[关键词]
[摘要]
为评价北山水库流域地表水资源, 选用 SWAT 软件构建了该流域的分布式水文模型。基于 201622018 年实 测水文数据以及高程、土地利用类型、土壤类型等数据, 完成了对北山水库流域的 SWAT 模型构建, 利用 SWAT2 CUP 软件对参数进行率定及敏感性分析, 选取决定系数( R2 ) 、纳什效率系数( NSE) 、平均相对误差绝对值( MARE) 和均方根误差( RMSE) 作为模型评价指标。结果表明: 北山水库月蓄水量模拟值与实测值吻合良好, 模型率定期和 验证期的 R2 均达到 01 89, NSE 分别达到 01 88 与 01 85, MARE 分别为 51 04% 与 41 23% , RMSE 分别为 11 15 @ 106 m3 与 01 90@ 106 m3 , 由此表明该模型能近似反映研究区的径流变化特征, 展示了 SWAT 模型在该流域的适用性。此 外, 基于验证的水文模型对主要参数进行敏感性分析, 表明影响该区径流模拟最为显著的两个参数是浅层地下水回 归流阈值和径流曲线数。
[Key word]
[Abstract]
SWAT soft war e was used to emplo y the distributed hy dr olog ical model t o evaluate the surface water resources in the Beishan Reser voir w atershed. Based on measur ed hydro lo gical data fr om 2016 to 2018 prov ided by the lo ca l wat ershed manag e2 ment institutio n, and the elevat ion, land use, and soil type data, the SWAT and SWAT2CUP so ftwar e w ere used to calibr ate and analyze the sensitiv ity of the par ameters in the Beishan Reserv oir w atershed. The coefficient of determination ( R2 ) , Nash2Sut2 cliffe efficiency ( NSE) , mean absolute relative erro r ( M ARE) and ro ot2mean2square erro r ( RM SE) w as selected as the model ev aluatio n index es. The results indicated that the simulated value of Beishan Reser vo irc s mo nthly water sto rag e show ed go od agr eement w ith the measured value. The mo del evaluation indexes R2 , NSE, M ARE and RMSE, w ere 01 89, 01 88, 51 04% and 11 15 @ 106m3 in calibration period, and 01 89, 01 85, 41 23% and 01 90 @ 106 m3 during validation period, r espectiv ely. This sug ges2 ted that the calibrated model can appr ox imately r eflect t he char act eristics of runo ff in the study ar ea, indicating the displayed best applicability of SWAT model in the w atershed. Mor eover, the sensitivity analysis of the main parameters based o n the vali2 dated hy dr olog ical mo del indicated that GWQMN ( threshold of shallow g r oundwater r egr ession flow) and CN2 ( number of SCS runo ff cur ves) w ere the most impo rtant par ameters show ed sig nificant effect o n the model r esults.
[中图分类号]
[基金项目]
国家自然科学基金( 41772254)