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【目的】建立徒骇马颊河流域的分布式水文模型,为进行该地区灌溉制度优化提供支持。【方法】首先运用洗牌复形演化(SCE-UA)算法在禹城试验站和洪门试验站对分布式水文模型(SWAT)中的作物参数进行率定,接着以遥感监测的蒸散数据为目标,应用拉丁超立方-单次单因素(LH-OAT)方法对蒸散发(ET)相关的参数进行了敏感性分析,用序贯不确定性(SUFI-2)算法优化出一套参数范围并进行不确定性分析。在此基础上,在考虑模型不确定性的情况下对冬小麦-夏玉米轮作体系产量的长期模拟结果进行验证。【结果】作物参数率定结果表明,禹城试验站上冬小麦和夏玉米产量的相对误差分别为7.02%和16.60%,洪门试验站上冬小麦和夏玉米产量的相对误差分别为0.09%和0.10%。ET参数率定和统计年鉴产量验证结果:除了NS系数,P_factor、R_factor以及R2的模拟精度较高。【结论】依据徒骇马颊河流域的特点进行SWAT模型相关参数的率定,得到较好的模拟结果,为进一步深入研究该地区水分生产函数和优化灌溉制度打下了基础。
【Objective】 To establish a distributed hydrological model of Tujiamage river basin and provide support for the optimization of irrigation system in this area. 【Method】 First, the crop parameters of Distributed Hydrological Model (SWAT) were calibrated in Shucheng Experimental Station and Hongmen Experimental Station by using shuffling complex evolution (SCE-UA) algorithm. Then the evapotranspiration data monitored by remote sensing were Objective To investigate the sensitivity of evapotranspiration (ET) parameters using the Latin hypercube-single factor (LH-OAT) method and to optimize a set of parameters using the SUFI-2 algorithm And carry on the uncertainty analysis. On this basis, the long-term simulation results of yield of winter wheat-summer maize cropping system are validated considering the model uncertainty. 【Result】 The results of crop parameter calibration showed that the relative errors of yield of winter wheat and summer maize at Yucheng experimental station were 7.02% and 16.60% respectively. The relative errors of output of winter wheat and summer maize at Hongmen experimental station were 0.09% and 0.10% %. ET Parameter Calibration and Statistical Yearbook Yield Verification Results: In addition to the NS coefficients, P_factor, R_factor, and R2 have higher simulation accuracy. 【Conclusion】 Based on the characteristics of Trekking River basin, the SWAT model parameters were calibrated and the simulation results were obtained, which laid the foundation for further study of the water production function and the optimization of irrigation system.