四湖流域径流及蓝水绿水资源时空分布模拟

为了解四湖流域的水文特征及蓝水绿水资源时空分布,通过水系概化、子流域划分、总出口概化、湖泊概化,完成SWAT模型构建,采用SUFI-2算法分析了模型参数的敏感性,基于决定系数R2、Nash-Sutcliffe效率系数E_NS与相对误差|R_e|评价了模型的有效性。结果表明:1)对四湖流域径流模拟影响较大的参数有ALPHA_BF (基流α系数)、GWQMN (基流判定系数)、CH_K2(河道水力传导系数)、CN2_AGRLSCS曲线系数(耕地)]、CH_N2(主河道曼宁系数)和SOL_AWC (土壤层含水率参数),表明地下水模块参数和河网概化参数对四湖流域水文过程影响较大;2)月径流模拟过程与实测水文过程拟合较好,率定期和验证期R2与E_NS分别为0.75、0.72和0.69、0.63,|R_e|均在5%以内,均达到令人满意的结果;3)四湖流域绿水资源量年度变化相比蓝水资源更为稳定,降雨量与蓝水资源呈正相关,在空间上蓝水资源分布较为均匀,绿水资源分布呈西北部、东南部多,中部少的分布特征,绿水系数与绿水资源分布特征相似,降雨量对蓝水资源空间分布影响较大。

SIMULATION OF RUNOFF AND SPATIO-TEMPORAL VARIATIONS OF BLUE AND GREEN WATER RESOURCES IN SIHU BASIN

To understand the hydrological characteristics of Sihu Basin and the spatio-temporal distribution of blue water and green water resources, a SWAT model was constructed through generalization of water systems, division of sub-basins, generalization of total outlets, and generalization of lakes. The SUFI-2 algorithm was used to analyse the sensitivity of the model parameters, and the effectiveness of the model was evaluated based on the determination coefficient R2, the Nash-Sutcliffe efficiency coefficient E_NS and the relative error|R_e|. The research results showed that:1) the parameters that had a greater impact on runoff simulation in Sihu Basin were ALPHA_BF, GWQMN, CH_K2, CN2_AGRL, CH_N2 and SOL_AWC, indicating that the groundwater module parameters and river network generalization parameters had a greater impact on the hydrological process of Sihu Basin. 2) the monthly runoff simulation process fitted well with the measured hydrological process. The R2 and E_NS of the regular rate and the verification period was 0.75, 0.72 and 0.69, 0.63, respectively, and the|R_e|was within 5%, while satisfactory results were achieved. 3) The annual change of the number of green water resources in the Sihu Basin was more stable than that of blue water resources, and rainfall was positively correlated with blue water resources. The distribution of blue water resources was relatively uniform in space. The distribution of green water resources was more in the northwest and southeast, and less in the middle. The green water coefficient was similar to the distribution characteristics of green water resources, and rainfall had a greater impact on spatial distribution of blue water resources.