滇池西岸山地区域SCS-CN模型优化

李金梅; 周京春; 王金亮

doi:10.13961/j.cnki.stbctb.20230525.001

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滇池西岸山地区域SCS-CN模型优化

试验研究

- 滇池西岸山地区域SCS-CN模型优化
- Optimization of SCS-CN Model in a Mountainous Area on West Bank of Dianchi Lake
- 水土保持通报 2023年43卷第3期页码：139-147
- 作者机构：
  
  1. 云南师范大学地理学部,云南,昆明,650500
  2. 云南省高校资源与环境遥感重点实验室,云南,昆明,650500
  3. 云南省地理空间信息技术工程技术研究中心,云南,昆明,650500
- 作者简介：
- 基金信息：
  
  国家重点研发计划政府间/港澳台重点专项项目“利用地理空间技术监测和评估土地利用/土地覆被变化对区域生态安全的影响”(2018YFE0184300)
- DOI：10.13961/j.cnki.stbctb.20230525.001
  中图分类号： P334;P338;P333.1
- 纸质出版：2023
- 稿件说明：
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李金梅, 周京春, 王金亮. 滇池西岸山地区域SCS-CN模型优化[J]. 水土保持通报, 2023,43(3):139-147.

Li Jinmei, Zhou Jingchun, Wang Jinliang. Optimization of SCS-CN Model in a Mountainous Area on West Bank of Dianchi Lake[J]. Bulletin of Soiland Water Conservation, 2023, 43(3): 139-147.
李金梅, 周京春, 王金亮. 滇池西岸山地区域SCS-CN模型优化[J]. 水土保持通报, 2023,43(3):139-147. DOI： 10.13961/j.cnki.stbctb.20230525.001.

Li Jinmei, Zhou Jingchun, Wang Jinliang. Optimization of SCS-CN Model in a Mountainous Area on West Bank of Dianchi Lake[J]. Bulletin of Soiland Water Conservation, 2023, 43(3): 139-147. DOI： 10.13961/j.cnki.stbctb.20230525.001.

摘要

[目的] 模拟计算滇池西岸山洪产流量，为该区面山截洪设施的修建，减少山洪灾害和保护滇池水环境提供科学决策的依据。[方法] 基于SCS-CN产流模型，选取昆明滇池西岸山地区域2019

2020年的33场实测降雨径流数据，通过坡度结合前期影响雨量对CN值进行分级优化设定。采用穷举法对λ进行优化取值。再以2021年的19场实测降雨径流数据验证优化SCS-CN模型的模拟精度及其参数适用性。[结果] ①采用坡度及前期影响雨量分级优化得到的CN值仅适用于降雨量＜30 mm的中小型降雨；对于降雨量≥30 mm的强降雨，需根据场次降雨前5 d的降雨总量采用线性内插法对标准SCS-CN模型中AMC等级进行修改，再确定对应的坡度CN修正值。②适合滇池西岸山地区域中小型降雨和强降雨的最佳初损系数λ值分别为0.15，0.2。③经验证，中小型降雨和强降雨下的NSE值分别为0.852 2，0.797 8，模型合格率分别为93.33%和75%。[结论] 优化的SCS-CN模型用于滇池西岸山地区域＜30 mm的中小型降雨和≥30 mm的强降雨情况下的产流计算是可行的，可为该区地表径流预测及SCS-CN模型的进一步优化提供科学依据和理论参考。

Abstract

[Objective] The mountain flood runoff on the west bank of Dianchi Lake was simulated and calculated in order to provide a scientific basis for constructing flood interception facilities

reducing mountain flood disasters

and protecting the water environment of Dianchi Lake.[Methods] We used the SCS-CN runoff model with 33 field-measured rainfall-runoff datasets for the mountainous area on the west bank of Dianchi Lake in Kunming City in 2019 and 2020. The curve number (CN) value was optimized and set according to the slope combined with previous rainfall. The initial abstraction coefficient (λ) was optimized by the exhaust method. Simulation accuracy and parameter applicability for the optimized SCS-CN model were verified by 19 field-measured rainfall-runoff datasets in 2021.[Results] ① The CN value obtained by the slope and previous rainfall classification optimization was only suitable for small and medium rainfall amounts (<30 mm). For heavy rainfall (≥ 30 mm)

the antecedent moisture condition (AMC) in the standard SCS-CN model should be modified by linear interpolation according to the total rainfall amount in the previous five days

and then the corresponding slope CN correction value should be determined. ② The optimal λ values for small and medium rainfall events and for heavy rainfall events in the mountainous area on the west bank of Dianchi Lake were 0.15 and 0.20

respectively. ③ The NSE values after model verification for small and medium rainfall and for heavy rainfall were 0.852 2 and 0.797 8

respectively

and the model accuracy rates were 93.33% and 75%

respectively.[Conclusion] The optimized SCS-CN model was considered to be feasible for calculating runoff under the conditions of small and medium rainfall (<30 mm) and heavy rainfall (≥ 30 mm) in the mountainous area on the west bank of Dianchi Lake

and therefore can provide a scientific basis and theoretical reference for the prediction of surface runoff and the further optimization of the SCS-CN model in this area.

关键词

Keywords

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