Study on multi-objective optimization of hydrological model based on runoff and soil moisture
WU Pinghui1, ZHANG Jiapeng2, WANG Jiahu2, JIANG Jieyu3
1. Hunan Institute of Hydrological Instrument and Equipment Testing, Changsha 410007; 2. College of Hydrology and Water Recourses, Hohai University, Nanjing 210098, China; 3. Hunan Institute of Water Resources and Hydropower Research, Changsha 410007
Abstract：In recent years, the progress of remote sensing technology has brought great convenience for obtaining large-scale continuous hydrological variables. In order to explore the feasibility of using other remote sensing hydrological variables to calibrate hydrological model parameters in case of lack of data in the basin, the Xin'anjiang model was taken as the research model using Shuffled Complex Evolution (SCE-UA) algorithm to calibrate hydrological model parameters, and the impact of combined remote sensing soil moisture and runoff data on model parameter calibration results in case of short series discharge data was analyzed. The results show that there are some uncertainties when using short series discharge data to calibrate hydrological model, and the simulation accuracy is poor in the validation period, while the simulation results obtained by introducing soil moisture to carry out parameter calibration are reduced in the rate period, but it is better than the former in the validation period, and it can be close to the level of using long series discharge data to calibrate parameters.
吴平辉, 张佳鹏, 王加虎, 蒋婕妤. 径流与土壤湿度数据联合率定水文模型参数研究[J]. 中国防汛抗旱, 2022, 32(4): 72-76.
WU Pinghui, ZHANG Jiapeng, WANG Jiahu, JIANG Jieyu. Study on multi-objective optimization of hydrological model based on runoff and soil moisture. journal1, 2022, 32(4): 72-76.
[1] Brocca L, Moramarco T, Melone F, et al. Assimilation of Surfaceand Root-Zone ASCAT Soil Moisture Products Into Rainfall-Runoff Modeling[J].IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(7):2542-2555. [2] Chen F, Crow W T, Starks P J, et al. Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture[J]. Advances in Water Resources, 2011, 34(4):526-536. [3] Wanders N, Bierkens M F P, De Jong S M, et al. The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models[C]//Egu General Assembly Conference. EGU General Assembly Conference Abstracts, 2013. [4] Yuan X,Ma Z,Pan M,et al. Microwave remote sensing of shortterm droughts during crop growing seasons[J].Geophysical Research Letters, 2015, 42(11):4394-4401. [5] 雷芳妮.微波遥感土壤湿度误差估计与水文数据同化[D].武汉大学, 2016. [6] 任立良,刘新仁,郝振纯.基于HUBEX试验资料的土壤水时空分布模拟[J].水文, 2000(5):1-5. [7] Miralles D G, Holmes T R, Jeu D R, et al. Global land-surface evaporation estimated from satellite-based observations[J]. Hydrology and Earth System Sciences, 2010, 15(2):453-469. [8] Dorigo W, Wagner W, Albergel C, et al. ESA CCI Soil Moisture for improved Earth system understanding:State-of-the art and future directions[J].Remote Sensing of Environment, 2017:S0034425717303061. [9] Renjun Z.The Xinanjiang model applied in China[J].Journal of Hydrology, 1992:371-381. [10] 刘金涛,张佳宝.前期土壤含水量对水文模拟不确定性影响分析[J].冰川冻土, 2006, 28(4):519-525. [11] Rushton K R, Eilers V H, Carter R C, et al. Improved soil moisture balance methodology for recharge estimation[J].Journal of Hydrology, 2006, 318(1):379-399. [12] Srivastava P K, Han D, Ramirez M A, et al. Appraisal of CCI soil moisture at a catchment scale in a temperate maritime climate[J]. Journal of Hydrology, 2013:292-304. [13] Duan Q, Sorooshian S, Gupta V K, et al. Effective and efficient global optimization for conceptual rainfall-runoff models[J].Water Resources Research, 1992, 28(4):1015-1031. [14] Gupta H V, Kling H, Yilmaz K K, et al.Decomposition of the mean squared error and NSE performance criteria:Implications for improving hydrological modelling[J].Journal of Hydrology, 2009, 377(1-2):80-91. [15] Chen X, Yang T, Wang X, et al.Uncertainty Intercomparison of Different Hydrological Models in Simulating Extreme Flows[J].Water Resources Management, 2013, 27(5):1393-1409. [16] Zhuo L, Dai Q, Han D. Evaluation of SMOS soil moisture retrievals over the central United States for hydro-meteorological application[J]. Physics and Chemistry of the Earth, Parts A/B/C, 2015, 83-84:146-155. [17] Silvestro F, Gabellani S, Rudari R, et al. Uncertainty reduction and parameter estimation of a distributed hydrological model with ground and remote-sensing data[J].Hydrology and Earth System Sciences, 2015, 19(4):1727-1751. [18] 崔兴齐,滕建标,姚晓磊,等.流量数据量对分布式水文模型参数率定结果的影响分析——以黑河流域上游为例[J].北京师范大学学报(自然科学版), 2014(5):570-575.
2022, Vol. 32 
