Impact of climate change on the sensitivity and uncertainty of HBV hydrologic model parameters

被引:0
|
作者
Ma, Qiumei [1 ]
Gui, Xu [1 ]
Xiong, Lihua [2 ]
Song, Wenjie [3 ,4 ]
Li, Jiqing [1 ]
机构
[1] School of Water Resources and Hydropower Engineering, North China Electric Power University, Beijing
[2] State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan
[3] Institute of Geographical Sciences and Resources, Chinese Academy of Sciences, Beijing
[4] College of Resources and Environment, University of Chinese Academy of Sciences, Beijing
来源
Shuikexue Jinzhan/Advances in Water Science | 2024年 / 35卷 / 04期
基金
中国国家自然科学基金;
关键词
climate change; CMIP6; hydrological modeling; water balance; water cycle process simulation;
D O I
10.14042/j.cnki.32.1309.2024.04.004
中图分类号
学科分类号
摘要
Elucidating the impact of climate change on watershed hydrological model parameters is a fundamental scientific issue for analyzing parameter transferability and estimating future water balance components. Based on meteorological data from three global climate models (CNRM, IPSL and MRI) under the CMIP6 framework, the HBV hydrological model was used to simulate monthly runoff changes in the Ganjiang River basin from 2015 to 2100. The sensitivity and uncertainty of typical parameters controlling runoff simulation processes under climate change were quantified and evaluated. The major findings of this research are as follows: ① In scenarios where future precipitation either increases or decreases, the sensitivity of model parameters is generally higher relative to the stable precipitation scenario, with the soil module parameters (which calculate soil evapotranspiration and water content) being most sensitive. ② The amount and intra- annual distribution of precipitation could influence parameters′ sensitivity. ③ If future climate change would significantly alter the proportions of runoff components (fast and slow flow), particularly under future scenarios of increased precipitation, more attention should be paid to the response module parameters. © 2024 International Research and Training Center on Erosion and Sedimentation and China Water and Power Press. All rights reserved.
引用
收藏
页码:556 / 568
页数:12
相关论文
共 28 条
  • [1] STEPHENS C M, JOHNSON F M, MARSHALL L A., Implications of future climate change for event-based hydrologic models, Advances in Water Resources, 119, pp. 95-110, (2018)
  • [2] KONAPALA G, MISHRA A K, WADA Y, Et al., Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation, Nature Communications, 11, (2020)
  • [3] YANG P, ZHANG S Q, XIA J, Et al., Analysis of drought and flood alternation and its driving factors in the Yangtze River basin under climate change, Atmospheric Research, 270, (2022)
  • [4] SCHNORBUS M A, CANNON A J., Statistical emulation of streamflow projections from a distributed hydrological model: application to CMIP3 and CMIP5 climate projections for British Columbia, Canada, Water Resources Research, 50, 11, pp. 8907-8926, (2014)
  • [5] XIAO H, LU G H, WU Z Y, Et al., Flood response to climate change in the Pearl River basin for the next three decades, Journal of Hydraulic Engineering, 44, 12, pp. 1409-1419, (2013)
  • [6] DESSU S B, MELESSE A M., Impact and uncertainties of climate change on the hydrology of the Mara River basin, Kenya/ Tanzania, Hydrological Processes, 27, 20, pp. 2973-2986, (2013)
  • [7] ZHANG A J, ZHANG C, FU G B, Et al., Assessments of impacts of climate change and human activities on runoff with SWAT for the Huifa River basin, Northeast China, Water Resources Management, 26, 8, pp. 2199-2217, (2012)
  • [8] ZHU Q., Influence of water input and hydrological model parameters on hydrological simulation due to climate change, (2017)
  • [9] POULIN A N, BRISSETTE F, LECONTE R, Et al., Uncertainty of hydrological modelling in climate change impact studies in a Canadian, snow-dominated river basin, Journal of Hydrology, 409, 3, pp. 626-636, (2011)
  • [10] MELSEN L A, GUSE B., Hydrological drought simulations: how climate and model structure control parameter sensitivity, Water Resources Research, 55, 12, pp. 10527-10547, (2019)