A Three-Parameter Hydrological Model for Monthly Runoff Simulation-A Case Study of Upper Hanjiang River Basin

被引:6
作者
Zou, Yixuan [1 ,2 ]
Yan, Baowei [1 ,2 ]
Feng, Baofei [3 ]
Zhang, Jun [3 ]
Tang, Yiwei [1 ,2 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Civil & Hydraul Engn, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Hubei Key Lab Digital River Basin Sci & Technol, Wuhan 430074, Peoples R China
[3] Changjiang Water Resource Commiss Minist Water Res, Bur Hydrol, Wuhan 430010, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
monthly hydrological model; proportionality hypothesis; sensitivity analysis; WATER-BALANCE MODELS; CLIMATE-CHANGE; TIME SCALES; PERFORMANCE; IMPACTS; BUDYKO;
D O I
10.3390/w15030474
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Monthly hydrological models are useful tools for runoff simulation and prediction. This study proposes a three-parameter monthly hydrological model based on the proportionality hypothesis (TMPH) and applies to the Upper Hanjiang River Basin (UHRB) in China. Two major modules are involved in the TMPH: the actual evapotranspiration and runoff, in which the coupled water-energy balance equation and the proportionality hypothesis are used for calculation, respectively. It is worth mentioning that the proportionality hypothesis was extended to the partitioning of the available water into water loss and runoff at the monthly scale, which demonstrates that the ratio of runoff to its potential value is equal to the ratio of continuing water loss to its potential value. Results demonstrate that the TMPH model performs well when the NSE values are 0.79 and 0.83, and the KGE values are 0.86 and 0.78 for calibration period and validation period, respectively. The widely used two-parameter monthly water balance (TWBM) model and ABCD model are compared with the proposed model. Results show that TMPH performs better than TWBM model with NSE increased by 0.07 and 0.11, and KGE increased by 0.02 and 0.16, respectively, whereas the TMPH performs similarly as the ABCD model in the calibration period, and performs slightly better in the validation period, with NSE increased by 0.02, and KGE increased by 0.03. Sensitivity analysis show that the simulation result is most sensitive to parameter n, followed by SC and lambda. In summary, the proposed model has strong applicability to the study area.
引用
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页数:13
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