Impact Analysis of Precipitation and Runoff Variation on Simulation Accuracy and Parameters of Monthly Water Balance Model

WU Di, GUO Jia-li, XIANG Xiao-li, YU Zhong-bo

Journal of Changjiang River Scientific Research Institute ›› 2020, Vol. 37 ›› Issue (7) : 41-46.

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Journal of Changjiang River Scientific Research Institute ›› 2020, Vol. 37 ›› Issue (7) : 41-46. DOI: 10.11988/ckyyb.20190311
WATER RESOURCES AND ENVIRONMENT

Impact Analysis of Precipitation and Runoff Variation on Simulation Accuracy and Parameters of Monthly Water Balance Model

  • WU Di1,2,3, GUO Jia-li4, XIANG Xiao-li3, YU Zhong-bo1,2,3
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Abstract

The purpose of this research is to assess the reliability of hydrological models, two-parameter monthly water balance model for example, in changing environments. First of all the consistency of precipitation and runoff data in 104 typical catchments in the United States is analyzed by Mann-Kendall method; in line with variable fuzzy theory, the impact of the consistency of precipitation and runoff data on the simulation accuracy of the two-parameter monthly water balance model is examined; furthermore the influences of the consistency of precipitation and runoff data and the climatic characteristics of catchment on the model parameters are also investigated. Results show that the consistency of precipitation or runoff data is damaged in 92.31% of the study catchment. Evaluation on the simulation effect of the model with variable fuzzy sets implies that the variation of precipitation and runoff trend weakens the simulation ability of hydrological model. The deterioration of precipitation consistency is the main reason for the weakening of hydrological model simulation ability. Moreover, the variable fuzzy method could accurately identify the secondary factors affecting the simulation ability. In addition, model parameters C and SC both increase with the augment of the annual average runoff coefficient. Parameter C represents the wetting degree of the basin, and parameter SC represents the storage capacity of the basin. The research findings offer technical support for flood control, draught relief, water resources planning and management.

Key words

precipitation and runoff variation / two-parameter monthly water balance model / model parameter / simulation accuracy / variable fuzzy set / consistency

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WU Di, GUO Jia-li, XIANG Xiao-li, YU Zhong-bo. Impact Analysis of Precipitation and Runoff Variation on Simulation Accuracy and Parameters of Monthly Water Balance Model[J]. Journal of Changjiang River Scientific Research Institute. 2020, 37(7): 41-46 https://doi.org/10.11988/ckyyb.20190311

References

[1] 李红霞,张新华,张永强,等. 缺资料流域水文模型参数区域化研究进展[J]. 水文,2011,31(3):13-17.
[2] BLÖSCHL G, MONTANARI A. Climate Change Impacts—Throwing the Dice?[J]. Hydrological Processes, 2010, 24(3): 374-381.
[3] CORON L, ANDREASSIAN V, PERRIN C, et al. Crash Testing Hydrological Models in Contrasted Climate Conditions: An Experiment on 216 Australian Catchments[J]. Water Resources Research, 2012, 48(5), doi: 10.1029/2011WR011721.
[4] BRIGODE P, OUDIN L, PERRIN C. Hydrological Model Parameter Instability: A Source of Additional Uncertainty in Estimating the Hydrological Impacts of Climate Change?[J]. Journal of Hydrology, 2013, 476: 410-425.
[5] 张利茹,王兴泽,王国庆,等.变化环境下水文资料序列的可靠性与一致性分析[J]. 水文,2015,35(2):39-43.
[6] 熊立华,郭生练,付小平,等. 两参数月水量平衡模型的研制和应用[J].水科学进展,1996(增刊1): 80-86.
[7] 刘欣蔚, 王 浩, 雷晓辉,等. 粒子群算法参数设置对新安江模型模拟结果的影响研究[J]. 南水北调与水利科技, 2018,16(1):69-74,208.
[8] 刘 冀,董晓华,张军锋. 月水量平衡模型的参数率定及组合预报[J]. 人民黄河, 2012, 34 (10): 28-31.
[9] 王 乐,刘德地,李天元,等. 基于多变量M-K检验的北江流域降水趋势分析[J]. 水文,2015,35(4):85-90.
[10]邹 强,周建中,周 超,等. 基于可变模糊集理论的洪水灾害风险分析[J]. 农业工程学报, 2012,28(5):126-132.
[11]陈守煜,袁晶瑄,郭 瑜. 可变模糊决策理论及其在水库防洪调度决策中应用[J]. 大连理工大学学报, 2008(2): 259-262.
[12]苏艳娜,柴春岭,杨亚梅,等. 常熟市农业生态环境质量的可变模糊评价[J]. 农业工程学报, 2007(11): 245-248.
[13]周惠成,张 丹. 可变模糊集理论在旱涝灾害评价中的应用[J]. 农业工程学报, 2009,25(9):56-61.
[14]吴开亚,金菊良,周玉良,等. 流域水资源安全评价的集对分析与可变模糊集耦合模型[J]. 四川大学学报(工程科学版), 2008(3): 6-12.
[15]李 帅,刘 冀,董晓华,等. 可变模糊模型在水资源短缺风险评价中的应用[J]. 水电能源科学, 2009,27(5):21-23,85.
[16]陈守煜,李 敏. 基于可变模糊集理论的水资源可再生能力评价模型[J]. 水利学报, 2006(4): 431-435.
[17]MORIASI D, ARNOLD J, VAN LIEW M W, et al. Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations[J]. Transactions of the ASABE, 2007, 50(3): 885-900.
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