共被期刊论文引用了3次
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| 1 | 浑太森林流域径流过程模拟显示文摘基于浑河与太子河上游1998—2007年北口前站和南甸峪站水文数据以及清原、新宾和本溪县气象站点同期气象数据,应用DHSVM分布式水文模型模拟浑太流域的水文过程,验证模型的科学适用性,并提供最敏感模型参数的参考值.结果表明:浑河源区月径流模拟的Nash-Suttclife系数(E值)在率定期(1998—2002年)和验证期(2003—2007年)分别达到0.9675和0.8957,较好重现了研究区的月径流过程.太子河上游流域的年、月径流模拟值的E值均大于0.6,说明模型在浑太流域有较好的适用性、率定的参数方案有良好的可靠性.本文为无站点观测资料的流域水文研究建立了一个坚实的框架,并构建了合理的参数方案. | 蔡研聪 金昌杰 王安志 关德新 吴家兵 袁凤辉 | 2013 | 应用生态学报2013，24，10： | 4 |
| 2 | EnKF优化土壤湿度方程中参数的性能研究显示文摘集合卡尔曼滤波(EnKF)是一种灵活有效的序贯数据同化方法,解决参数优化问题具有优势:一是可以显式地考虑多源不确定性,从而避免对参数的过度调整来弥补其他来源的误差而产生次优参数;二是实时处理最新更新的观测数据,从而不需要存储和同时处理所有历史数据;三是使用集合和蒙特卡罗方法来表征和预报相关误差统计量,不需要封闭解逼近,易于实施。论文借助一维土壤湿度模型,通过观测系统模拟试验的方式,评估EnKF对水力学函数参数的优化效果。结果表明,敏感参数更易得到最优估值,优化效果不受初始猜测及观测误差设置等的影响。和直观想法相反,增加同化频率可能会使估值结果不稳定。 | 李超 惠建忠 唐千红 杨霏云 | 2015 | 自然资源学报2015，30，12： | 2 |
| 3 | Assimilating ASAR Data for Estimating Soil Moisture Profile Using an Ensemble Kalman Filter显示文摘Active microwave remote sensing data were used to calculate the near-surface soil moisture in the vegetated areas.In this study,Advanced Synthetic Aperture Radar(ASAR)observations of surface soil moisture content were used in a data assimilation framework to improve the estimation of the soil moisture profile at the middle reaches of the Heihe River Basin,Northwest China.A one-dimensional soil moisture assimilation system based on the ensemble Kalman filter(EnKF),the forward radiative transfer model,crop model,and the Distributed Hydrology-Soil-Vegetation Model(DHSVM)was developed.The crop model,as a semi-empirical model,was used to estimate the surface backscattering of vegetated areas.The DHSVM is a distributed hydrology-vegetation model that explicitly represents the effects of topography and vegetation on water fluxes through the landscape.Numerical experiments were conducted to assimilate the ASAR data into the DHSVM and in situ soil moisture at the middle reaches of the Heihe River Basin from June20 to July 15,2008.The results indicated that EnKF is effective for assimilating ASAR observations into the hydrological model.Compared with the simulation and in situ observations,the assimilated results were significantly improved in the surface layer and root layer,and the soil moisture varied slightly in the deep layer.Additionally,EnKF is an efficient approach to handle the strongly nonlinear problem which is practical and effective for soil moisture estimation by assimilation of remote sensing data.Moreover,to improve the assimilation results,further studies on obtaining more reliable forcing data and model parameters and increasing the efficiency and accuracy of the remote sensing observations are needed,also improving estimation accuracy of model operator is important. | YU Fan LI Haitao GU Haiyan HAN Yanshun | 2013 | Chinese Geographical Science2013，23，6： | 0 |
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