Free Search算法率定的Sacramento模型在东北寒旱区的应用

Application of Sacramento Model Calibrated by Free Search Algorithm in Cold and Arid Region of Northeast China

采用模型对比研究方法,以萨克拉门托(Sacramento,SAC)模型为研究对象,以新安江模型为参考,采用基于动物群体的自由搜索(Free search,FS)算法作为率定水文模型的优化算法,选取松花江水系和辽河水系的3个集水区为实证流域,通过对比FS算法率定的SAC模型和新安江模型在3个流域的模拟效果,验证SAC模型在东北寒旱区流域的适用性。研究结果表明,FS算法迭代计算过程简单,需要设置的算法参数较少,在率定SAC模型和新安江模型时效率较高;在相同的模拟条件下,FS算法率定的SAC模型模拟效果更好,其Nash模型效率系数高于新安江模型,表明SAC模型适用于东北寒旱区流域;但SAC模型在东北寒旱区的模拟精度还有待提升,模型尚需进一步发展和完善。

Free search（ FS）,which was set up based on the group of animal behavior,was adopted as an optimization algorithm to calibrate the Sacramento（ SAC） model and the Xin＇anjiang（ XAJ） model.Calculation of the calibrated SAC model and XAJ model were conducted for the three watersheds of Songhua River System and Liao River System. Applicability of the SAC model was validated in cold and arid regions of Northeast China via comparison of the simulation results between the SAC model and XAJ model. The results indicated that the iterative calculation process of FS was simple and needed a few settings of the algorithm parameters,and it exhibited relatively high efficiency in the process of SAC model and XAJ model calibration; the simulation result of the SAC model was better than that of the XAJ model under the same conditions and its Nash-Sutcliffe model efficiency coefficient was higher than that of XAJ model. Whereas,the simulation accuracy of the SAC model needed to be improved in the case of application to the cold and arid region of Northeast China,and the performance of the SAC model neededfurther development and improvement.