-3.
Du, R., F. Shang, and N. Ma. 2019. “Automatic mutation feature identification from well logging curves based on sliding t test algorithm.” Cluster Comput. 22 (6): 14193–14200. https://doi.org/10.1007/s10586-018-2267-z.
Duan, K., Y. Mei, and L. Zhang. 2016. “Copula-based bivariate flood frequency analysis in a changing climate—A case study in the Huai River Basin, China.” J. Earth Sci. 27 (1): 37–46. https://doi.org/10.1007/s12583-016-0625-4.
Endale, D. M., D. S. Fisher, and J. L. Steiner. 2006. “Hydrology of a zero-order Southern Piedmont watershed through 45 years of changing agricultural land use. Part 1. Monthly and seasonal rainfall-runoff relationships.” J. Hydrol. 316 (1–4): 1–12. https://doi.org/10.1016/j.jhydrol.2005.04.008.
Gentilucci, M., M. Barbieri, H. S. Lee, and D. Zardi. 2019. “Analysis of rainfall trends and extreme precipitation in the middle Adriatic side, Marche Region (Central Italy).” Water 11 (9): 1948. https://doi.org/10.3390/w11091948.
Guo, A., J. Chang, Y. Wang, and Y. Li. 2015. “Variation characteristics of rainfall-runoff relationship and driving factors analysis in Jinghe river basin in nearly 50 years.” Trans. Chin. Soc. Agric. Eng. 31 (14): 165–171. https://doi.org/10.11975/j.issn.1002-6819.2015.14.023.
Han, C., S. Liu, Y. Guo, H. Lin, Y. Liang, and H. Zhang. 2018. “Copula-based analysis of flood peak level and duration: Two case studies in Taihu Basin, China.” J. Hydrol. Eng. 23 (6): 05018009. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001661.
Hu, Q., Z. Li, L. Wang, Y. Huang, Y. Wang, and L. Li. 2019. “Rainfall spatial estimations: A review from spatial interpolation to multi-source data merging.” Water 11 (3): 579. https://doi.org/10.3390/w11030579.
Hu, S., Z. Wang, Y. Wang, H. Wu, J. Jin, X. Feng, and L. Cheng. 2010. “Encounter probability analysis of typhoon and plum rain in the Taihu Lake Basin.” Sci. China Technol. Sci. 53 (12): 3331–3340. https://doi.org/10.1007/s11431-010-4158-2.
Jhong, B. C., and C. P. Tung. 2018. “Evaluating future joint probability of precipitation extremes with a copula-based assessing approach in climate change.” Water Resour. Manage. 32 (13): 4253–4274. https://doi.org/10.1007/s11269-018-2045-y.
Kim, J., J. Lee, D. Kim, and B. Kang. 2019. “The role of rainfall spatial variability in estimating areal reduction factors.” J. Hydrol. 568 (Apr): 416–426. https://doi.org/10.1016/j.jhydrol.2018.11.014.
Klein, B., M. Pahlow, Y. Hundecha, and A. Schumann. 2010. “Probability analysis of hydrological loads for the design of flood control systems using copulas.” J. Hydrol. Eng. 15 (5): 360–369. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000204.
Lei, H. F., P. Xie, and G. C. Chen. 2007. “Comparison and analysis on the performance of hydrological time series change-point testing methods.” Water Resour. Power 25 (4): 36–40.
Li, Z., X. Li, and Z. Xu. 2010. “Impacts of water conservancy and soil conservation measures on annual runoff in the Chaohe River Basin during 1961–2005.” J. Geog. Sci. 20 (6): 947–960. https://doi.org/10.1007/s11442-010-0823-4.
Lian, Y., M. Sun, J. Wang, Q. Luan, M. Jiao, X. Zhao, and X. Gao. 2021. “Quantitative impacts of climate change and human activities on the runoff evolution process in the Yanhe River Basin.” Phys. Chem. Earth 2021 (1): 122. https://doi.org/10.1016/j.pce.2021.102998.
Liu, X., D. Peng, and Z. Xu. 2017. “Identification of the impacts of climate changes and human activities on runoff in the Jinsha River Basin, China.” Adv. Meteorol. 2017 (1): 4631831. https://doi.org/10.1155/2017/4631831.
Mair, A., and A. Fares. 2011. “Comparison of rainfall interpolation methods in a mountainous region of a tropical island.” J. Hydrol. Eng. 16 (4): 371–383. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000330.
Michael, R., C. R. O’Lenick, A. Monaghan, O. Wilhelmi, C. Wiedinmyer, M. Hayden, and M. Estes. 2019. “Application of geostatistical approaches to predict the spatio-temporal distribution of summer ozone in Houston, Texas.” J. Exposure Sci. Environ. Epidemiol. 29 (6): 806–820. https://doi.org/10.1038/s41370-018-0091-4.
Mlynski, D., A. Walega, A. Petroselli, F. Tauro, and M. Cebulska. 2019. “Estimating maximum daily precipitation in the upper Vistula basin, Poland.” Atmosphere 10 (2): 43. https://doi.org/10.3390/atmos10020043.
Najjari, V., and M. G. Unsal. 2012. “An application of Archimedean copulas for meteorological data.” Gazi Univ. J. Sci. 25 (2): 417–424.
Ohba, M., and S. Sugimoto. 2019. “Differences in climate change impacts between weather patterns: Possible effects on spatial heterogeneous changes in future extreme rainfall.” Clim. Dyn. 52 (7–8): 4177–4191. https://doi.org/10.1007/s00382-018-4374-1.
Pasini, M. P. B., A. D. Lucio, and A. Cargnelutti. 2014. “Semivariogram models for estimating fig fly population density throughout the year.” Pesqui. Agropecu. Bras. 49 (7): 493–505. https://doi.org/10.1590/S0100-204X2014000700001.
Razafimahefa, H., and F. Anctil. 2014. Performance and reliability of probabilistic scenarios of interpolated rainfall based on geostatistics.” J. Hydrol. Eng. 19 (6): 1214–1223. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000913.
Rigby, R. A., and D. M. Stasinopoulos. 2005. “Generalized additive models for location, scale and shape.” J. R. Stat. Soc. 54 (3): 507–554. https://doi.org/10.1111/j.1467-9876.2005.00510.x.
Sklar, E. 1959. “The treatment of nausea and vomiting with trifluoperazine (stelazine).” Br. J. Clin. Pract. 13 (7): 505.
Xiong, L., C. Jiang, and T. Du. 2014. “Statistical attribution analysis of the nonstationarity of the annual runoff series of the Weihe River.” Water Sci. Technol. 70 (5): 939–946. https://doi.org/10.2166/wst.2014.322.
Xu, L.-J. 2011. “Analysis on dynamic feature of the rainfall-runoff relationship in the Daqing River basin under the influence of human activities.” South-to-North Water Trans. Water Sci. Technol. 9 (2): 73–76.
Xu, Y., Z. Ge, J. Wang, W. Li, and S. Feng. 2019. “Study on relationship between soil salinization and groundwater table depth based on indicator Kriging.” Trans. Chin. Soc. Agric. Eng. 35 (1): 123–130. https://doi.org/10.11975/j.issn.1002-6819.2019.01.015.
Yang, X., J. Wang, and S. Weng. 2020. “Joint probability study of destructive factors related to the ‘Triad’ phenomenon during typhoon events in the coastal regions: Taking Jiangsu Province as an example.” J. Hydrol. Eng. 25 (11): 05020038. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002007.
Zhang, J., D. Han, Y. Song, and Q. Dai. 2018. “Study on the effect of rainfall spatial variability on runoff modelling.” J. Hydroinf. 20 (3): 577–587. https://doi.org/10.2166/hydro.2018.129.
Zhu, J. T., M. C. Stone, and W. Forsee. 2012. “Analysis of potential impacts of climate change on intensity-duration-frequency (IDF) relationships for six regions in the United States.” J. Water Clim. Change 3 (3): 185–196. https://doi.org/10.2166/wcc.2012.045.
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Journal of Hydrologic Engineering
Volume 27 • Issue 7 • July 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Aug 17, 2021
Accepted: Feb 15, 2022
Published online: Apr 18, 2022
Published in print: Jul 1, 2022
Discussion open until: Sep 18, 2022
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