基于HEC-HMS模型的兰江流域径流预测

唐中楠; 杨国丽; 李军; 刘鹏霄

doi:10.13961/j.cnki.stbctb.20210809.002

您当前的位置：

首页 >

文章列表页 >

基于HEC-HMS模型的兰江流域径流预测

试验研究

- 基于HEC-HMS模型的兰江流域径流预测
- Runoff Prediction in Lanjiang River Basin Based on HEC-HMS Model
- 水土保持通报 2021年41卷第5期页码：137-145
- 作者机构：
  
  河北建筑工程学院河北省水质工程与水资源综合利用重点实验室,河北,张家口,075000
- 作者简介：
- 基金信息：
  
  河北省科技厅项目“河北建筑工程学院院士工作站建设专项”（199A4201H）;河北省教育厅青年资助项目（QN2020424）;河北省教育厅重点项目（ZD20180202）
- DOI：10.13961/j.cnki.stbctb.20210809.002
  中图分类号： TV121
- 纸质出版：2021
- 稿件说明：
移动端阅览
唐中楠, 杨国丽, 李军, 等. 基于HEC-HMS模型的兰江流域径流预测[J]. 水土保持通报, 2021,41(5):137-145.

Tang Zhongnan, Yang Guoli, Li Jun, et al. Runoff Prediction in Lanjiang River Basin Based on HEC-HMS Model[J]. Bulletin of Soiland Water Conservation, 2021, 41(5): 137-145.
唐中楠, 杨国丽, 李军, 等. 基于HEC-HMS模型的兰江流域径流预测[J]. 水土保持通报, 2021,41(5):137-145. DOI： 10.13961/j.cnki.stbctb.20210809.002.

Tang Zhongnan, Yang Guoli, Li Jun, et al. Runoff Prediction in Lanjiang River Basin Based on HEC-HMS Model[J]. Bulletin of Soiland Water Conservation, 2021, 41(5): 137-145. DOI： 10.13961/j.cnki.stbctb.20210809.002.

摘要

[目的

]

分析兰江流域径流对气候变化的水文过程响应，为区域水资源可持续发展和防洪抗旱提供科学基础。[方法

]

利用2015—2018年日降雨径流过程和6场暴雨洪水过程率定并验证HEC-HMS水文模型在该流域的适用性；基于SDSM统计降尺度模型，对2030—2100年CanESM2模式下RCP2.6，RCP4.5和RCP8.53种情景的气候数据进行降尺度，生成兰江流域6个气象站点未来日降水序列以预测未来气候变化下的径流响应。[结果

]

HEC-HMS模型对场次洪水和逐日径流模拟的相关系数平均值达到0.89，0.77，平均效率系数达到0.86，0.76；RCP2.6情景下研究区面降水量较于基准期（2015—2018年）减小0.82%，在RCP4.5，RCP8.5情景下分别增大6.18%，18.17%；RCP2.6，RCP4.5，RCP8.53种情景下多年平均径流相较于基准期分别增幅为17.00%，26.22%，41.93%。[结论

]

HEC-HMS模型在兰江流域有较好的适用性；未来兰江流域径流呈显著上升趋势，增幅程度随辐射强迫度的增加同步增大。当辐射强迫度升高至8.5 W/m

时，流域径流量平均每10 a上升49.49 m

/s。预计21世纪末多年平均径流量达到1 101 m

/s，年径流变化起伏剧烈，汛期径流占全年比例较高，旱涝事件趋于频繁，对人民福祉威胁较大。

Abstract

[Objective] Runoff responses to climate changes in Lanjiang River basin were analyzed in an effort to provide a scientific basis for improving sustainable water resources

flood control

and drought resistance.[Methods] The applicability of the HEC-HMS hydrological model in this basin was determined by calibrating the processes of daily rainfall and runoff

in addition to six processes of rainstorms and floods from 2015 to 2018. Based on the statistical downscaling model (SDSM)

the climate data of three climate change scenarios (RCP 2.6

RCP 4.5

and RCP 8.5) under the CANESM2 model from 2030 to 2100 were downscaled for generating future daily precipitation time series at six meteorological stations in Lanjiang River basin in order to predict the runoff in response to future climate changes.[Results] The average correlation coefficients of the HEC-HMS model for floods and daily runoff simulations were 0.89 and 0.77

respectively. The average efficiency coefficients of the HEC-HMS model for floods and daily runoff simulations were 0.86 and 0.76

respectively. Precipitation in the study area under the RCP2.6 scenario decreased by 0.82% compared with the base period (2015-2018)

and increased by 6.18% and 18.17% under the RCP4.5 and RCP8.5 scenarios

respectively. Average annual runoff under the RCP2.6

RCP4.5

and RCP8.5 scenarios increased by 17.00%

26.22%

and 41.93%

respectively

compared with the base period.[Conclusion] The HEC-HMS model is applicable for runoff simulation in the Lanjiang River basin. In the future

runoff in the Lanjiang River basin will show a significant upward trend

and increase synchronously with the enhancement of radiation forcing. When radiative forcing increases to 8.5 W/m2

runoff will increase by 49.49 m3/s every 10 years

and predictably

the average annual runoff will reach 1 101 m3/s at the end of the 21st century. Additionally

annual runoff will fluctuate sharply

runoff in the flood season will account for a higher proportion of the year

and drought and flood events will tend to be frequent.

关键词

Keywords

references

董思言, 高学杰.长期气候变化:IPCC第五次评估报告解读[J].气候变化研究进展, 2014, 10(1):56-59.

Zhang Yuqing, You Qinglong, Chen Changchun, et al.Impacts of climate change on streamflows under RCP scenarios:A case study in Xin River basin, China[J]. Atmospheric Research, 2016, 178/179:521-534.

Wang Jucui, Huo Aidi, Zhang Xuezhen, et al. Prediction of the response of groundwater recharge to climate changes in Heihe River basin, China[J]. Environmental Earth Sciences, 2019, 79(1):1-16.

冯禹, 崔宁博, 龚道枝, 等.用统计降尺度模型预测川中丘陵区参考作物蒸散量[J].农业工程学报, 2016, 32(S1):71-79.

刘永和, 郭维栋, 冯锦明, 等.气象资料的统计降尺度方法综述[J].地球科学进展, 2011, 26(8):837-847.

董磊华, 熊立华, 于坤霞, 等.气候变化与人类活动对水文影响的研究进展[J].水科学进展, 2012, 23(2):278-285.

高玉芳, 陈耀登, 蒋义芳, 等. DEM数据源及分辨率对HEC-HMS水文模拟的影响[J].水科学进展, 2015, 26(5):624-630.

郭静, 王宁, 粟晓玲.气候变化下石羊河流域上游产流区的径流响应研究[J].西北农林科技大学学报(自然科学版), 2016, 44(12):211-218.

刘梅, 吕军.我国东部河流水文水质对气候变化响应的研究[J].环境科学学报, 2015, 35(1):108-117.

张静, 杨明祥, 雷晓辉, 等.基于HEC-HMS的青狮潭水库入库洪水预报研究[J].水土保持通报, 2017, 37(4):225-229, 235.

Abdessamed D, Abderrazak B. Coupling HEC-RAS and HEC-HMS in rainfall-runoff modeling and evaluating floodplain inundation maps in arid environments:Case study of Ain Sefra city, Ksour Mountain. SW of Algeria[J]. Environmental Earth Sciences, 2019, 78(19):586-603.

Mahmood R, Jia Shaofeng. Assessment of hydro-climatic trends and causes of dramatically declining stream flow to Lake Chad, Africa, using a hydrological approach[J]. Science of the Total Environment, 2019, 675:122-140.

袁玉, 方国华, 陆承璇, 等.基于景观生态学的城市化背景下洪灾风险评估[J].地理学报, 2020, 75(9):1921-1933.

田竞, 夏军, 张艳军, 等. HEC-HMS模型在官山河流域的应用研究[J].武汉大学学报(工学版), 2021, 54(1):8-14.

夏芳.钱塘江流域气候变化及其对水文径流的影响[D].浙江杭州:浙江大学, 2016.

刘莉, Krewinkel B C, Booij M J, 等.兰江流域降雨量与气候指数的相关性研究[J].浙江大学学报(工学版), 2018, 52(12):2332-2341.

郑鹏, 林韵, 潘文斌, 等.基于HEC-HMS模型的八一水库流域洪水重现期研究[J].生态学报, 2013, 33(4):1268-1275.

邹杨, 胡国华, 于泽兴, 等. HEC-HMS模型在武水流域山洪预报中的应用[J].中国水土保持科学, 2018, 16(2):95-102.

桂晗亮, 张春萍, 武治国, 等. HSPF在热带沿海流域水文模拟中的应用[J].水土保持通报, 2020, 40(6):115-120, 129.

董立俊, 董晓华, 曾强, 等.气候变化条件下雅砻江流域未来径流变化趋势研究[J].气候变化研究进展, 2019, 15(6):596-606.

刘昌明, 刘文彬, 傅国斌, 等.气候影响评价中统计降尺度若干问题的探讨[J].水科学进展, 2012, 23(3):427-437.

刘卫林, 熊翰林, 刘丽娜, 等.基于CMIP5模式和SDSM的赣江流域未来气候变化情景预估[J].水土保持研究, 2019, 26(2):145-152.

林朝晖, 杨笑宇, 吴成来, 等. CMIP5模式对中国东部夏季不同强度降水气候态和年代际变化的模拟能力评估[J].气候与环境研究, 2018, 23(1):1-25.

Xuan Weidong, Ma Chong, Kang Lili, et al. Evaluating historical simulations of CMIP5 GCMs for key climatic variables in Zhejiang Province, China[J]. Theoretical and Applied Climatology, 2017, 128(1/2):207-222.

郝丽娜, 粟晓玲, 王宁.基于统计降尺度模型的河西走廊未来气温和降水的时空变化[J].西北农林科技大学学报(自然科学版), 2015, 43(10):219-228.

初祁, 徐宗学, 蒋昕昊.两种统计降尺度模型在太湖流域的应用对比[J].资源科学, 2012, 34(12):2323-2336.

娄伟, 李致家, 刘玉环.多模式下泾河上游流域未来降水变化预估[J].南水北调与水利科技(中英文), 2020, 18(6):1-16.

任婧宇, 赵俊侠, 马红斌, 等.2015-2100年黄土高原四季气候变化的时空分布趋势预测[J].水土保持通报, 2019, 39(5):262-271.

方思达, 刘敏, 任永建.南水北调中线工程水源区和受水区旱涝特征及风险预估[J].水土保持通报, 2018, 38(6):263-267, 276.

Zhang Xujie, Xu Yueping, Fu Guangtao. Uncertainties in SWAT extreme flow simulation under climate change[J]. Journal of Hydrology, 2014, 515:205-222.

Xia Fang, Liu Xingmei, Xu Jianming, et al. Trends in the daily and extreme temperatures in the Qiantang River basin, China[J]. International Journal of Climatology, 2015, 35(1):57-68.

赵姹, 李志, 刘文兆. GCM降尺度预测泾河流域未来降水变化[J].水土保持研究, 2014, 21(1):23-28.

郝振纯, 苏振宽.土地利用变化对海河流域典型区域的径流影响[J].水科学进展, 2015, 26(4):491-499.

浏览量

831

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

SWAT径流模拟及其对流域内地形参数变化的响应研究

SCS模型在泥石流多发区降雨—径流模拟中的应用——以云南省蒋家沟流域为例

不同土地利用变化情景下的洪汝河流域水文响应

HEC-HMS水文模型在数据稀缺山区流域中的应用——以乌鲁木齐河流域为例

不同改良剂对滨海盐渍土盐分离子及玉米生长的影响