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清华大学学报(自然科学版)  2019, Vol. 59 Issue (12): 975-980    DOI: 10.16511/j.cnki.qhdxxb.2019.26.025
  水利水电工程 本期目录 | 过刊浏览 | 高级检索 |
面向逐日产沙模拟的SWAT模型封闭与检验
李二辉, 王冰洁, 傅旭东
清华大学 水沙科学与水利水电工程国家重点实验室, 北京 100084
Closure and validation of a SWAT model for daily scale sediment simulations
LI Erhui, WANG Bingjie, FU Xudong
State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
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摘要 针对SWAT(soil and water assessment tool)模型逐日产沙模拟中含沙量-流速关系的尺度匹配问题,给出了日尺度产沙模拟的最大含沙量封闭关系。该文采用黄河中游砒砂岩区9个水文站长系列实测水沙资料,确定日输沙率-日流量的幂函数型关系曲线,提供了SWAT模型日尺度最大含沙量的封闭关系。并将封闭的SWAT模型用于皇甫川流域水沙产输过程模拟,采用空间嵌套的皇甫站和沙圪堵站实测资料进行模型验证。结果表明:皇甫站率定期和验证期日输沙过程的Nash-Sutcliffe效率系数(Nash-Sutcliffe efficiency coefficient,NSE)分别为0.70和0.66,决定系数R2分别为0.74和0.68;沙圪堵站率定期和验证期NSE分别为0.78和0.72,R2分别为0.78和0.74;未进行封闭模型的沙圪堵站率定期和验证期NSE分别为0.36和0.26,R2分别为0.39和0.26。表明封闭后的SWAT模型显著提高了模拟效率,能够用于黄土高原砒砂岩地区泥沙逐日过程模拟。
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李二辉
王冰洁
傅旭东
关键词 SWAT模型输沙率-流量关系曲线封闭关系日尺度皇甫川流域    
Abstract:A closed relationship for daily maximum sediment concentration was developed to solve the scale matching problem between the sediment concentration and the flow velocity in the SWAT model. A power function was used to fit the daily flow rate to the sedimentation flux at 9 gauging stations located in the soft sandstone region of the middle Yellow River to provide a closed relationship for the daily sedimentation rate. The closed SWAT model was then used to simulate the sediment transport in the Huangfuchuan watershed of the Yellow River. The model was validated by comparing the observed and simulated sediment loads at the Huangfu and Shagedu stations. The results showed that the Nash-Sutcliffe efficiency coefficient (NSE) was 0.70 and the determination coefficient (R2) was 0.74 during the calibration period and were equal to 0.66 and 0.68 during the validation period for the daily scale sediment load at the Huangfu station. The closed SWAT model predictions at the Shagedu station correlated with the observed sediment load with NSE=0.78 and R2=0.78 for the calibration period and NSE=0.72 and R2=0.74 for the validation period. The unclosed SWAT model had NSE=0.36 and R2=0.39 for the calibration period and NSE=0.26 and R2=0.26 for the validation period at the Shagedu station. The results indicate that the closed SWAT model improves the simulation accuracy for sediment transport within the basin to improve applications of the SWAT model in the soft sandstone region for sediment simulation.
Key wordsSWAT model    sediment rating curve    closed relationship    daily scale    Huangfuchuan basin
收稿日期: 2019-03-18      出版日期: 2019-12-19
基金资助:傅旭东,教授,E-mail:xdfu@tsinghua.edu.cn
引用本文:   
李二辉, 王冰洁, 傅旭东. 面向逐日产沙模拟的SWAT模型封闭与检验[J]. 清华大学学报(自然科学版), 2019, 59(12): 975-980.
LI Erhui, WANG Bingjie, FU Xudong. Closure and validation of a SWAT model for daily scale sediment simulations. Journal of Tsinghua University(Science and Technology), 2019, 59(12): 975-980.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2019.26.025  或          http://jst.tsinghuajournals.com/CN/Y2019/V59/I12/975
  图1 输沙率-流量幂函数方程系数a和指数b与控制面积关系
  图2 ( 网络版彩图) 研究区地理位置和雨量站、水文站及气象站分布图
  图3 ( 网络版彩图) 皇甫站日输沙量模拟值与 实测值对比
  图4 ( 网络版彩图) 沙圪堵站日输沙量 模拟值与实测值对比
  图5 ( 网络版彩图) 沙圪堵站未封闭模型输 沙量模拟值与实测值对比
  
[1] 冉大川, 刘斌, 罗全华, 等. 泾河流域水沙变化水文分析[J]. 人民黄河, 2001, 23(2):9-11. RAN D C, LIU B, LUO Q H, et al. Hydrological analysis of water and sediment evolution in Jing River basin[J]. Yellow River, 2001, 23(2):9-11. (in Chinese)
[2] 徐宗学, 程磊. 分布式水文模型研究与应用进展[J]. 水利学报, 2010, 41(9):1009-1017. XU Z X, CHENG L. Progress on studies and applications of the distributed hydrological models[J]. Journal of Hydraulic Engineering, 2010, 41(9):1009-1017. (in Chinese)
[3] PATI A, SEN S, PERUMAL M. Modified channel-routing scheme for SWAT model[J]. Journal of Hydrologic Engineering, 2018, 23(6):04018019.
[4] FURL C, SHARIF H, JEONG J. Analysis and simulation of large erosion events at central Texas unit source watersheds[J]. Journal of Hydrology, 2015, 527:494-504.
[5] ADHIKARI U, NEJADHASHEMI A P. Impacts of climate change on water resources in Malawi[J]. Journal of Hydrologic Engineering, 2016, 21(11):05016026.
[6] MARHAENTO H, BOOIJ M J, RIENTJES T H M, et al. Attribution of changes in the water balance of a tropical catchment to land use change using the SWAT model[J]. Hydrological Processes, 2017, 31(11):2029-2040.
[7] DURU U, ARABI M, WOHL E E. Modeling stream flow and sediment yield using the SWAT model:A case study of Ankara River basin, Turkey[J]. Physical Geography, 2018, 39(3):264-289.
[8] VERMA S, BHATTARAI R, BOSCH N S, et al. Climate change impacts on flow, sediment and nutrient export in a great lakes watershed using SWAT[J]. Clean-Soil Air Water, 2015, 43(11):1464-1474.
[9] YESUF H M, ASSEN M, ALAMIREW T, et al. Modeling of sediment yield in Maybar gauged watershed using SWAT, northeast Ethiopia[J]. Catena, 2015, 127:191-205.
[10] WILLIAMS J R. SPNM, a model for predicting sediment, phosphorus, and nitrogen yields from agricultural basins[J]. Water Resources Bulletin, 1980, 16(5):843-848.
[11] QIU L J, ZHENG F L, YIN R S. SWAT-based runoff and sediment simulation in a small watershed, the loessial hilly-gullied region of China:Capabilities and challenges[J]. International Journal of Sediment Research, 2012, 27(2):226-234.
[12] DUTTA S, SEN D. Application of SWAT model for predicting soil erosion and sediment yield[J]. Sustainable Water Resources Management, 2018, 4(3):447-468.
[13] YU X, XIE X H, MENG S S. Modeling the responses of water and sediment discharge to climate change in the upper Yellow River basin, China[J]. Journal of Hydrologic Engineering, 2017, 22(12):05017026.
[14] LI E H, MU X M, ZHAO G J, et al. Effects of check dams on runoff and sediment load in a semi-arid river basin of the Yellow River[J]. Stochastic Environmental Research and Risk Assessment, 2017, 31(7):1791-1803.
[15] YANG G F, CHEN Z Y, YU F L, et al. Sediment rating parameters and their implications:Yangtze River, China[J]. Geomorphology, 2007, 85(3-4):166-175.
[16] HU B Q, WANG H J, YANG Z S, et al. Temporal and spatial variations of sediment rating curves in the Changjiang (Yangtze River) basin and their implications[J]. Quaternary International, 2011, 230(1-2):34-43.
[17] BUSSI G, DADSON S J, BOWES M J, et al. Seasonal and interannual changes in sediment transport identified through sediment rating curves[J]. Journal of Hydrologic Engineering, 2017, 22(2):06016016.
[18] ZHANG S Y, CHEN D, LI F X, et al. Evaluating spatial variation of suspended sediment rating curves in the middle Yellow River basin, China[J]. Hydrological Processes, 2018, 32(11):1616-1624.
[19] 高健健, 穆兴民, 孙文义. 1981-2012年黄土高原植被覆盖度时空变化特征[J]. 中国水土保持, 2016, (7):52-56. GAO J J, MU X M, SUN W Y. Temporal and spatial variation characteristics of vegetation coverage in the loess plateau from 1981 to 2012[J]. Soil and Water Conservation in China, 2016, (7):52-56. (in Chinese)
[20] 江忠善, 王志强, 刘志. 黄土丘陵区小流域土壤侵蚀空间变化定量研究[J]. 土壤侵蚀与水土保持学报, 1996, 2(1):1-9. JIANG Z S, WANG Z Q, LIU Z. Quantitative study on spatial variation of soil erosion in a small watershed in the loess Hilly Region[J]. Journal of Soil and Water Conservation, 1996, 2(1):1-9. (in Chinese)
[21] 李斌兵, 郑粉莉, 龙栋材, 等. 基于GIS纸坊沟小流域土壤侵蚀强度空间分布[J]. 地理科学, 2009, 29(1):105-110. LI B B, ZHENG F L, LONG D C, et al. Spatial distribution of soil erosion intensityin Zhifanggou small watershed based on GIS[J]. Scientia Geographica Sinica, 2009, 29(1):105-110. (in Chinese)
[22] 郑捷, 李光永, 韩振中, 等. 改进的SWAT模型在平原灌区的应用[J]. 水利学报, 2011, 42(1):88-97. ZHENG J, LI G Y, HAN Z Z, et al. Application of modified SWAT model in plain irrigation district[J]. Journal of Hydraulic Engineering, 2011, 42(1):88-97. (in Chinese)
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